Impact analysis of two kinds of failure strategies in Beijing road transportation network

NASA Astrophysics Data System (ADS)

Zhang, Zundong; Xu, Xiaoyang; Zhang, Zhaoran; Zhou, Huijuan

The Beijing road transportation network (BRTN), as a large-scale technological network, exhibits very complex and complicate features during daily periods. And it has been widely highlighted that how statistical characteristics (i.e. average path length and global network efficiency) change while the network evolves. In this paper, by using different modeling concepts, three kinds of network models of BRTN namely the abstract network model, the static network model with road mileage as weights and the dynamic network model with travel time as weights — are constructed, respectively, according to the topological data and the real detected flow data. The degree distribution of the three kinds of network models are analyzed, which proves that the urban road infrastructure network and the dynamic network behavior like scale-free networks. By analyzing and comparing the important statistical characteristics of three models under random attacks and intentional attacks, it shows that the urban road infrastructure network and the dynamic network of BRTN are both robust and vulnerable.

GIS Data Based Automatic High-Fidelity 3D Road Network Modeling

NASA Technical Reports Server (NTRS)

Wang, Jie; Shen, Yuzhong

2011-01-01

3D road models are widely used in many computer applications such as racing games and driving simulations_ However, almost all high-fidelity 3D road models were generated manually by professional artists at the expense of intensive labor. There are very few existing methods for automatically generating 3D high-fidelity road networks, especially those existing in the real world. This paper presents a novel approach thai can automatically produce 3D high-fidelity road network models from real 2D road GIS data that mainly contain road. centerline in formation. The proposed method first builds parametric representations of the road centerlines through segmentation and fitting . A basic set of civil engineering rules (e.g., cross slope, superelevation, grade) for road design are then selected in order to generate realistic road surfaces in compliance with these rules. While the proposed method applies to any types of roads, this paper mainly addresses automatic generation of complex traffic interchanges and intersections which are the most sophisticated elements in the road networks

Comparative analysis of the performance of One-Way and Two-Way urban road networks

NASA Astrophysics Data System (ADS)

Gheorghe, Carmen

2017-10-01

The fact that the number of vehicles is increasing year after year represents a challenge in road traffic management because it is necessary to adjust the road traffic, in order to prevent any incidents, using mostly the same road infrastructure. At this moment one-way road network provides efficient traffic flow for vehicles but it is not ideal for pedestrians. Therefore, a proper solution must be found and applied when and where it is necessary. Replacing one-way road network with two-way road network may be a viable solution especially if in the area is high pedestrian traffic. The paper aims to highlight the influence of both, one-way and two-way urban road networks through an experimental research which was performed by using traffic data collected in the field. Each of the two scenarios analyzed were based on the same traffic data, the same geometrical conditions of the road (lane width, total road segment width, road slopes, total length of the road network) and also the same signaling conditions (signalised intersection or roundabout). The analysis which involves two-way scenario reveals changes in the performance parameters like delay average, stops average, delay stop average and vehicle speed average. Based on the values obtained, it was possible to perform a comparative analysis between the real, one-way, scenario and the theoretical, two-way, scenario.

Contraction star-shaped cracks: From 90 degrees to 120 degrees crack intersections

NASA Astrophysics Data System (ADS)

Lazarus, Veronique; Gauthier, Georges

2010-05-01

Giant's Causeway, Port Arthur tessellated pavement, Bimini Road, Mars polygons, fracture networks in permafrost, septarias are some more or less known examples of self-organized crack patterns that have intrigued people through out history. These pavements are formed by constrained shrinking of the media due, for instance, to cooling or drying leading to fracture. The crack networks form in some conditions star-shaped cracks with mostly 90 or 120 degrees angles. Here, we report experiments allowing to control the transition between 90 and 120 degrees. We show that the transition is governed by the linear elastic fracture mechanics energy minimization principle, hence by two parameters: the cell size and the Griffith's length (balance between the energy needed to create cracks and to deform the material elastically). The results are used to infer new informations on tessellated pavements formation.

Spatiotemporal responses of dengue fever transmission to the road network in an urban area.

PubMed

Li, Qiaoxuan; Cao, Wei; Ren, Hongyan; Ji, Zhonglin; Jiang, Huixian

2018-07-01

Urbanization is one of the important factors leading to the spread of dengue fever. Recently, some studies found that the road network as an urbanization factor affects the distribution and spread of dengue epidemic, but the study of relationship between the distribution of dengue epidemic and road network is limited, especially in highly urbanized areas. This study explores the temporal and spatial spread characteristics of dengue fever in the distribution of road network by observing a dengue epidemic in the southern Chinese cities. Geographic information technology is used to extract the spatial location of cases and explore the temporal and spatial changes of dengue epidemic and its spatial relationship with road network. The results showed that there was a significant "severe" period in the temporal change of dengue epidemic situation, and the cases were mainly concentrated in the vicinity of narrow roads, the spread of the epidemic mainly along the high-density road network area. These results show that high-density road network is an important factor to the direction and scale of dengue epidemic. This information may be helpful to the development of related epidemic prevention and control strategies. Copyright © 2018. Published by Elsevier B.V.

An expert-based approach to forest road network planning by combining Delphi and spatial multi-criteria evaluation.

PubMed

Hayati, Elyas; Majnounian, Baris; Abdi, Ehsan; Sessions, John; Makhdoum, Majid

2013-02-01

Changes in forest landscapes resulting from road construction have increased remarkably in the last few years. On the other hand, the sustainable management of forest resources can only be achieved through a well-organized road network. In order to minimize the environmental impacts of forest roads, forest road managers must design the road network efficiently and environmentally as well. Efficient planning methodologies can assist forest road managers in considering the technical, economic, and environmental factors that affect forest road planning. This paper describes a three-stage methodology using the Delphi method for selecting the important criteria, the Analytic Hierarchy Process for obtaining the relative importance of the criteria, and finally, a spatial multi-criteria evaluation in a geographic information system (GIS) environment for identifying the lowest-impact road network alternative. Results of the Delphi method revealed that ground slope, lithology, distance from stream network, distance from faults, landslide susceptibility, erosion susceptibility, geology, and soil texture are the most important criteria for forest road planning in the study area. The suitability map for road planning was then obtained by combining the fuzzy map layers of these criteria with respect to their weights. Nine road network alternatives were designed using PEGGER, an ArcView GIS extension, and finally, their values were extracted from the suitability map. Results showed that the methodology was useful for identifying road that met environmental and cost considerations. Based on this work, we suggest future work in forest road planning using multi-criteria evaluation and decision making be considered in other regions and that the road planning criteria identified in this study may be useful.

Automated road network extraction from high spatial resolution multi-spectral imagery

NASA Astrophysics Data System (ADS)

Zhang, Qiaoping

For the last three decades, the Geomatics Engineering and Computer Science communities have considered automated road network extraction from remotely-sensed imagery to be a challenging and important research topic. The main objective of this research is to investigate the theory and methodology of automated feature extraction for image-based road database creation, refinement or updating, and to develop a series of algorithms for road network extraction from high resolution multi-spectral imagery. The proposed framework for road network extraction from multi-spectral imagery begins with an image segmentation using the k-means algorithm. This step mainly concerns the exploitation of the spectral information for feature extraction. The road cluster is automatically identified using a fuzzy classifier based on a set of predefined road surface membership functions. These membership functions are established based on the general spectral signature of road pavement materials and the corresponding normalized digital numbers on each multi-spectral band. Shape descriptors of the Angular Texture Signature are defined and used to reduce the misclassifications between roads and other spectrally similar objects (e.g., crop fields, parking lots, and buildings). An iterative and localized Radon transform is developed for the extraction of road centerlines from the classified images. The purpose of the transform is to accurately and completely detect the road centerlines. It is able to find short, long, and even curvilinear lines. The input image is partitioned into a set of subset images called road component images. An iterative Radon transform is locally applied to each road component image. At each iteration, road centerline segments are detected based on an accurate estimation of the line parameters and line widths. Three localization approaches are implemented and compared using qualitative and quantitative methods. Finally, the road centerline segments are grouped into a road network. The extracted road network is evaluated against a reference dataset using a line segment matching algorithm. The entire process is unsupervised and fully automated. Based on extensive experimentation on a variety of remotely-sensed multi-spectral images, the proposed methodology achieves a moderate success in automating road network extraction from high spatial resolution multi-spectral imagery.

A Tool for Modelling the Probability of Landslides Impacting Road Networks

NASA Astrophysics Data System (ADS)

Taylor, Faith E.; Santangelo, Michele; Marchesini, Ivan; Malamud, Bruce D.; Guzzetti, Fausto

2014-05-01

Triggers such as earthquakes or heavy rainfall can result in hundreds to thousands of landslides occurring across a region within a short space of time. These landslides can in turn result in blockages across the road network, impacting how people move about a region. Here, we show the development and application of a semi-stochastic model to simulate how landslides intersect with road networks during a triggered landslide event. This was performed by creating 'synthetic' triggered landslide inventory maps and overlaying these with a road network map to identify where road blockages occur. Our landslide-road model has been applied to two regions: (i) the Collazzone basin (79 km2) in Central Italy where 422 landslides were triggered by rapid snowmelt in January 1997, (ii) the Oat Mountain quadrangle (155 km2) in California, USA, where 1,350 landslides were triggered by the Northridge Earthquake (M = 6.7) in January 1994. For both regions, detailed landslide inventory maps for the triggered events were available, in addition to maps of landslide susceptibility and road networks of primary, secondary and tertiary roads. To create 'synthetic' landslide inventory maps, landslide areas (AL) were randomly selected from a three-parameter inverse gamma probability density function, consisting of a power law decay of about -2.4 for medium and large values of AL and an exponential rollover for small values of AL. The number of landslide areas selected was based on the observed density of landslides (number of landslides km-2) in the triggered event inventories. Landslide shapes were approximated as ellipses, where the ratio of the major and minor axes varies with AL. Landslides were then dropped over the region semi-stochastically, conditioned by a landslide susceptibility map, resulting in a synthetic landslide inventory map. The originally available landslide susceptibility maps did not take into account susceptibility changes in the immediate vicinity of roads, therefore our landslide susceptibility map was adjusted to further reduce the susceptibility near each road based on the road level (primary, secondary, tertiary). For each model run, we superimposed the spatial location of landslide drops with the road network, and recorded the number, size and location of road blockages recorded, along with landslides within 50 and 100 m of the different road levels. Network analysis tools available in GRASS GIS were also applied to measure the impact upon the road network in terms of connectivity. The model was performed 100 times in a Monte-Carlo simulation for each region. Initial results show reasonable agreement between model output and the observed landslide inventories in terms of the number of road blockages. In Collazzone (length of road network = 153 km, landslide density = 5.2 landslides km-2), the median number of modelled road blockages over 100 model runs was 5 (±2.5 standard deviation) compared to the mapped inventory observed number of 5 road blockages. In Northridge (length of road network = 780 km, landslide density = 8.7 landslides km-2), the median number of modelled road blockages over 100 model runs was 108 (±17.2 standard deviation) compared to the mapped inventory observed number of 48 road blockages. As we progress with model development, we believe this semi-stochastic modelling approach will potentially aid civil protection agencies to explore different scenarios of road network potential damage as the result of different magnitude landslide triggering event scenarios.

A STUDY ON PREPARING THE BCP FOR LOCAL ADMINISTRATION COSIDERING SUBSISTED RISK ANALYSIS OF ROAD NETWORK

NASA Astrophysics Data System (ADS)

Sakata, Akio; Ito, Norio; Kawamoto, Atsushi; Shiraki, Wataru

For road networks in mountain site which are very important infrastructures for rescue and support operations in disaster, a study on preparing the BCP for local administrations at less favored area considering subsisted risk analysis is performed. As a risk the stop of road networks caused by collapse of natural slop or cut slop is considered. The effects of the stop of road networks are analyzed and the important of preparing the BCP is demonstrated.

Repeatability of road pavement condition assessment based on three-dimensional analysis of linear accelerations of vehicles

NASA Astrophysics Data System (ADS)

Staniek, Marcin

2018-05-01

The article provides a discussion concerning a tool used for road pavement condition assessment based on signals of linear accelerations recorded with high sampling frequency for typical vehicles traversing the road network under real-life road traffic conditions. Specific relationships have been established for the sake of road pavement condition assessment, including identification of road sections of poor technical condition. The data thus acquired have been verified with regard to repeatability of estimated road pavement assessment indices. The data make it possible to describe the road network status against an area in which users of the system being developed move. What proves to be crucial in the assessment process is the scope of the data set based on multiple transfers within the road network.

Convolutional neural network for road extraction

NASA Astrophysics Data System (ADS)

Li, Junping; Ding, Yazhou; Feng, Fajie; Xiong, Baoyu; Cui, Weihong

2017-11-01

In this paper, the convolution neural network with large block input and small block output was used to extract road. To reflect the complex road characteristics in the study area, a deep convolution neural network VGG19 was conducted for road extraction. Based on the analysis of the characteristics of different sizes of input block, output block and the extraction effect, the votes of deep convolutional neural networks was used as the final road prediction. The study image was from GF-2 panchromatic and multi-spectral fusion in Yinchuan. The precision of road extraction was 91%. The experiments showed that model averaging can improve the accuracy to some extent. At the same time, this paper gave some advice about the choice of input block size and output block size.

Locating inefficient links in a large-scale transportation network

NASA Astrophysics Data System (ADS)

Sun, Li; Liu, Like; Xu, Zhongzhi; Jie, Yang; Wei, Dong; Wang, Pu

2015-02-01

Based on data from geographical information system (GIS) and daily commuting origin destination (OD) matrices, we estimated the distribution of traffic flow in the San Francisco road network and studied Braess's paradox in a large-scale transportation network with realistic travel demand. We measured the variation of total travel time Δ T when a road segment is closed, and found that | Δ T | follows a power-law distribution if Δ T < 0 or Δ T > 0. This implies that most roads have a negligible effect on the efficiency of the road network, while the failure of a few crucial links would result in severe travel delays, and closure of a few inefficient links would counter-intuitively reduce travel costs considerably. Generating three theoretical networks, we discovered that the heterogeneously distributed travel demand may be the origin of the observed power-law distributions of | Δ T | . Finally, a genetic algorithm was used to pinpoint inefficient link clusters in the road network. We found that closing specific road clusters would further improve the transportation efficiency.

Roads at risk - the impact of debris flows on road network reliability and vulnerability in southern Norway

NASA Astrophysics Data System (ADS)

Meyer, Nele Kristin; Schwanghart, Wolfgang; Korup, Oliver

2014-05-01

Norwegian's road network is frequently affected by debris flows. Both damage repair and traffic interruption generate high economic losses and necessitate a rigorous assessment of where losses are expected to be high and where preventive measures should be focused on. In recent studies, we have developed susceptibility and trigger probability maps that serve as input into a hazard calculation at the scale of first-order watersheds. Here we combine these results with graph theory to assess the impact of debris flows on the road network of southern Norway. Susceptibility and trigger probability are aggregated for individual road sections to form a reliability index that relates to the failure probability of a link that connects two network vertices, e.g., road junctions. We define link vulnerability as a function of traffic volume and additional link failure distance. Additional link failure distance is the extra length of the alternative path connecting the two associated link vertices in case the network link fails and is calculated by a shortest-path algorithm. The product of network reliability and vulnerability indices represent the risk index. High risk indices identify critical links for the Norwegian road network and are investigated in more detail. Scenarios demonstrating the impact of single or multiple debris flow events are run for the most important routes between seven large cities in southern Norway. First results show that the reliability of the road network is lowest in the central and north-western part of the study area. Road network vulnerability is highest in the mountainous regions in central southern Norway where the road density is low and in the vicinity of cities where the traffic volume is large. The scenarios indicate that city connections that have their shortest path via routes crossing the central part of the study area have the highest risk of route failure.

Response of moose to a high‐density road network

USGS Publications Warehouse

Wattles, David W.; Zeller, Katherine A.; DeStefano, Stephen

2018-01-01

Road networks and the disturbance associated with vehicle traffic alter animal behavior, movements, and habitat selection. The response of moose (Alces americanus) to roads has been documented in relatively rural areas, but less is known about moose response to roads in more highly roaded landscapes. We examined road‐crossing frequencies and habitat use of global positioning system (GPS)‐collared moose in Massachusetts, USA, where moose home ranges have road densities approximately twice that of previous studies. We compared seasonal road‐crossing frequencies of moose with a null movement model. We estimated moose travel speeds during road‐crossing events and compared them with speeds during other home range movements. To estimate the extent of the road effect zone and determine how roads influenced moose habitat use, we fit a third‐order resource selection function. With the exception of the lowest use road class (<10 vehicles/day), we found moose crossed roads less than expected based on the null movement model and frequency decreased with increasing road size and traffic. Moose crossed roads faster than they traveled during other times. This effect increased with increasing road use intensity. Overall, roads were a major factor determining what portions of Massachusetts moose used and how they moved among habitat patches. Our results suggest that moose in Massachusetts can adapt to a high‐density road network, but the road effect is still strongly negative and, in some cases, is more pronounced than in study areas with lower road densities. Future road construction and the expansion of road networks may have a large effect on moose and other wildlife.

A suite of tools for monitoring and assessing impacts of road networks and off-road vehicle activity on rangelands

USDA-ARS?s Scientific Manuscript database

Despite increasing amounts of transportation related activities on rangelands globally, few tools exist for assessing and monitoring impacts of roads, road networks and off-road vehicle traffic. This is in part due to an historical emphasis on grazing issues in rangelands and the complexity of monit...

Modelling the Probability of Landslides Impacting Road Networks

NASA Astrophysics Data System (ADS)

Taylor, F. E.; Malamud, B. D.

2012-04-01

During a landslide triggering event, the threat of landslides blocking roads poses a risk to logistics, rescue efforts and communities dependant on those road networks. Here we present preliminary results of a stochastic model we have developed to evaluate the probability of landslides intersecting a simple road network during a landslide triggering event and apply simple network indices to measure the state of the road network in the affected region. A 4000 x 4000 cell array with a 5 m x 5 m resolution was used, with a pre-defined simple road network laid onto it, and landslides 'randomly' dropped onto it. Landslide areas (AL) were randomly selected from a three-parameter inverse gamma probability density function, consisting of a power-law decay of about -2.4 for medium and large values of AL and an exponential rollover for small values of AL; the rollover (maximum probability) occurs at about AL = 400 m2 This statistical distribution was chosen based on three substantially complete triggered landslide inventories recorded in existing literature. The number of landslide areas (NL) selected for each triggered event iteration was chosen to have an average density of 1 landslide km-2, i.e. NL = 400 landslide areas chosen randomly for each iteration, and was based on several existing triggered landslide event inventories. A simple road network was chosen, in a 'T' shape configuration, with one road 1 x 4000 cells (5 m x 20 km) in a 'T' formation with another road 1 x 2000 cells (5 m x 10 km). The landslide areas were then randomly 'dropped' over the road array and indices such as the location, size (ABL) and number of road blockages (NBL) recorded. This process was performed 500 times (iterations) in a Monte-Carlo type simulation. Initial results show that for a landslide triggering event with 400 landslides over a 400 km2 region, the number of road blocks per iteration, NBL,ranges from 0 to 7. The average blockage area for the 500 iterations (A¯ BL) is about 3000 m2, which closely matches the value of A¯ L for the triggered landslide inventories. We further find that over the 500 iterations, the probability of a given number of road blocks occurring on any given iteration, p(NBL) as a function of NBL, follows reasonably well a three-parameter inverse gamma probability density distribution with an exponential rollover (i.e., the most frequent value) at NBL = 1.3. In this paper we have begun to calculate the probability of the number of landslides blocking roads during a triggering event, and have found that this follows an inverse-gamma distribution, which is similar to that found for the statistics of landslide areas resulting from triggers. As we progress to model more realistic road networks, this work will aid in both long-term and disaster management for road networks by allowing probabilistic assessment of road network potential damage during different magnitude landslide triggering event scenarios.

Overview of the new National Near-Road Air Quality Monitoring Network

EPA Science Inventory

In 2010, EPA promulgated new National Ambient Air Quality Standards (NAAQS) for nitrogen dioxide (NO2). As part of this new NAAQS, EPA required the establishment of a national near-road air quality monitoring network. This network will consist of one NO2 near-road monitoring st...

Comparison of Point Matching Techniques for Road Network Matching

NASA Astrophysics Data System (ADS)

Hackeloeer, A.; Klasing, K.; Krisp, J. M.; Meng, L.

2013-05-01

Map conflation investigates the unique identification of geographical entities across different maps depicting the same geographic region. It involves a matching process which aims to find commonalities between geographic features. A specific subdomain of conflation called Road Network Matching establishes correspondences between road networks of different maps on multiple layers of abstraction, ranging from elementary point locations to high-level structures such as road segments or even subgraphs derived from the induced graph of a road network. The process of identifying points located on different maps by means of geometrical, topological and semantical information is called point matching. This paper provides an overview of various techniques for point matching, which is a fundamental requirement for subsequent matching steps focusing on complex high-level entities in geospatial networks. Common point matching approaches as well as certain combinations of these are described, classified and evaluated. Furthermore, a novel similarity metric called the Exact Angular Index is introduced, which considers both topological and geometrical aspects. The results offer a basis for further research on a bottom-up matching process for complex map features, which must rely upon findings derived from suitable point matching algorithms. In the context of Road Network Matching, reliable point matches provide an immediate starting point for finding matches between line segments describing the geometry and topology of road networks, which may in turn be used for performing a structural high-level matching on the network level.

A Few Large Roads or Many Small Ones? How to Accommodate Growth in Vehicle Numbers to Minimise Impacts on Wildlife

PubMed Central

Rhodes, Jonathan R.; Lunney, Daniel; Callaghan, John; McAlpine, Clive A.

2014-01-01

Roads and vehicular traffic are among the most pervasive of threats to biodiversity because they fragmenting habitat, increasing mortality and opening up new areas for the exploitation of natural resources. However, the number of vehicles on roads is increasing rapidly and this is likely to continue into the future, putting increased pressure on wildlife populations. Consequently, a major challenge is the planning of road networks to accommodate increased numbers of vehicles, while minimising impacts on wildlife. Nonetheless, we currently have few principles for guiding decisions on road network planning to reduce impacts on wildlife in real landscapes. We addressed this issue by developing an approach for quantifying the impact on wildlife mortality of two alternative mechanisms for accommodating growth in vehicle numbers: (1) increasing the number of roads, and (2) increasing traffic volumes on existing roads. We applied this approach to a koala (Phascolarctos cinereus) population in eastern Australia and quantified the relative impact of each strategy on mortality. We show that, in most cases, accommodating growth in traffic through increases in volumes on existing roads has a lower impact than building new roads. An exception is where the existing road network has very low road density, but very high traffic volumes on each road. These findings have important implications for how we design road networks to reduce their impacts on biodiversity. PMID:24646891

A few large roads or many small ones? How to accommodate growth in vehicle numbers to minimise impacts on wildlife.

PubMed

Rhodes, Jonathan R; Lunney, Daniel; Callaghan, John; McAlpine, Clive A

2014-01-01

Roads and vehicular traffic are among the most pervasive of threats to biodiversity because they fragmenting habitat, increasing mortality and opening up new areas for the exploitation of natural resources. However, the number of vehicles on roads is increasing rapidly and this is likely to continue into the future, putting increased pressure on wildlife populations. Consequently, a major challenge is the planning of road networks to accommodate increased numbers of vehicles, while minimising impacts on wildlife. Nonetheless, we currently have few principles for guiding decisions on road network planning to reduce impacts on wildlife in real landscapes. We addressed this issue by developing an approach for quantifying the impact on wildlife mortality of two alternative mechanisms for accommodating growth in vehicle numbers: (1) increasing the number of roads, and (2) increasing traffic volumes on existing roads. We applied this approach to a koala (Phascolarctos cinereus) population in eastern Australia and quantified the relative impact of each strategy on mortality. We show that, in most cases, accommodating growth in traffic through increases in volumes on existing roads has a lower impact than building new roads. An exception is where the existing road network has very low road density, but very high traffic volumes on each road. These findings have important implications for how we design road networks to reduce their impacts on biodiversity.

Integrated use of spatial and semantic relationships for extracting road networks from floating car data

NASA Astrophysics Data System (ADS)

Li, Jun; Qin, Qiming; Xie, Chao; Zhao, Yue

2012-10-01

The update frequency of digital road maps influences the quality of road-dependent services. However, digital road maps surveyed by probe vehicles or extracted from remotely sensed images still have a long updating circle and their cost remain high. With GPS technology and wireless communication technology maturing and their cost decreasing, floating car technology has been used in traffic monitoring and management, and the dynamic positioning data from floating cars become a new data source for updating road maps. In this paper, we aim to update digital road maps using the floating car data from China's National Commercial Vehicle Monitoring Platform, and present an incremental road network extraction method suitable for the platform's GPS data whose sampling frequency is low and which cover a large area. Based on both spatial and semantic relationships between a trajectory point and its associated road segment, the method classifies each trajectory point, and then merges every trajectory point into the candidate road network through the adding or modifying process according to its type. The road network is gradually updated until all trajectories have been processed. Finally, this method is applied in the updating process of major roads in North China and the experimental results reveal that it can accurately derive geometric information of roads under various scenes. This paper provides a highly-efficient, low-cost approach to update digital road maps.

Vulnerability analysis methods for road networks

NASA Astrophysics Data System (ADS)

Bíl, Michal; Vodák, Rostislav; Kubeček, Jan; Rebok, Tomáš; Svoboda, Tomáš

2014-05-01

Road networks rank among the most important lifelines of modern society. They can be damaged by either random or intentional events. Roads are also often affected by natural hazards, the impacts of which are both direct and indirect. Whereas direct impacts (e.g. roads damaged by a landslide or due to flooding) are localized in close proximity to the natural hazard occurrence, the indirect impacts can entail widespread service disabilities and considerable travel delays. The change in flows in the network may affect the population living far from the places originally impacted by the natural disaster. These effects are primarily possible due to the intrinsic nature of this system. The consequences and extent of the indirect costs also depend on the set of road links which were damaged, because the road links differ in terms of their importance. The more robust (interconnected) the road network is, the less time is usually needed to secure the serviceability of an area hit by a disaster. These kinds of networks also demonstrate a higher degree of resilience. Evaluating road network structures is therefore essential in any type of vulnerability and resilience analysis. There are a range of approaches used for evaluation of the vulnerability of a network and for identification of the weakest road links. Only few of them are, however, capable of simulating the impacts of the simultaneous closure of numerous links, which often occurs during a disaster. The primary problem is that in the case of a disaster, which usually has a large regional extent, the road network may remain disconnected. The majority of the commonly used indices use direct computation of the shortest paths or time between OD (origin - destination) pairs and therefore cannot be applied when the network breaks up into two or more components. Since extensive break-ups often occur in cases of major disasters, it is important to study the network vulnerability in these cases as well, so that appropriate steps can be taken in order to make it more resilient. Performing such an analysis of network break-ups requires consideration of the network as a whole, ideally identifying all the cases generated by simultaneous closure of multiple links and evaluating them using various criteria. The spatial distribution of settlements, important companies and the overall population in the nodes of the network are several factors, apart from the topology of the network which could be taken into account when computing vulnerability indices and identifying the weakest links and/or weakest link combinations. However, even for small networks (i.e., hundreds of nodes and links), the problem of break-up identification becomes extremely difficult to resolve. The naive approaches of the brute force examination consequently fail and more elaborated algorithms have to be applied. We address the problem of evaluating the vulnerability of road networks in our work by simulating the impacts of the simultaneous closure of multiple roads/links. We present an ongoing work on a sophisticated algorithm focused on the identification of network break-ups and evaluating them by various criteria.

Using data mining techniques to predict the severity of bicycle crashes.

PubMed

Prati, Gabriele; Pietrantoni, Luca; Fraboni, Federico

2017-04-01

To investigate the factors predicting severity of bicycle crashes in Italy, we used an observational study of official statistics. We applied two of the most widely used data mining techniques, CHAID decision tree technique and Bayesian network analysis. We used data provided by the Italian National Institute of Statistics on road crashes that occurred on the Italian road network during the period ranging from 2011 to 2013. In the present study, the dataset contains information about road crashes occurred on the Italian road network during the period ranging from 2011 to 2013. We extracted 49,621 road accidents where at least one cyclist was injured or killed from the original database that comprised a total of 575,093 road accidents. CHAID decision tree technique was employed to establish the relationship between severity of bicycle crashes and factors related to crash characteristics (type of collision and opponent vehicle), infrastructure characteristics (type of carriageway, road type, road signage, pavement type, and type of road segment), cyclists (gender and age), and environmental factors (time of the day, day of the week, month, pavement condition, and weather). CHAID analysis revealed that the most important predictors were, in decreasing order of importance, road type (0.30), crash type (0.24), age of cyclist (0.19), road signage (0.08), gender of cyclist (0.07), type of opponent vehicle (0.05), month (0.04), and type of road segment (0.02). These eight most important predictors of the severity of bicycle crashes were included as predictors of the target (i.e., severity of bicycle crashes) in Bayesian network analysis. Bayesian network analysis identified crash type (0.31), road type (0.19), and type of opponent vehicle (0.18) as the most important predictors of severity of bicycle crashes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Automatic 3D high-fidelity traffic interchange modeling using 2D road GIS data

NASA Astrophysics Data System (ADS)

Wang, Jie; Shen, Yuzhong

2011-03-01

3D road models are widely used in many computer applications such as racing games and driving simulations. However, almost all high-fidelity 3D road models were generated manually by professional artists at the expense of intensive labor. There are very few existing methods for automatically generating 3D high-fidelity road networks, especially for those existing in the real world. Real road network contains various elements such as road segments, road intersections and traffic interchanges. Among them, traffic interchanges present the most challenges to model due to their complexity and the lack of height information (vertical position) of traffic interchanges in existing road GIS data. This paper proposes a novel approach that can automatically produce 3D high-fidelity road network models, including traffic interchange models, from real 2D road GIS data that mainly contain road centerline information. The proposed method consists of several steps. The raw road GIS data are first preprocessed to extract road network topology, merge redundant links, and classify road types. Then overlapped points in the interchanges are detected and their elevations are determined based on a set of level estimation rules. Parametric representations of the road centerlines are then generated through link segmentation and fitting, and they have the advantages of arbitrary levels of detail with reduced memory usage. Finally a set of civil engineering rules for road design (e.g., cross slope, superelevation) are selected and used to generate realistic road surfaces. In addition to traffic interchange modeling, the proposed method also applies to other more general road elements. Preliminary results show that the proposed method is highly effective and useful in many applications.

Golden Ratio Genetic Algorithm Based Approach for Modelling and Analysis of the Capacity Expansion of Urban Road Traffic Network

PubMed Central

Zhang, Lun; Zhang, Meng; Yang, Wenchen; Dong, Decun

2015-01-01

This paper presents the modelling and analysis of the capacity expansion of urban road traffic network (ICURTN). Thebilevel programming model is first employed to model the ICURTN, in which the utility of the entire network is maximized with the optimal utility of travelers' route choice. Then, an improved hybrid genetic algorithm integrated with golden ratio (HGAGR) is developed to enhance the local search of simple genetic algorithms, and the proposed capacity expansion model is solved by the combination of the HGAGR and the Frank-Wolfe algorithm. Taking the traditional one-way network and bidirectional network as the study case, three numerical calculations are conducted to validate the presented model and algorithm, and the primary influencing factors on extended capacity model are analyzed. The calculation results indicate that capacity expansion of road network is an effective measure to enlarge the capacity of urban road network, especially on the condition of limited construction budget; the average computation time of the HGAGR is 122 seconds, which meets the real-time demand in the evaluation of the road network capacity. PMID:25802512

Secure Service Proxy: A CoAP(s) Intermediary for a Securer and Smarter Web of Things

PubMed Central

Van den Abeele, Floris; Moerman, Ingrid; Demeester, Piet

2017-01-01

As the IoT continues to grow over the coming years, resource-constrained devices and networks will see an increase in traffic as everything is connected in an open Web of Things. The performance- and function-enhancing features are difficult to provide in resource-constrained environments, but will gain importance if the WoT is to be scaled up successfully. For example, scalable open standards-based authentication and authorization will be important to manage access to the limited resources of constrained devices and networks. Additionally, features such as caching and virtualization may help further reduce the load on these constrained systems. This work presents the Secure Service Proxy (SSP): a constrained-network edge proxy with the goal of improving the performance and functionality of constrained RESTful environments. Our evaluations show that the proposed design reaches its goal by reducing the load on constrained devices while implementing a wide range of features as different adapters. Specifically, the results show that the SSP leads to significant savings in processing, network traffic, network delay and packet loss rates for constrained devices. As a result, the SSP helps to guarantee the proper operation of constrained networks as these networks form an ever-expanding Web of Things. PMID:28696393

Secure Service Proxy: A CoAP(s) Intermediary for a Securer and Smarter Web of Things.

PubMed

Van den Abeele, Floris; Moerman, Ingrid; Demeester, Piet; Hoebeke, Jeroen

2017-07-11

As the IoT continues to grow over the coming years, resource-constrained devices and networks will see an increase in traffic as everything is connected in an open Web of Things. The performance- and function-enhancing features are difficult to provide in resource-constrained environments, but will gain importance if the WoT is to be scaled up successfully. For example, scalable open standards-based authentication and authorization will be important to manage access to the limited resources of constrained devices and networks. Additionally, features such as caching and virtualization may help further reduce the load on these constrained systems. This work presents the Secure Service Proxy (SSP): a constrained-network edge proxy with the goal of improving the performance and functionality of constrained RESTful environments. Our evaluations show that the proposed design reaches its goal by reducing the load on constrained devices while implementing a wide range of features as different adapters. Specifically, the results show that the SSP leads to significant savings in processing, network traffic, network delay and packet loss rates for constrained devices. As a result, the SSP helps to guarantee the proper operation of constrained networks as these networks form an ever-expanding Web of Things.

A quantitative approach to measure road network information based on edge diversity

NASA Astrophysics Data System (ADS)

Wu, Xun; Zhang, Hong; Lan, Tian; Cao, Weiwei; He, Jing

2015-12-01

The measure of map information has been one of the key issues in assessing cartographic quality and map generalization algorithms. It is also important for developing efficient approaches to transfer geospatial information. Road network is the most common linear object in real world. Approximately describe road network information will benefit road map generalization, navigation map production and urban planning. Most of current approaches focused on node diversities and supposed that all the edges are the same, which is inconsistent to real-life condition, and thus show limitations in measuring network information. As real-life traffic flow are directed and of different quantities, the original undirected vector road map was first converted to a directed topographic connectivity map. Then in consideration of preferential attachment in complex network study and rich-club phenomenon in social network, the from and to weights of each edge are assigned. The from weight of a given edge is defined as the connectivity of its end node to the sum of the connectivities of all the neighbors of the from nodes of the edge. After getting the from and to weights of each edge, edge information, node information and the whole network structure information entropies could be obtained based on information theory. The approach has been applied to several 1 square mile road network samples. Results show that information entropies based on edge diversities could successfully describe the structural differences of road networks. This approach is a complementarity to current map information measurements, and can be extended to measure other kinds of geographical objects.

Assessment of Climate Change Adaptation Costs for the U.S. Road Network

EPA Science Inventory

The U.S. road network is one of the nation’s most important capital assets and is vital to the functioning of the U.S. economy. Climate change may represent a risk or an opportunity to this network, as changes in climate stress will affect the resources necessary for both road m...

Multilayered complex network datasets for three supply chain network archetypes on an urban road grid.

PubMed

Viljoen, Nadia M; Joubert, Johan W

2018-02-01

This article presents the multilayered complex network formulation for three different supply chain network archetypes on an urban road grid and describes how 500 instances were randomly generated for each archetype. Both the supply chain network layer and the urban road network layer are directed unweighted networks. The shortest path set is calculated for each of the 1 500 experimental instances. The datasets are used to empirically explore the impact that the supply chain's dependence on the transport network has on its vulnerability in Viljoen and Joubert (2017) [1]. The datasets are publicly available on Mendeley (Joubert and Viljoen, 2017) [2].

New optimization strategies of pavement maintenance: A case study for national road network in Indonesia using integrated road management system

NASA Astrophysics Data System (ADS)

Hamdi, Hadiwardoyo, Sigit P.; Correia, A. Gomes; Pereira, Paulo

2017-06-01

A road network requires timely maintenance to keep the road surface in good condition onward better services to improve accessibility and mobility. Strategies and maintenance techniques must be chosen in order to maximize road service level through cost-effective interventions. This approach requires an updated database, which the road network in Indonesia is supported by a manual and visual survey, also using NAASRA profiler. Furthermore, in this paper, the deterministic model of deterioration was used. This optimization model uses life cycle cost analysis (LCCA), applied in an integrated manner, using IRI indicator, and allows determining the priority of treatment, type of treatment and its relation to the cost. The purpose of this paper was focussed on the aspects of road maintenance management, i.e., maintenance optimization models for different levels of traffic and various initial of road distress conditions on the national road network in Indonesia. The implementation of Integrated Road Management System (IRMS) can provide a solution to the problem of cost constraints in the maintenance of the national road network. The results from this study found that as the lowest as agency cost, it will affect the increasing of user cost. With the achievement of the target plan scenario Pl000 with initial value IRI 2, it was found that the routine management throughout the year and in early reconstruction and periodic maintenance with a 30 mm thick overlay, will simultaneously provide a higher net benefit value and has the lowest total cost of transportation.

The improved degree of urban road traffic network: A case study of Xiamen, China

NASA Astrophysics Data System (ADS)

Wang, Shiguang; Zheng, Lili; Yu, Dexin

2017-03-01

The complex network theory is applied to the study of urban road traffic network topology, and we constructed a new measure to characterize an urban road network. It is inspiring to quantify the interaction more appropriately between nodes in complex networks, especially in the field of traffic. The measure takes into account properties of lanes (e.g. number of lanes, width, traffic direction). As much, it is a more comprehensive measure in comparison to previous network measures. It can be used to grasp the features of urban street network more clearly. We applied this measure to the road network in Xiamen, China. Based on a standard method from statistical physics, we examined in more detail the distribution of this new measure and found that (1) due to the limitation of space geographic attributes, traditional research conclusions acquired by using the original definition of degree to study the primal approach modeled urban street network are not very persuasive; (2) both of the direction of the network connection and the degree's odd or even classifications need to be analyzed specifically; (3) the improved degree distribution presents obvious hierarchy, and hierarchical values conform to the power-law distribution, and correlation of our new measure shows some significant segmentation of the urban road network.

Multitask assessment of roads and vehicles network (MARVN)

NASA Astrophysics Data System (ADS)

Yang, Fang; Yi, Meng; Cai, Yiran; Blasch, Erik; Sullivan, Nichole; Sheaff, Carolyn; Chen, Genshe; Ling, Haibin

2018-05-01

Vehicle detection in wide area motion imagery (WAMI) has drawn increasing attention from the computer vision research community in recent decades. In this paper, we present a new architecture for vehicle detection on road using multi-task network, which is able to detect and segment vehicles, estimate their pose, and meanwhile yield road isolation for a given region. The multi-task network consists of three components: 1) vehicle detection, 2) vehicle and road segmentation, and 3) detection screening. Segmentation and detection components share the same backbone network and are trained jointly in an end-to-end way. Unlike background subtraction or frame differencing based methods, the proposed Multitask Assessment of Roads and Vehicles Network (MARVN) method can detect vehicles which are slowing down, stopped, and/or partially occluded in a single image. In addition, the method can eliminate the detections which are located at outside road using yielded road segmentation so as to decrease the false positive rate. As few WAMI datasets have road mask and vehicles bounding box anotations, we extract 512 frames from WPAFB 2009 dataset and carefully refine the original annotations. The resulting dataset is thus named as WAMI512. We extensively compare the proposed method with state-of-the-art methods on WAMI512 dataset, and demonstrate superior performance in terms of efficiency and accuracy.

Progressive transmission of road network

NASA Astrophysics Data System (ADS)

Ai, Bo; Ai, Tinghua; Tang, Xinming; Li, Zhen

2009-10-01

The progressive transmission of vector map data requires efficient multi-scale data model to process the data into hierarchical structure. This paper presents such a data structure of road network without redundancy of geometry for progressive transmission. For a given scale, the road network display has to settle two questions. One is which road objects to be represented and the other is what geometric details to be visualized for the selected roads. This paper combines the Töpfer law and the BLG-tree structure into a multi-scale representation matrix to answer simultaneously the above two questions. In the matrix, rows from top to bottom represent the roads in the sequence of descending classification of traffic and length, which can support the Töpfer law to retrieve the more important roads. In a row, columns record one road by a linear BLG-tree to provide good line graphics.

Understanding Road Usage Patterns in Urban Areas

NASA Astrophysics Data System (ADS)

Wang, Pu; Hunter, Timothy; Bayen, Alexandre M.; Schechtner, Katja; González, Marta C.

2012-12-01

In this paper, we combine the most complete record of daily mobility, based on large-scale mobile phone data, with detailed Geographic Information System (GIS) data, uncovering previously hidden patterns in urban road usage. We find that the major usage of each road segment can be traced to its own - surprisingly few - driver sources. Based on this finding we propose a network of road usage by defining a bipartite network framework, demonstrating that in contrast to traditional approaches, which define road importance solely by topological measures, the role of a road segment depends on both: its betweeness and its degree in the road usage network. Moreover, our ability to pinpoint the few driver sources contributing to the major traffic flow allows us to create a strategy that achieves a significant reduction of the travel time across the entire road system, compared to a benchmark approach.

Soil geohazard mapping for improved asset management of UK local roads

NASA Astrophysics Data System (ADS)

Pritchard, O. G.; Hallett, S. H.; Farewell, T. S.

2015-09-01

Unclassified roads comprise 60 % of the road network in the United Kingdom (UK). The resilience of this locally important network is declining. It is considered by the Institution of Civil Engineers to be "at risk" and is ranked 26th in the world. Many factors contribute to the degradation and ultimate failure of particular road sections. However, several UK local authorities have identified that in drought conditions, road sections founded upon shrink-swell susceptible clay soils undergo significant deterioration compared with sections on non-susceptible soils. This arises from the local road network having little, if any, structural foundations. Consequently, droughts in East Anglia have resulted in millions of pounds of damage, leading authorities to seek emergency governmental funding. This paper assesses the use of soil-related geohazard assessments in providing soil-informed maintenance strategies for the asset management of the locally important road network of the UK. A case study draws upon the UK administrative county of Lincolnshire, where road assessment data have been analysed against mapped clay-subsidence risk. This reveals a statistically significant relationship between road condition and susceptible clay soils. Furthermore, incorporation of UKCP09 future climate projections within the geohazard models has highlighted roads likely to be at future risk of clay-related subsidence.

Soil geohazard mapping for improved asset management of UK local roads

NASA Astrophysics Data System (ADS)

Pritchard, O. G.; Hallett, S. H.; Farewell, T. S.

2015-05-01

Unclassified roads comprise 60% of the road network in the United Kingdom (UK). The resilience of this locally important network is declining. It is considered by the Institution of Civil Engineers to be "at risk" and is ranked 26th in the world. Many factors contribute to the degradation and ultimate failure of particular road sections. However, several UK local authorities have identified that in drought conditions, road sections founded upon shrink/swell susceptible clay soils undergo significant deterioration compared with sections on non-susceptible soils. This arises from the local road network having little, if any structural foundations. Consequently, droughts in East Anglia have resulted in millions of pounds of damage, leading authorities to seek emergency governmental funding. This paper assesses the use of soil-related geohazard assessments in providing soil-informed maintenance strategies for the asset management of the locally important road network of the UK. A case study draws upon the UK administrative county of Lincolnshire, where road assessment data have been analysed against mapped clay-subsidence risk. This reveals a statistically significant relationship between road condition and susceptible clay soils. Furthermore, incorporation of UKCP09 future climate projections within the geohazard models has highlighted roads likely to be at future risk of clay-related subsidence.

Geospatial and Remote Sensing-based Indicators of Settlement Type---Differentiating Informal and Formal Settlements in Guatemala City

NASA Astrophysics Data System (ADS)

Owen, Karen K.

This research addresses the need for reliable, repeatable, quantitative measures to differentiate informal (slum) from formal (planned) settlements using commercial very high resolution imagery and elevation data. Measuring the physical, spatial and spectral qualities of informal settlements is an important precursor for evaluating success toward improving the lives of 100 million slum dwellers worldwide, as pledged by the United Nations Millennium Development Goal Target 7D. A variety of measures were tested based on surface material spectral properties, texture, built-up structure, road network accessibility, and geomorphology from twelve communities in Guatemala City to reveal statistically significant differences between informal and formal settlements that could be applied to other parts of the world without the need for costly or dangerous field surveys. When information from satellite imagery is constrained to roads and residential boundaries, a more precise understanding of human habitation is produced. A classification and regression tree (CART) approach and linear discriminant function analysis enabled a variable dimensionality reduction from the original 23 to 6 variables that are sufficient to differentiate a settlement as informal or formal. The results demonstrate that the entropy texture of roads, the degree of asphalt road surface, the vegetation patch compactness and patch size, the percent of bare soil land cover, the geomorphic profile convexity of the terrain, and the road density distinguish informal from formal settlements with 87--92% accuracy when results are cross-validated. The variables with highest contribution to model outcome that are common to both approaches are entropy texture of roads, vegetation patch size, and vegetation compactness suggesting that road texture, surface materials and vegetation provide the necessary characteristics to distinguish the level of informality of a settlement. The results will assist urban planners and settlement analysts who must process vast amounts of imagery worldwide, enabling them to report annually on slum conditions. An added benefit is the ability to use the measures in data-poor regions of the world without field surveys.

Roads at risk - traffic detours from debris flows in southern Norway

NASA Astrophysics Data System (ADS)

Meyer, N. K.; Schwanghart, W.; Korup, O.; Nadim, F.

2014-10-01

Globalization and interregional exchange of people, goods, and services has boosted the importance of and reliance on all kinds of transport networks. The linear structure of road networks is especially sensitive to natural hazards. In southern Norway, steep topography and extreme weather events promote frequent traffic disruption caused by debris flows. Topographic susceptibility and trigger frequency maps serve as input into a hazard appraisal at the scale of first-order catchments to quantify the impact of debris flows on the road network in terms of a failure likelihood of each link connecting two network vertices, e.g., road junctions. We compute total additional traffic loads as a function of traffic volume and excess distance, i.e. the extra length of an alternative path connecting two previously disrupted network vertices using a shortest-path algorithm. Our risk metric of link failure is the total additional annual traffic load expressed as vehicle kilometers because of debris-flow related road closures. We present two scenarios demonstrating the impact of debris flows on the road network, and quantify the associated path failure likelihood between major cities in southern Norway. The scenarios indicate that major routes crossing the central and northwestern part of the study area are associated with high link failure risk. Yet options for detours on major routes are manifold, and incur only little additional costs provided that drivers are sufficiently well informed about road closures. Our risk estimates may be of importance to road network managers and transport companies relying of speedy delivery of services and goods.

Roads at risk: traffic detours from debris flows in southern Norway

NASA Astrophysics Data System (ADS)

Meyer, N. K.; Schwanghart, W.; Korup, O.; Nadim, F.

2015-05-01

Globalisation and interregional exchange of people, goods, and services has boosted the importance of and reliance on all kinds of transport networks. The linear structure of road networks is especially sensitive to natural hazards. In southern Norway, steep topography and extreme weather events promote frequent traffic disruption caused by debris flows. Topographic susceptibility and trigger frequency maps serve as input into a hazard appraisal at the scale of first-order catchments to quantify the impact of debris flows on the road network in terms of a failure likelihood of each link connecting two network vertices, e.g. road junctions. We compute total additional traffic loads as a function of traffic volume and excess distance, i.e. the extra length of an alternative path connecting two previously disrupted network vertices using a shortest-path algorithm. Our risk metric of link failure is the total additional annual traffic load, expressed as vehicle kilometres, because of debris-flow-related road closures. We present two scenarios demonstrating the impact of debris flows on the road network and quantify the associated path-failure likelihood between major cities in southern Norway. The scenarios indicate that major routes crossing the central and north-western part of the study area are associated with high link-failure risk. Yet options for detours on major routes are manifold and incur only little additional costs provided that drivers are sufficiently well informed about road closures. Our risk estimates may be of importance to road network managers and transport companies relying on speedy delivery of services and goods.

Network-level accident-mapping: Distance based pattern matching using artificial neural network.

PubMed

Deka, Lipika; Quddus, Mohammed

2014-04-01

The objective of an accident-mapping algorithm is to snap traffic accidents onto the correct road segments. Assigning accidents onto the correct segments facilitate to robustly carry out some key analyses in accident research including the identification of accident hot-spots, network-level risk mapping and segment-level accident risk modelling. Existing risk mapping algorithms have some severe limitations: (i) they are not easily 'transferable' as the algorithms are specific to given accident datasets; (ii) they do not perform well in all road-network environments such as in areas of dense road network; and (iii) the methods used do not perform well in addressing inaccuracies inherent in and type of road environment. The purpose of this paper is to develop a new accident mapping algorithm based on the common variables observed in most accident databases (e.g. road name and type, direction of vehicle movement before the accident and recorded accident location). The challenges here are to: (i) develop a method that takes into account uncertainties inherent to the recorded traffic accident data and the underlying digital road network data, (ii) accurately determine the type and proportion of inaccuracies, and (iii) develop a robust algorithm that can be adapted for any accident set and road network of varying complexity. In order to overcome these challenges, a distance based pattern-matching approach is used to identify the correct road segment. This is based on vectors containing feature values that are common in the accident data and the network data. Since each feature does not contribute equally towards the identification of the correct road segments, an ANN approach using the single-layer perceptron is used to assist in "learning" the relative importance of each feature in the distance calculation and hence the correct link identification. The performance of the developed algorithm was evaluated based on a reference accident dataset from the UK confirming that the accuracy is much better than other methods. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Thermoelectric generator installation at Divide Road Weather Information Systems (RWIS).

DOT National Transportation Integrated Search

2016-04-13

The Department of Transportation and Public Facilities (DOT&PF) has a network of Road Weather Information System (RWIS) environmental sensor stations (ESS) deployed along the road network. Six of the stations do not have access to commercial power an...

Road safety performance indicators for the interurban road network.

PubMed

Yannis, George; Weijermars, Wendy; Gitelman, Victoria; Vis, Martijn; Chaziris, Antonis; Papadimitriou, Eleonora; Azevedo, Carlos Lima

2013-11-01

Various road safety performance indicators (SPIs) have been proposed for different road safety research areas, mainly as regards driver behaviour (e.g. seat belt use, alcohol, drugs, etc.) and vehicles (e.g. passive safety); however, no SPIs for the road network and design have been developed. The objective of this research is the development of an SPI for the road network, to be used as a benchmark for cross-region comparisons. The developed SPI essentially makes a comparison of the existing road network to the theoretically required one, defined as one which meets some minimum requirements with respect to road safety. This paper presents a theoretical concept for the determination of this SPI as well as a translation of this theory into a practical method. Also, the method is applied in a number of pilot countries namely the Netherlands, Portugal, Greece and Israel. The results show that the SPI could be efficiently calculated in all countries, despite some differences in the data sources. In general, the calculated overall SPI scores were realistic and ranged from 81 to 94%, with the exception of Greece where the SPI was relatively lower (67%). However, the SPI should be considered as a first attempt to determine the safety level of the road network. The proposed method has some limitations and could be further improved. The paper presents directions for further research to further develop the SPI. Copyright © 2012 Elsevier Ltd. All rights reserved.

Spatial Patterns of Road-Induced Backwater Sediment Storage Across A Rural to Urban Gradient

NASA Astrophysics Data System (ADS)

Copeland, M.; Bain, D.

2017-12-01

Road networks dominate many landscapes and often interact with stream networks to alter basin sediment dynamics. Currently, conceptual models of catchment-scale sediment fluxes remain at a coarse scale (i.e., the entire catchment) and are unable to resolve important human-driven sediment storage processes. The spatio-temporal complexity of the interactions between road networks and streams has made it challenging to infer the fine-scale impacts of road crossings on fluvial systems. Here, road crossings in multiple drainage networks and the associated backwater sediment accumulations are examined along a rural to urban gradient around Pittsburgh, PA. Preliminary results indicate that upstream drainage area, channel slope, and human activities control stream crossing type and therefore drive associated sediment accumulation, particularly in urban headwater channels. The data indicate that the combination of land use intensity and infrastructure age influences the volume of sediment trapped in road-induced backwaters. Clarification of the coupled human, road-building, and natural stream adjustments will allow for more effective treatments of fluvial impacts, such as the "urban stream syndrome."

A GRASS GIS Semi-Stochastic Model for Evaluating the Probability of Landslides Impacting Road Networks in Collazzone, Central Italy

NASA Astrophysics Data System (ADS)

Taylor, Faith E.; Santangelo, Michele; Marchesini, Ivan; Malamud, Bruce D.

2013-04-01

During a landslide triggering event, the tens to thousands of landslides resulting from the trigger (e.g., earthquake, heavy rainfall) may block a number of sections of the road network, posing a risk to rescue efforts, logistics and accessibility to a region. Here, we present initial results from a semi-stochastic model we are developing to evaluate the probability of landslides intersecting a road network and the network-accessibility implications of this across a region. This was performed in the open source GRASS GIS software, where we took 'model' landslides and dropped them on a 79 km2 test area region in Collazzone, Umbria, Central Italy, with a given road network (major and minor roads, 404 km in length) and already determined landslide susceptibilities. Landslide areas (AL) were randomly selected from a three-parameter inverse gamma probability density function, consisting of a power-law decay of about -2.4 for medium and large values of AL and an exponential rollover for small values of AL; the rollover (maximum probability) occurs at about AL = 400 m.2 The number of landslide areas selected for each triggered event iteration was chosen to have an average density of 1 landslide km-2, i.e. 79 landslide areas chosen randomly for each iteration. Landslides were then 'dropped' over the region semi-stochastically: (i) random points were generated across the study region; (ii) based on the landslide susceptibility map, points were accepted/rejected based on the probability of a landslide occurring at that location. After a point was accepted, it was assigned a landslide area (AL) and length to width ratio. Landslide intersections with roads were then assessed and indices such as the location, number and size of road blockage recorded. The GRASS-GIS model was performed 1000 times in a Monte-Carlo type simulation. Initial results show that for a landslide triggering event of 1 landslide km-2 over a 79 km2 region with 404 km of road, the number of road blockages ranges from 6 to 17, resulting in one road blockage every 24-67 km of roads. The average length of road blocked was 33 m. As we progress with model development and more sophisticated network analysis, we believe this semi-stochastic modelling approach will aid civil protection agencies to get a rough idea for the probability of road network potential damage (road block number and extent) as the result of different magnitude landslide triggering event scenarios.

The effect of road network patterns on pedestrian safety: A zone-based Bayesian spatial modeling approach.

PubMed

Guo, Qiang; Xu, Pengpeng; Pei, Xin; Wong, S C; Yao, Danya

2017-02-01

Pedestrian safety is increasingly recognized as a major public health concern. Extensive safety studies have been conducted to examine the influence of multiple variables on the occurrence of pedestrian-vehicle crashes. However, the explicit relationship between pedestrian safety and road network characteristics remains unknown. This study particularly focused on the role of different road network patterns on the occurrence of crashes involving pedestrians. A global integration index via space syntax was introduced to quantify the topological structures of road networks. The Bayesian Poisson-lognormal (PLN) models with conditional autoregressive (CAR) prior were then developed via three different proximity structures: contiguity, geometry-centroid distance, and road network connectivity. The models were also compared with the PLN counterpart without spatial correlation effects. The analysis was based on a comprehensive crash dataset from 131 selected traffic analysis zones in Hong Kong. The results indicated that higher global integration was associated with more pedestrian-vehicle crashes; the irregular pattern network was proved to be safest in terms of pedestrian crash occurrences, whereas the grid pattern was the least safe; the CAR model with a neighborhood structure based on road network connectivity was found to outperform in model goodness-of-fit, implying the importance of accurately accounting for spatial correlation when modeling spatially aggregated crash data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata

PubMed Central

Chen, Yangzhou; Guo, Yuqi; Wang, Ying

2017-01-01

In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research. PMID:28353664

Modeling and Density Estimation of an Urban Freeway Network Based on Dynamic Graph Hybrid Automata.

PubMed

Chen, Yangzhou; Guo, Yuqi; Wang, Ying

2017-03-29

In this paper, in order to describe complex network systems, we firstly propose a general modeling framework by combining a dynamic graph with hybrid automata and thus name it Dynamic Graph Hybrid Automata (DGHA). Then we apply this framework to model traffic flow over an urban freeway network by embedding the Cell Transmission Model (CTM) into the DGHA. With a modeling procedure, we adopt a dual digraph of road network structure to describe the road topology, use linear hybrid automata to describe multi-modes of dynamic densities in road segments and transform the nonlinear expressions of the transmitted traffic flow between two road segments into piecewise linear functions in terms of multi-mode switchings. This modeling procedure is modularized and rule-based, and thus is easily-extensible with the help of a combination algorithm for the dynamics of traffic flow. It can describe the dynamics of traffic flow over an urban freeway network with arbitrary topology structures and sizes. Next we analyze mode types and number in the model of the whole freeway network, and deduce a Piecewise Affine Linear System (PWALS) model. Furthermore, based on the PWALS model, a multi-mode switched state observer is designed to estimate the traffic densities of the freeway network, where a set of observer gain matrices are computed by using the Lyapunov function approach. As an example, we utilize the PWALS model and the corresponding switched state observer to traffic flow over Beijing third ring road. In order to clearly interpret the principle of the proposed method and avoid computational complexity, we adopt a simplified version of Beijing third ring road. Practical application for a large-scale road network will be implemented by decentralized modeling approach and distributed observer designing in the future research.

Multilane Traffic Flow Modeling Using Cellular Automata Theory

NASA Astrophysics Data System (ADS)

Chechina, Antonina; Churbanova, Natalia; Trapeznikova, Marina

2018-02-01

The paper deals with the mathematical modeling of traffic flows on urban road networks using microscopic approach. The model is based on the cellular automata theory and presents a generalization of the Nagel-Schreckenberg model to a multilane case. The created program package allows to simulate traffic on various types of road fragments (T or X type intersection, strait road elements, etc.) and on road networks that consist of these elements. Besides that, it allows to predict the consequences of various decisions regarding road infrastructure changes, such as: number of lanes increasing/decreasing, putting new traffic lights into operation, building new roads, entrances/exits, road junctions.

Pareto frontier analyses based decision making tool for transportation of hazardous waste.

PubMed

Das, Arup; Mazumder, T N; Gupta, A K

2012-08-15

Transportation of hazardous wastes through a region poses immense threat on the development along its road network. The risk to the population, exposed to such activities, has been documented in the past. However, a comprehensive framework for routing hazardous wastes has often been overlooked. A regional Hazardous Waste Management scheme should incorporate a comprehensive framework for hazardous waste transportation. This framework would incorporate the various stakeholders involved in decision making. Hence, a multi-objective approach is required to safeguard the interest of all the concerned stakeholders. The objective of this study is to design a methodology for routing of hazardous wastes between the generating units and the disposal facilities through a capacity constrained network. The proposed methodology uses posteriori method with multi-objective approach to find non-dominated solutions for the system consisting of multiple origins and destinations. A case study of transportation of hazardous wastes in Kolkata Metropolitan Area has also been provided to elucidate the methodology. Copyright © 2012 Elsevier B.V. All rights reserved.

Road networks as collections of minimum cost paths

NASA Astrophysics Data System (ADS)

Wegner, Jan Dirk; Montoya-Zegarra, Javier Alexander; Schindler, Konrad

2015-10-01

We present a probabilistic representation of network structures in images. Our target application is the extraction of urban roads from aerial images. Roads appear as thin, elongated, partially curved structures forming a loopy graph, and this complex layout requires a prior that goes beyond standard smoothness and co-occurrence assumptions. In the proposed model the network is represented as a union of 1D paths connecting distant (super-)pixels. A large set of putative candidate paths is constructed in such a way that they include the true network as much as possible, by searching for minimum cost paths in the foreground (road) likelihood. Selecting the optimal subset of candidate paths is posed as MAP inference in a higher-order conditional random field. Each path forms a higher-order clique with a type of clique potential, which attracts the member nodes of cliques with high cumulative road evidence to the foreground label. That formulation induces a robust PN -Potts model, for which a global MAP solution can be found efficiently with graph cuts. Experiments with two road data sets show that the proposed model significantly improves per-pixel accuracies as well as the overall topological network quality with respect to several baselines.

Solutions to Improve Road Circulation in the Pitesti City Based on Analysis-Diagnostics of Road Traffic

NASA Astrophysics Data System (ADS)

Vîlcan, A.; Neagu, E.; Badarau Suster, H.; Boroiu, A. A.

2017-10-01

Road traffic congestion has become a daily phenomenon in the central area of Pitesti in the peak traffic periods. In order to achieve the mobility plan of Pitesti, an important stage is the diagnostic analysis of the road traffic. For this purpose, the urban road network was formalized through a graph containing the most important 40 intersections and traffic measurements were made at all these intersections and on the main roads connecting the peri-urban area. The data obtained by traffic macrosimulation confirmed the overloading of the street network during peak traffic hours and the analyzes made for various road traffic organization scenarios have shown that there are sustainable solutions for urban mobility only if the road network is fundamentally reconfigured (a belt outside the city and a median ring). Thus, the necessity of realizing the road passage in the Prundu neighbourhood and the finishing of the city belt by realizing the “detour West” of the city is argued. The importance of the work is that it brings scientific arguments for the realization of these road infrastructure projects, integrated in the urban mobility plan, which will base the development strategy of the Pitesti municipality.

Road networks predict human influence on Amazonian bird communities

PubMed Central

Ahmed, Sadia E.; Lees, Alexander C.; Moura, Nárgila G.; Gardner, Toby A.; Barlow, Jos; Ferreira, Joice; Ewers, Robert M.

2014-01-01

Road building can lead to significant deleterious impacts on biodiversity, varying from direct road-kill mortality and direct habitat loss associated with road construction, to more subtle indirect impacts from edge effects and fragmentation. However, little work has been done to evaluate the specific effects of road networks and biodiversity loss beyond the more generalized effects of habitat loss. Here, we compared forest bird species richness and composition in the municipalities of Santarém and Belterra in Pará state, eastern Brazilian Amazon, with a road network metric called ‘roadless volume (RV)’ at the scale of small hydrological catchments (averaging 3721 ha). We found a significant positive relationship between RV and both forest bird richness and the average number of unique species (species represented by a single record) recorded at each site. Forest bird community composition was also significantly affected by RV. Moreover, there was no significant correlation between RV and forest cover, suggesting that road networks may impact biodiversity independently of changes in forest cover. However, variance partitioning analysis indicated that RV has partially independent and therefore additive effects, suggesting that RV and forest cover are best used in a complementary manner to investigate changes in biodiversity. Road impacts on avian species richness and composition independent of habitat loss may result from road-dependent habitat disturbance and fragmentation effects that are not captured by total percentage habitat cover, such as selective logging, fire, hunting, traffic disturbance, edge effects and road-induced fragmentation. PMID:25274363

Constraining Dust and Color Variations of High-z SNe Using NICMOS on the

Science.gov Websites

Hubble SAO/NASA ADS Astronomy Abstract Service Title: Constraining Dust and Color Variations of Road, Oxford OX1 3RH, UK), AN(Department of Astronomy and Astrophysics, University of Toronto, 60 St ). Publication Date: 08/2009 Origin: IOP Astronomy Keywords: cosmology: observations, cosmological parameters

Advanced development and calibration of the network robustness index to identify critical road network links.

DOT National Transportation Integrated Search

2010-05-31

In this research project, transportation flexibility and reliability concepts are extended and applied : to a new method for identifying the most critical links in a road network. Current transportation : management practices typically utilize locali...

An Optimal Schedule for Urban Road Network Repair Based on the Greedy Algorithm

PubMed Central

Lu, Guangquan; Xiong, Ying; Wang, Yunpeng

2016-01-01

The schedule of urban road network recovery caused by rainstorms, snow, and other bad weather conditions, traffic incidents, and other daily events is essential. However, limited studies have been conducted to investigate this problem. We fill this research gap by proposing an optimal schedule for urban road network repair with limited repair resources based on the greedy algorithm. Critical links will be given priority in repair according to the basic concept of the greedy algorithm. In this study, the link whose restoration produces the ratio of the system-wide travel time of the current network to the worst network is the minimum. We define such a link as the critical link for the current network. We will re-evaluate the importance of damaged links after each repair process is completed. That is, the critical link ranking will be changed along with the repair process because of the interaction among links. We repair the most critical link for the specific network state based on the greedy algorithm to obtain the optimal schedule. The algorithm can still quickly obtain an optimal schedule even if the scale of the road network is large because the greedy algorithm can reduce computational complexity. We prove that the problem can obtain the optimal solution using the greedy algorithm in theory. The algorithm is also demonstrated in the Sioux Falls network. The problem discussed in this paper is highly significant in dealing with urban road network restoration. PMID:27768732

Soil-related geohazard assessments for maintaining the UK's minor road network

NASA Astrophysics Data System (ADS)

Pritchard, Oliver; Hallett, Stephen; Farewell, Timothy

2015-04-01

The minor road network of the UK (United Kingdom) encompasses 98% of the overall road network. In recent years the UK's roads have been deteriorating, currently rated 26th in the world and considered at risk and declining by the Institution of Civil Engineers (ICE). Many factors contribute to the degradation and ultimately, to the failure of particular road sections. However, several UK local authorities have identified that during drought conditions, road sections founded upon clay soils which are susceptible to volumetric shrinkage and swelling undergo significant deterioration compared to those sections on non-susceptible soils. Droughts in East Anglia recently resulted in estimated damages of £26 million, leading several local authorities to apply to Central Government for emergency funding. The minor or evolved road network is most at risk due to them having often little, if any, structural foundations. This paper addresses the use of soil-related geohazard assessments and GIS (Geographical Information Systems) in helping to provide a soil-informed maintenance strategy for the asset management of the important (both socially and commercially) local road network of the UK. Furthermore, to establish future subsidence risk, UKCP09 climate projections have been used to model the likely potential soil moisture deficit (PSMD) for baseline (1961-1990), 2030 (2020-2049) and 2050 (2040-2069) scenarios. The incorporation of probabilistic PSMD data into clay-related subsidence models has allowed an assessment of potential subsidence risk, with a range of uncertainties, for these scenarios. Intersection of road networks with future projections of subsidence risk has enabled metrics of potential vulnerability to be established. This will aid prioritisation of areas which require further maintenance to make them more climate resilient, avoiding emergency funding situations. Subsequently, this approach can then be extrapolated to the entire UK minor road network, on a local authority level, to provide a series of regional risk assessments. Case studies are drawn from the UK administrative counties of Lincolnshire and Worcestershire. Data from observed road assessments, obtained from the respective local authorities have been analysed and intersected with clay-related subsidence risk. Lincolnshire County Council have already implemented this research to prioritise approximately £600,000 of road maintenance fund to their minor road network. Further appreciation of the spatial distribution and understanding of soil-related hazards has also led Lincolnshire County Council to trial new resurfacing strategies; these new techniques helping to reduce carbon outputs in the form of materials and transport. A reduction in the amount of potential hazardous (bituminous) waste to landfill is also being achieved through re-inclusion of waste material back into the road foundation where areas are particularly prone to soil shrinkage. Our research shows that soil-related geohazard assessments have a part to play in the asset management of the UK's local highways network. The study supports the ICE's recommendation for a regime which moves towards planned, preventative maintenance and achieving Defra's (Department for Environment, Food and Rural Affairs) aim of a climate resilient UK infrastructure. The methodology introduced here also has applicability to other countries, where appropriate soils and infrastructure data are available.

The Impact of Large Urban Structural Elements on Traffic Flow   a Case Study of Danwei and Xiaoqu in Shanghai

NASA Astrophysics Data System (ADS)

Lyu, H.; Ding, L.; Fan, H.; Meng, L.

2017-09-01

Danwei (working unit) and Xiaoqu (residential community) are two typical and unique structural urban elements in China. The interior roads of Danwei and Xiaoqu are usually not accessible for the public. Recently, there is a call for opening these interior roads to the public to improve road network structure and optimize traffic flow. In this paper we investigate the impact of Danwei and Xiaoqu on their neighbouring traffic quantitatively. By taking into consideration of origins and destinations (ODs) distributions and route selection behaviours (e.g., shortest paths), we propose an extended betweenness centrality to investigate the traffic flow in two scenarios 1) the interior roads of Danwei and Xiaoqu are excluded from urban road network, 2) the interior roads are integrated into road network. A Danwei and a Xiaoqu in Shanghai are used as the study area. The preliminary results show the feasibility of our extended betweenness centrality in investigating the traffic flow patterns and reveal the quantitative changes of the traffic flow after opening interior roads.

Modeling the heterogeneous traffic correlations in urban road systems using traffic-enhanced community detection approach

NASA Astrophysics Data System (ADS)

Lu, Feng; Liu, Kang; Duan, Yingying; Cheng, Shifen; Du, Fei

2018-07-01

A better characterization of the traffic influence among urban roads is crucial for traffic control and traffic forecasting. The existence of spatial heterogeneity imposes great influence on modeling the extent and degree of road traffic correlation, which is usually neglected by the traditional distance based method. In this paper, we propose a traffic-enhanced community detection approach to spatially reveal the traffic correlation in city road networks. First, the road network is modeled as a traffic-enhanced dual graph with the closeness between two road segments determined not only by their topological connection, but also by the traffic correlation between them. Then a flow-based community detection algorithm called Infomap is utilized to identify the road segment clusters. Evaluated by Moran's I, Calinski-Harabaz Index and the traffic interpolation application, we find that compared to the distance based method and the community based method, our proposed traffic-enhanced community based method behaves better in capturing the extent of traffic relevance as both the topological structure of the road network and the traffic correlations among urban roads are considered. It can be used in more traffic-related applications, such as traffic forecasting, traffic control and guidance.

Modeling an impact of road geometric design on vehicle energy consumption

NASA Astrophysics Data System (ADS)

Luin, Blaž; Petelin, Stojan; Al-Mansour, Fouad

2017-11-01

Some roads connect traffic origins and destinations directly, some use winding, indirect routes. Indirect connections result in longer distances driven and increased fuel consumption. A similar effect is observed on congested roads and mountain roads with many changes in altitude. Therefore a framework to assess road networks based on energy consumption is proposed. It has been shown that road geometry has significant impact on overall traffic energy consumption and emissions. The methodology presented in the paper analyzes impact of traffic volume, shares of vehicle classes, road network configuration on the energy used by the vehicles. It can be used to optimize energy consumption with efficient traffic management and to choose optimum new road in the design phase. This is especially important as the energy consumed by the vehicles shortly after construction supersedes the energy spent for the road construction.

Satellites vs. fiber optics based networks and services - Road map to strategic planning

NASA Astrophysics Data System (ADS)

Marandi, James H. R.

An overview of a generic telecommunications network and its components is presented, and the current developments in satellite and fiber optics technologies are discussed with an eye on the trends in industry. A baseline model is proposed, and a cost comparison of fiber- vs satellite-based networks is made. A step-by-step 'road map' to the successful strategic planning of telecommunications services and facilities is presented. This road map provides for optimization of the current and future networks and services through effective utilization of both satellites and fiber optics. The road map is then applied to different segments of the telecommunications industry and market place, to show its effectiveness for the strategic planning of executives of three types: (1) those heading telecommunications manufacturing concerns, (2) those leading communication service companies, and (3) managers of telecommunication/MIS departments of major corporations. Future networking issues, such as developments in integrated-services digital network standards and technologies, are addressed.

Detection of Road Surface States from Tire Noise Using Neural Network Analysis

NASA Astrophysics Data System (ADS)

Kongrattanaprasert, Wuttiwat; Nomura, Hideyuki; Kamakura, Tomoo; Ueda, Koji

This report proposes a new processing method for automatically detecting the states of road surfaces from tire noises of passing vehicles. In addition to multiple indicators of the signal features in the frequency domain, we propose a few feature indicators in the time domain to successfully classify the road states into four categories: snowy, slushy, wet, and dry states. The method is based on artificial neural networks. The proposed classification is carried out in multiple neural networks using learning vector quantization. The outcomes of the networks are then integrated by the voting decision-making scheme. Experimental results obtained from recorded signals for ten days in the snowy season demonstrated that an accuracy of approximately 90% can be attained for predicting road surface states using only tire noise data.

An eco-efficient and economical optimum evaluation technique for the forest road networks: the case of the mountainous forest of Metsovo, Greece.

PubMed

Tampekis, Stergios; Samara, Fani; Sakellariou, Stavros; Sfougaris, Athanassios; Christopoulou, Olga

2018-02-12

The sustainable forest management can be achieved only through environmentally sound and economically efficient and feasible forest road networks and transportation systems that can potentially improve the multi-functional use of forest resources. However, road network planning and construction suggest long-term finance that require a capital investment (cash outflow), which would be equal to the value of the total revenue flow (cash inflow) over the whole lifecycle project. This paper emphasizes in an eco-efficient and economical optimum evaluation method for the forest road networks in the mountainous forest of Metsovo, Greece. More specifically, with the use of this technique, we evaluated the forest roads' (a) total construction costs, (b) annual maintenance cost, and (c) log skidding cost. In addition, we estimated the total economic value of forest goods and services that are lost from the forest roads' construction. Finally, we assessed the optimum eco-efficient and economical forest roads densities based on linear equations that stem from the internal rate of return method (IRR) and have been presented graphically. Data analysis and its presentation are achieved with the contribution of geographic information systems (GIS). The technique which is described in this study can be for the decision makers an attractive and useful implement in order to select the most eco-friendly and economical optimum solution to plan forest road network or to evaluate the existing forest transportation systems. Hence, with the use of this method, we can combine not only the multi-objective utilization of natural resources but also the environmental protection of forest ecosystems.

Towards an agent based traffic regulation and recommendation system for the on-road air quality control.

PubMed

Sadiq, Abderrahmane; El Fazziki, Abdelaziz; Ouarzazi, Jamal; Sadgal, Mohamed

2016-01-01

This paper presents an integrated and adaptive problem-solving approach to control the on-road air quality by modeling the road infrastructure, managing traffic based on pollution level and generating recommendations for road users. The aim is to reduce vehicle emissions in the most polluted road segments and optimizing the pollution levels. For this we propose the use of historical and real time pollution records and contextual data to calculate the air quality index on road networks and generate recommendations for reassigning traffic flow in order to improve the on-road air quality. The resulting air quality indexes are used in the system's traffic network generation, which the cartography is represented by a weighted graph. The weights evolve according to the pollution indexes and path properties and the graph is therefore dynamic. Furthermore, the systems use the available pollution data and meteorological records in order to predict the on-road pollutant levels by using an artificial neural network based prediction model. The proposed approach combines the benefits of multi-agent systems, Big data technology, machine learning tools and the available data sources. For the shortest path searching in the road network, we use the Dijkstra algorithm over Hadoop MapReduce framework. The use Hadoop framework in the data retrieve and analysis process has significantly improved the performance of the proposed system. Also, the agent technology allowed proposing a suitable solution in terms of robustness and agility.

Road networks predict human influence on Amazonian bird communities.

PubMed

Ahmed, Sadia E; Lees, Alexander C; Moura, Nárgila G; Gardner, Toby A; Barlow, Jos; Ferreira, Joice; Ewers, Robert M

2014-11-22

Road building can lead to significant deleterious impacts on biodiversity, varying from direct road-kill mortality and direct habitat loss associated with road construction, to more subtle indirect impacts from edge effects and fragmentation. However, little work has been done to evaluate the specific effects of road networks and biodiversity loss beyond the more generalized effects of habitat loss. Here, we compared forest bird species richness and composition in the municipalities of Santarém and Belterra in Pará state, eastern Brazilian Amazon, with a road network metric called 'roadless volume (RV)' at the scale of small hydrological catchments (averaging 3721 ha). We found a significant positive relationship between RV and both forest bird richness and the average number of unique species (species represented by a single record) recorded at each site. Forest bird community composition was also significantly affected by RV. Moreover, there was no significant correlation between RV and forest cover, suggesting that road networks may impact biodiversity independently of changes in forest cover. However, variance partitioning analysis indicated that RV has partially independent and therefore additive effects, suggesting that RV and forest cover are best used in a complementary manner to investigate changes in biodiversity. Road impacts on avian species richness and composition independent of habitat loss may result from road-dependent habitat disturbance and fragmentation effects that are not captured by total percentage habitat cover, such as selective logging, fire, hunting, traffic disturbance, edge effects and road-induced fragmentation. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Road Maintenance in Africa: Approaches and Perspectives

NASA Astrophysics Data System (ADS)

M, Mostafa Hassan

2018-06-01

In Africa, roads are the dominant mode of passenger and freight transport, for which the need is growing rapidly. It is noticeable that most of the African countries do not do enough to ensure the sustainability of road infrastructure as it has been widely reported that roads are affected, to varying degrees, by premature deterioration. Most of the African countries have adopted institutional reforms, notably entailing the creation of road funds and road agencies, and made significant progress on road maintenance. However, many challenges remain to be addressed in all of them to ensure appropriate maintenance. Although spending on road maintenance has increased over time in all African countries it remains insufficient to cover the needs. Poorly maintained roads constrain mobility, significantly raise vehicle operating costs, increase accident rates and their associated human and property costs, and aggravate isolation, poverty, poor health, and illiteracy in rural communities. This paper focuses, in particular, on road maintenance in some African countries considering types of road maintenance and the different approaches aiming at a comparison to reflect on similarities and differences.

Implications of climate change on winter road networks in Ontario's Far North and northern Manitoba, Canada, based on climate model projections

NASA Astrophysics Data System (ADS)

Hori, Y.; Cheng, V. Y. S.; Gough, W. A.

2017-12-01

A network of winter roads in northern Canada connects a number of remote First Nations communities to all-season roads and rails. The extent of the winter road networks depends on the geographic features, socio-economic activities, and the numbers of remote First Nations so that it differs among the provinces. The most extensive winter road networks below the 60th parallel south are located in Ontario and Manitoba, serving 32 and 18 communities respectively. In recent years, a warmer climate has resulted in a shorter winter road season and an increase in unreliable road conditions; thus, limiting access among remote communities. This study focused on examining the future freezing degree-days (FDDs) accumulations during the winter road season at selected locations throughout Ontario's Far North and northern Manitoba using recent climate model projections from the multi-model ensembles of General Circulation Models (GCMs) under the Representative Concentration Pathway (RCP) scenarios. First, the non-parametric Mann-Kendall correlation test and the Theil-Sen method were used to identify any statistically significant trends between FDDs and time for the base period (1981-2010). Second, future climate scenarios are developed for the study areas using statistical downscaling methods. This study also examined the lowest threshold of FDDs during the winter road construction in a future period. Our previous study established the lowest threshold of 380 FDDs, which derived from the relationship between the FDDs and the opening dates of James Bay Winter Road near the Hudson-James Bay coast. Thus, this study applied the threshold measure as a conservative estimate of the minimum threshold of FDDs to examine the effects of climate change on the winter road construction period.

a Numerical Investigation of the Jamming Transition in Traffic Flow on Diluted Planar Networks

NASA Astrophysics Data System (ADS)

Achler, Gabriele; Barra, Adriano

In order to develop a toy model for car's traffic in cities, in this paper we analyze, by means of numerical simulations, the transition among fluid regimes and a congested jammed phase of the flow of kinetically constrained hard spheres in planar random networks similar to urban roads. In order to explore as timescales as possible, at a microscopic level we implement an event driven dynamics as the infinite time limit of a class of already existing model (Follow the Leader) on an Erdos-Renyi two-dimensional graph, the crossroads being accounted by standard Kirchoff density conservations. We define a dynamical order parameter as the ratio among the moving spheres versus the total number and by varying two control parameters (density of the spheres and coordination number of the network) we study the phase transition. At a mesoscopic level it respects an, again suitable, adapted version of the Lighthill-Whitham model, which belongs to the fluid-dynamical approach to the problem. At a macroscopic level, the model seems to display a continuous transition from a fluid phase to a jammed phase when varying the density of the spheres (the amount of cars in a city-like scenario) and a discontinuous jump when varying the connectivity of the underlying network.

Modeling spatial decisions with graph theory: logging roads and forest fragmentation in the Brazilian Amazon.

PubMed

Walker, Robert; Arima, Eugenio; Messina, Joe; Soares-Filho, Britaldo; Perz, Stephen; Vergara, Dante; Sales, Marcio; Pereira, Ritaumaria; Castro, Williams

2013-01-01

This article addresses the spatial decision-making of loggers and implications for forest fragmentation in the Amazon basin. It provides a behavioral explanation for fragmentation by modeling how loggers build road networks, typically abandoned upon removal of hardwoods. Logging road networks provide access to land, and the settlers who take advantage of them clear fields and pastures that accentuate their spatial signatures. In shaping agricultural activities, these networks organize emergent patterns of forest fragmentation, even though the loggers move elsewhere. The goal of the article is to explicate how loggers shape their road networks, in order to theoretically explain an important type of forest fragmentation found in the Amazon basin, particularly in Brazil. This is accomplished by adapting graph theory to represent the spatial decision-making of loggers, and by implementing computational algorithms that build graphs interpretable as logging road networks. The economic behavior of loggers is conceptualized as a profit maximization problem, and translated into spatial decision-making by establishing a formal correspondence between mathematical graphs and road networks. New computational approaches, adapted from operations research, are used to construct graphs and simulate spatial decision-making as a function of discount rates, land tenure, and topographic constraints. The algorithms employed bracket a range of behavioral settings appropriate for areas of terras de volutas, public lands that have not been set aside for environmental protection, indigenous peoples, or colonization. The simulation target sites are located in or near so-called Terra do Meio, once a major logging frontier in the lower Amazon Basin. Simulation networks are compared to empirical ones identified by remote sensing and then used to draw inferences about factors influencing the spatial behavior of loggers. Results overall suggest that Amazonia's logging road networks induce more fragmentation than necessary to access fixed quantities of wood. The paper concludes by considering implications of the approach and findings for Brazil's move to a system of concession logging.

Road-networks, a practical indicator of human impacts on biodiversity in Tropical forests

NASA Astrophysics Data System (ADS)

Hosaka, T.; Yamada, T.; Okuda, T.

2014-02-01

Tropical forests sustain the most diverse plants and animals in the world, but are also being lost most rapidly. Rapid assessment and monitoring using remote sensing on biodiversity of tropical forests is needed to predict and evaluate biodiversity loss by human activities. Identification of reliable indicators of forest biodiversity and/or its loss is an urgent issue. In the present paper, we propose the density of road networks in tropical forests can be a good and practical indicator of human impacts on biodiversity in tropical forests through reviewing papers and introducing our preliminary survey in peninsular Malaysia. Many previous studies suggest a strong negative impact of forest roads on biodiversity in tropical rainforests since they changes microclimate, soil properties, drainage patterns, canopy openness and forest accessibility. Moreover, our preliminary survey also showed that even a narrow logging road (6 m wide) significantly lowered abundance of dung beetles (well-known bio-indicator in biodiversity survey in tropical forests) near the road. Since these road networks are readily to be detected with remote sensing approach such as aerial photographs and Lider, regulation and monitoring of the road networks using remote sensing techniques is a key to slow down the rate of biodiversity loss due to forest degradation in tropical forests.

Impacts of road network expansion on landscape ecological risk in a megacity, China: A case study of Beijing.

PubMed

Mo, Wenbo; Wang, Yong; Zhang, Yingxue; Zhuang, Dafang

2017-01-01

Road networks affect the spatial structure of urban landscapes, and with continuous expansion, it will also exert more widespread influences on the regional ecological environment. With the support of geographic information system (GIS) technology, based on the application of various spatial analysis methods, this study analyzed the spatiotemporal changes of road networks and landscape ecological risk in the research area of Beijing to explore the impacts of road network expansion on ecological risk in the urban landscape. The results showed the following: 1) In the dynamic processes of change in the overall landscape pattern, the changing differences in landscape indices of various landscape types were obvious and were primarily related to land-use type. 2) For the changes in a time series, the expansion of the road kernel area was consistent with the extension of the sub-low-risk area in the urban center, but some differences were observed during different stages of development. 3) For the spatial position, the expanding changes in the road kernel area were consistent with the grade changes of the urban central ecological risk, primarily because both had a certain spatial correlation with the expressways. 4) The influence of road network expansion on the ecological risk in the study area had obvious spatial differences, which may be closely associated with the distribution of ecosystem types. Copyright © 2016 Office national des forêts. Published by Elsevier B.V. All rights reserved.

Extending natural hazard impacts: an assessment of landslide disruptions on a national road transportation network

NASA Astrophysics Data System (ADS)

Postance, Benjamin; Hillier, John; Dijkstra, Tom; Dixon, Neil

2017-01-01

Disruptions to transportation networks by natural hazard events cause direct losses (e.g. by physical damage) and indirect socio-economic losses via travel delays and decreased transportation efficiency. The severity and spatial distribution of these losses varies according to user travel demands and which links, nodes or infrastructure assets are physically disrupted. Increasing transport network resilience, for example by targeted mitigation strategies, requires the identification of the critical network segments which if disrupted would incur undesirable or unacceptable socio-economic impacts. Here, these impacts are assessed on a national road transportation network by coupling hazard data with a transport network model. This process is illustrated using a case study of landslide hazards on the road network of Scotland. A set of possible landslide-prone road segments is generated using landslide susceptibility data. The results indicate that at least 152 road segments are susceptible to landslides, which could cause indirect economic losses exceeding £35 k for each day of closure. In addition, previous estimates for historic landslide events might be significant underestimates. For example, the estimated losses for the 2007 A83 ‘Rest and Be Thankful’ landslide are £80 k day-1, totalling £1.2 million over a 15 day closure, and are ˜60% greater than previous estimates. The spatial distribution of impact to road users is communicated in terms of ‘extended hazard impact footprints’. These footprints reveal previously unknown exposed communities and unanticipated spatial patterns of severe disruption. Beyond cost-benefit analyses for landslide mitigation efforts, the approach implemented is applicable to other natural hazards (e.g. flooding), combinations of hazards, or even other network disruption events.

Phenotypic constraints promote latent versatility and carbon efficiency in metabolic networks.

PubMed

Bardoscia, Marco; Marsili, Matteo; Samal, Areejit

2015-07-01

System-level properties of metabolic networks may be the direct product of natural selection or arise as a by-product of selection on other properties. Here we study the effect of direct selective pressure for growth or viability in particular environments on two properties of metabolic networks: latent versatility to function in additional environments and carbon usage efficiency. Using a Markov chain Monte Carlo (MCMC) sampling based on flux balance analysis (FBA), we sample from a known biochemical universe random viable metabolic networks that differ in the number of directly constrained environments. We find that the latent versatility of sampled metabolic networks increases with the number of directly constrained environments and with the size of the networks. We then show that the average carbon wastage of sampled metabolic networks across the constrained environments decreases with the number of directly constrained environments and with the size of the networks. Our work expands the growing body of evidence about nonadaptive origins of key functional properties of biological networks.

A Summary of Research on Energy Saving and Emission Reduction of Transportation

NASA Astrophysics Data System (ADS)

Cheng, Dongxiang; Wu, Lufen

2017-12-01

Road transport is an important part of transportation, and road in the field of energy-saving emission reduction is a very important industry. According to the existing problems of road energy saving and emission reduction, this paper elaborates the domestic and international research on energy saving and emission reduction from three aspects: road network optimization, pavement material and pavement maintenance. Road network optimization may be overlooked, and the research content is still relatively preliminary; pavement materials mainly from the asphalt pavement temperature mixed asphalt technology research; pavement maintenance technology development is relatively comprehensive.

Quantification of Road Network Vulnerability and Traffic Impacts to Regional Landslide Hazards.

NASA Astrophysics Data System (ADS)

Postance, Benjamin; Hillier, John; Dixon, Neil; Dijkstra, Tom

2015-04-01

Slope instability represents a prevalent hazard to transport networks. In the UK regional road networks are frequently disrupted by multiple slope failures triggered during intense precipitation events; primarily due to a degree of regional homogeneity of slope materials, geomorphology and weather conditions. It is of interest to examine how different locations and combinations of slope failure impact road networks, particularly in the context of projected climate change and a 40% increase in UK road demand by 2040. In this study an extensive number (>50 000) of multiple failure event scenarios are simulated within a dynamic micro simulation to assess traffic impacts during peak flow (7 - 10 AM). Possible failure locations are selected within the county of Gloucestershire (3150 km2) using historic failure sites and British Geological Survey GeoSure data. Initial investigations employ a multiple linear regression analyses to consider the severity of traffic impacts, as measured by time, in respect of spatial and topographical network characteristics including connectivity, density and capacity in proximity to failure sites; the network distance between disruptions in multiple failure scenarios is used to consider the effects of spatial clustering. The UK Department of Transport road travel demand and UKCP09 weather projection data to 2080 provide a suitable basis for traffic simulations and probabilistic slope stability assessments. Future work will thus focus on the development of a catastrophe risk model to simulate traffic impacts under various narratives of future travel demand and slope instability under climatic change. The results of this investigation shall contribute to the understanding of road network vulnerabilities and traffic impacts from climate driven slope hazards.

Winter risk estimations through infrared cameras an principal component analysis

NASA Astrophysics Data System (ADS)

Marchetti, M.; Dumoulin, J.; Ibos, L.

2012-04-01

Thermal mapping has been implemented since the late eighties to measure road pavement temperature along with some other atmospheric parameters to establish a winter risk describing the susceptibility of road network to ice occurrence. Measurements are done using a vehicle circulating on the road network in various road weather conditions. When the dew point temperature drops below road surface temperature a risk of ice occurs and therefore a loss of grip risk for circulating vehicles. To avoid too much influence of the sun, and to see the thermal behavior of the pavement enhanced, thermal mapping is usually done before dawn during winter time. That is when the energy accumulated by the road during daytime is mainly dissipated (by radiation, by conduction and by convection) and before the road structure starts a new cycle. This analysis is mainly done when a new road network is built, or when some major pavement changes are made, or when modifications in the road surroundings took place that might affect the thermal heat balance. This helps road managers to install sensors to monitor road status on specific locations identified as dangerous, or simply to install specific road signs. Measurements are anyhow time-consuming. Indeed, a whole road network can hardly be analysed at once, and has to be partitioned in stretches that could be done in the open time window to avoid temperature artefacts due to a rising sun. The LRPC Nancy has been using a thermal mapping vehicle with now two infrared cameras. Road events were collected by the operator to help the analysis of the network thermal response. A conventional radiometer with appropriate performances was used as a reference. The objective of the work was to compare results from the radiometer and the cameras. All the atmospheric parameters measured by the different sensors such as air temperature and relative humidity were used as input parameters for the infrared camera when recording thermal images. Road thermal heterogeneities were clearly identified, while usually missed by a conventional radiometer. In the case presented here, the two lanes of the road could be properly observed. Promising perspectives appeared to increase the measurement rate. Furthermore, to cope with the climatic constraints of the winter measurements as to build a dynamic winter risk, a multivariate data analysis approach was implemented. Principal component analysis was performed and enabled to set up of dynamic thermal signature with a great agreement between statistical results and field measurements.

Optimization-based method for automated road network extraction

DOT National Transportation Integrated Search

2001-09-18

Automated road information extraction has significant applicability in transportation. : It provides a means for creating, maintaining, and updating transportation network databases that : are needed for purposes ranging from traffic management to au...

An Energy-Efficient Cluster-Based Vehicle Detection on Road Network Using Intention Numeration Method

PubMed Central

Devasenapathy, Deepa; Kannan, Kathiravan

2015-01-01

The traffic in the road network is progressively increasing at a greater extent. Good knowledge of network traffic can minimize congestions using information pertaining to road network obtained with the aid of communal callers, pavement detectors, and so on. Using these methods, low featured information is generated with respect to the user in the road network. Although the existing schemes obtain urban traffic information, they fail to calculate the energy drain rate of nodes and to locate equilibrium between the overhead and quality of the routing protocol that renders a great challenge. Thus, an energy-efficient cluster-based vehicle detection in road network using the intention numeration method (CVDRN-IN) is developed. Initially, sensor nodes that detect a vehicle are grouped into separate clusters. Further, we approximate the strength of the node drain rate for a cluster using polynomial regression function. In addition, the total node energy is estimated by taking the integral over the area. Finally, enhanced data aggregation is performed to reduce the amount of data transmission using digital signature tree. The experimental performance is evaluated with Dodgers loop sensor data set from UCI repository and the performance evaluation outperforms existing work on energy consumption, clustering efficiency, and node drain rate. PMID:25793221

An energy-efficient cluster-based vehicle detection on road network using intention numeration method.

PubMed

Devasenapathy, Deepa; Kannan, Kathiravan

2015-01-01

The traffic in the road network is progressively increasing at a greater extent. Good knowledge of network traffic can minimize congestions using information pertaining to road network obtained with the aid of communal callers, pavement detectors, and so on. Using these methods, low featured information is generated with respect to the user in the road network. Although the existing schemes obtain urban traffic information, they fail to calculate the energy drain rate of nodes and to locate equilibrium between the overhead and quality of the routing protocol that renders a great challenge. Thus, an energy-efficient cluster-based vehicle detection in road network using the intention numeration method (CVDRN-IN) is developed. Initially, sensor nodes that detect a vehicle are grouped into separate clusters. Further, we approximate the strength of the node drain rate for a cluster using polynomial regression function. In addition, the total node energy is estimated by taking the integral over the area. Finally, enhanced data aggregation is performed to reduce the amount of data transmission using digital signature tree. The experimental performance is evaluated with Dodgers loop sensor data set from UCI repository and the performance evaluation outperforms existing work on energy consumption, clustering efficiency, and node drain rate.

Measuring accessibility of sustainable transportation using space syntax in Bojonggede area

NASA Astrophysics Data System (ADS)

Suryawinata, B. A.; Mariana, Y.; Wijaksono, S.

2017-12-01

Changes in the physical structure of regional space as a result of the increase of planned and unplanned settlements in the Bojonggede area have an impact on the road network pattern system. Changes in road network patterns will have an impact on the permeability of the area. Permeability measures the extent to which road network patterns provide an option in traveling. If the permeability increases the travel distance decreases and the route of travel choice increases, permeability like this can create an easy access system and physically integrated. This study aims to identify the relationship of physical characteristics of residential area and road network pattern to the level of space permeability in Bojonggede area. By conducting this research can be a reference for the arrangement of circulation, accessibility, and land use in the vicinity of Bojonggede. This research uses quantitative method and space syntax method to see global integration and local integration on the region which become the parameter of permeability level. The results showed that the level of permeability globally and locally high in Bojonggede physical area is the physical characteristics of the area that has a grid pattern of road network grid.

Constrained target controllability of complex networks

NASA Astrophysics Data System (ADS)

Guo, Wei-Feng; Zhang, Shao-Wu; Wei, Ze-Gang; Zeng, Tao; Liu, Fei; Zhang, Jingsong; Wu, Fang-Xiang; Chen, Luonan

2017-06-01

It is of great theoretical interest and practical significance to study how to control a system by applying perturbations to only a few driver nodes. Recently, a hot topic of modern network researches is how to determine driver nodes that allow the control of an entire network. However, in practice, to control a complex network, especially a biological network, one may know not only the set of nodes which need to be controlled (i.e. target nodes), but also the set of nodes to which only control signals can be applied (i.e. constrained control nodes). Compared to the general concept of controllability, we introduce the concept of constrained target controllability (CTC) of complex networks, which concerns the ability to drive any state of target nodes to their desirable state by applying control signals to the driver nodes from the set of constrained control nodes. To efficiently investigate the CTC of complex networks, we further design a novel graph-theoretic algorithm called CTCA to estimate the ability of a given network to control targets by choosing driver nodes from the set of constrained control nodes. We extensively evaluate the CTC of numerous real complex networks. The results indicate that biological networks with a higher average degree are easier to control than biological networks with a lower average degree, while electronic networks with a lower average degree are easier to control than web networks with a higher average degree. We also show that our CTCA can more efficiently produce driver nodes for target-controlling the networks than existing state-of-the-art methods. Moreover, we use our CTCA to analyze two expert-curated bio-molecular networks and compare to other state-of-the-art methods. The results illustrate that our CTCA can efficiently identify proven drug targets and new potentials, according to the constrained controllability of those biological networks.

ISED: Constructing a high-resolution elevation road dataset from massive, low-quality in-situ observations derived from geosocial fitness tracking data.

PubMed

McKenzie, Grant; Janowicz, Krzysztof

2017-01-01

Gaining access to inexpensive, high-resolution, up-to-date, three-dimensional road network data is a top priority beyond research, as such data would fuel applications in industry, governments, and the broader public alike. Road network data are openly available via user-generated content such as OpenStreetMap (OSM) but lack the resolution required for many tasks, e.g., emergency management. More importantly, however, few publicly available data offer information on elevation and slope. For most parts of the world, up-to-date digital elevation products with a resolution of less than 10 meters are a distant dream and, if available, those datasets have to be matched to the road network through an error-prone process. In this paper we present a radically different approach by deriving road network elevation data from massive amounts of in-situ observations extracted from user-contributed data from an online social fitness tracking application. While each individual observation may be of low-quality in terms of resolution and accuracy, taken together they form an accurate, high-resolution, up-to-date, three-dimensional road network that excels where other technologies such as LiDAR fail, e.g., in case of overpasses, overhangs, and so forth. In fact, the 1m spatial resolution dataset created in this research based on 350 million individual 3D location fixes has an RMSE of approximately 3.11m compared to a LiDAR-based ground-truth and can be used to enhance existing road network datasets where individual elevation fixes differ by up to 60m. In contrast, using interpolated data from the National Elevation Dataset (NED) results in 4.75m RMSE compared to the base line. We utilize Linked Data technologies to integrate the proposed high-resolution dataset with OpenStreetMap road geometries without requiring any changes to the OSM data model.

Analyses of the response of a complex weighted network to nodes removal strategies considering links weight: The case of the Beijing urban road system

NASA Astrophysics Data System (ADS)

Bellingeri, Michele; Lu, Zhe-Ming; Cassi, Davide; Scotognella, Francesco

2018-02-01

Complex network response to node loss is a central question in different fields of science ranging from physics, sociology, biology to ecology. Previous studies considered binary networks where the weight of the links is not accounted for. However, in real-world networks the weights of connections can be widely different. Here, we analyzed the response of real-world road traffic complex network of Beijing, the most prosperous city in China. We produced nodes removal attack simulations using classic binary node features and we introduced weighted ranks for node importance. We measured the network functioning during nodes removal with three different parameters: the size of the largest connected cluster (LCC), the binary network efficiency (Bin EFF) and the weighted network efficiency (Weg EFF). We find that removing nodes according to weighted rank, i.e. considering the weight of the links as a number of taxi flows along the roads, produced in general the highest damage in the system. Our results show that: (i) in order to model Beijing road complex networks response to nodes (intersections) failure, it is necessary to consider the weight of the links; (ii) to discover the best attack strategy, it is important to use nodes rank accounting links weight.

Optimizing the process of recovery after road network break-up

NASA Astrophysics Data System (ADS)

Bíl, Michal; Vodák, Rostislav; Křivánková, Zuzana

2016-04-01

A functioning road network provides accessibility to municipalities, important services and facilities. This basic role of the network can be disrupted by natural disasters which usually affect large areas and cause temporal blockages or even destruction of many roads at the same time. This often leads to road network break-up, when a number of disconnected parts emerge. These parts are often of varying importance to society. Some of them may contain large cities or important facilities such as hospitals. This should be reflected during reconnection works when the most important parts of the network should be reconnected among the first in order to reduce the impact of the event. Decision makers and crisis managers, however, do still not have any dynamic tool which might help them with prioritizing the necessary steps. In our presentation we introduce an algorithm and examples of suitable loss functions which enable us to rapidly identify isolated parts of the network, evaluate them and consequently establish an optimal ranked sequence of interrupted links which have to be repaired to reduce the consequences of the disasters.

Constrained ℋ∞ control for low bandwidth active suspensions

NASA Astrophysics Data System (ADS)

Wasiwitono, Unggul; Sutantra, I. Nyoman

2017-08-01

Low Bandwidth Active Suspension (LBAS) is shown to be more competitive to High Bandwidth Active Suspension (HBAS) when energy and cost aspects are taken into account. In this paper, the constrained ℋ∞ control scheme is applied for LBAS system. The ℋ∞ performance is used to measure ride comfort while the concept of reachable set in a state-space ellipsoid defined by a quadratic storage function is used to capture the time domain constraint that representing the requirements for road holding, suspension deflection limitation and actuator saturation. Then, the control problem is derived in the framework of Linear Matrix Inequality (LMI) optimization. The simulation is conducted considering the road disturbance as a stationary random process. The achievable performance of LBAS is analyzed for different values of bandwidth and damping ratio.

Complex Road Intersection Modelling Based on Low-Frequency GPS Track Data

NASA Astrophysics Data System (ADS)

Huang, J.; Deng, M.; Zhang, Y.; Liu, H.

2017-09-01

It is widely accepted that digital map becomes an indispensable guide for human daily traveling. Traditional road network maps are produced in the time-consuming and labour-intensive ways, such as digitizing printed maps and extraction from remote sensing images. At present, a large number of GPS trajectory data collected by floating vehicles makes it a reality to extract high-detailed and up-to-date road network information. Road intersections are often accident-prone areas and very critical to route planning and the connectivity of road networks is mainly determined by the topological geometry of road intersections. A few studies paid attention on detecting complex road intersections and mining the attached traffic information (e.g., connectivity, topology and turning restriction) from massive GPS traces. To the authors' knowledge, recent studies mainly used high frequency (1 s sampling rate) trajectory data to detect the crossroads regions or extract rough intersection models. It is still difficult to make use of low frequency (20-100 s) and easily available trajectory data to modelling complex road intersections geometrically and semantically. The paper thus attempts to construct precise models for complex road intersection by using low frequency GPS traces. We propose to firstly extract the complex road intersections by a LCSS-based (Longest Common Subsequence) trajectory clustering method, then delineate the geometry shapes of complex road intersections by a K-segment principle curve algorithm, and finally infer the traffic constraint rules inside the complex intersections.

Road analysis: a tool for cost-effective rehabilitation measures for Finnish roads

NASA Astrophysics Data System (ADS)

Roimela, Petri; Salmenkaita, Seppo; Maijala, Pekka; Saarenketo, Timo

2000-04-01

Public funding for road network maintenance has decreased 30% during the last few years in Finland. Reduced resources, together with the current rehabilitation strategies, will in the long term result in increasing deterioration of the Finnish road network. For this reason road rehabilitation funding should be focused more specifically on those roads and road sections requiring measures and these measures should be optimized to ensure that only the specific problem structure will be repaired. Roadscanners Oy, in cooperation with the Finnish National Road Administration (Finnra), has developed a new and effective Road Analysis technique to survey the condition of roads and road networks. Road Analysis is based on the integrated analysis of the measured data collected from the road under survey. The basic survey methods used in Road Analysis include Ground Penetrating Data (GPR), falling weight deflectometer (FWD), roughness and rutting measurements, pavement distress mapping and GPS-positioning, as well as reference drilling based on preliminary GPR data analysis. The collected road survey data is processed, interpreted, analyzed and classified using Road Doctor software, specifically developed for this purpose. GPR measurements in road analysis are carried out using a 400 MHz ground-coupled antenna and a 1.0 GHz horn antenna. Horn antenna data is used to measure the thickness of the pavement and base course layers, as well as to evaluate their quality based on their dielectric properties. The 400 MHz ground-coupled data is used to estimate the thickness of the pavement structure and embankment. Ground-coupled antenna data is used for subgrade quality estimations and in evaluating the causes of subgrade- related frost defects. GPR data also provides important location information about special structures, such as steel reinforcements, cables and pipelines. Road Analysis includes a classification of the critical elements affecting the lifetime of the road: (1) overall pavement condition, (2) condition assessment of the unbound pavement structure, (3) road fatigue related to subgrade frost-action, (4) drainage condition and (5) local damages, such as settlements of the surveyed road. The results of Road Analysis provide a better understanding of the causes of defects occurring on the road and allow more precise rehabilitation measures for problem layers.

Three-Dimensional Road Network by Fusion of Polarimetric and Interferometric SAR Data

NASA Technical Reports Server (NTRS)

Gamba, P.; Houshmand, B.

1998-01-01

In this paper a fuzzy classification procedure is applied to polarimetric radar measurements, and street pixels are detected. These data are successively grouped into consistent roads by means of a dynamic programming approach based on the fuzzy membership function values. Further fusion of the 2D road network extracted and 3D TOPSAR measurements provides a powerful way to analyze urban infrastructures.

A decision algorithm for determining safe clearing limits for the construction of skid roads

Treesearch

Chris LeDoux

2006-01-01

The majority of the timber harvested in the United States is extracted by ground-based skidders and crawler/dozer systems. Ground-based systems generally require a primary transportation network (a network of skid trails/roads) throughout the area being harvested. Logs are skidded or dragged along these skid roads/trails as they are transported from where they were cut...

Road Nail: Experimental Solar Powered Intelligent Road Marking System

NASA Astrophysics Data System (ADS)

Samardžija, Dragan; Teslić, Nikola; Todorović, Branislav M.; Kovač, Erne; Isailović, Đorđe; Miladinović, Bojan

2012-03-01

Driving in low visibility conditions (night time, fog or heavy precipitation) is particularly challenging task with an increased probability of traffic accidents and possible injuries. Road Nail is a solar powered intelligent road marking system of wirelessly networked signaling devices that improve driver safety in low visibility conditions along hazardous roadways. Nails or signaling devices are autonomous nodes with capability to accumulate energy, exchange wireless messages, detect approaching vehicles and emit signalization light. We have built an experimental test-bed that consists of 20 nodes and a cellular gateway. Implementation details of the above system, including extensive measurements and performance evaluations in realistic field deployments are presented. A novel distributed network topology discovery scheme is proposed which integrates both sensor and wireless communication aspects, where nodes act autonomously. Finally, integration of the Road Nail system with the cellular network and the Internet is described.

Vehicular-networking- and road-weather-related research in Sodankylä

NASA Astrophysics Data System (ADS)

Sukuvaara, Timo; Mäenpää, Kari; Ylitalo, Riika

2016-10-01

Vehicular-networking- and especially safety-related wireless vehicular services have been under intensive research for almost a decade now. Only in recent years has road weather information also been acknowledged to play an important role when aiming to reduce traffic accidents and fatalities via intelligent transport systems (ITSs). Part of the progress can be seen as a result of the Finnish Meteorological Institute's (FMI) long-term research work in Sodankylä within the topic, originally started in 2006. Within multiple research projects, the FMI Arctic Research Centre has been developing wireless vehicular networking and road weather services, in co-operation with the FMI meteorological services team in Helsinki. At the beginning the wireless communication was conducted with traditional Wi-Fi type local area networking, but during the development the system has evolved into a hybrid communication system of a combined vehicular ad hoc networking (VANET) system with special IEEE 802.11p protocol and supporting cellular networking based on a commercial 3G network, not forgetting support for Wi-Fi-based devices also. For piloting purposes and further research, we have established a special combined road weather station (RWS) and roadside unit (RSU), to interact with vehicles as a service hotspot. In the RWS-RSU we have chosen to build support to all major approaches, IEEE 802.11, traditional Wi-Fi and cellular 3G. We employ road weather systems of FMI, along with RWS and vehicle data gathered from vehicles, in the up-to-date localized weather data delivered in real time. IEEE 802.11p vehicular networking is supported with Wi-Fi and 3G communications. This paper briefly introduces the research work related to vehicular networking and road weather services conducted in Sodankylä, as well as the research project involved in this work. The current status of instrumentation, available services and capabilities are presented in order to formulate a clear general view of the research field.

Development of Gis Tool for the Solution of Minimum Spanning Tree Problem using Prim's Algorithm

NASA Astrophysics Data System (ADS)

Dutta, S.; Patra, D.; Shankar, H.; Alok Verma, P.

2014-11-01

minimum spanning tree (MST) of a connected, undirected and weighted network is a tree of that network consisting of all its nodes and the sum of weights of all its edges is minimum among all such possible spanning trees of the same network. In this study, we have developed a new GIS tool using most commonly known rudimentary algorithm called Prim's algorithm to construct the minimum spanning tree of a connected, undirected and weighted road network. This algorithm is based on the weight (adjacency) matrix of a weighted network and helps to solve complex network MST problem easily, efficiently and effectively. The selection of the appropriate algorithm is very essential otherwise it will be very hard to get an optimal result. In case of Road Transportation Network, it is very essential to find the optimal results by considering all the necessary points based on cost factor (time or distance). This paper is based on solving the Minimum Spanning Tree (MST) problem of a road network by finding it's minimum span by considering all the important network junction point. GIS technology is usually used to solve the network related problems like the optimal path problem, travelling salesman problem, vehicle routing problems, location-allocation problems etc. Therefore, in this study we have developed a customized GIS tool using Python script in ArcGIS software for the solution of MST problem for a Road Transportation Network of Dehradun city by considering distance and time as the impedance (cost) factors. It has a number of advantages like the users do not need a greater knowledge of the subject as the tool is user-friendly and that allows to access information varied and adapted the needs of the users. This GIS tool for MST can be applied for a nationwide plan called Prime Minister Gram Sadak Yojana in India to provide optimal all weather road connectivity to unconnected villages (points). This tool is also useful for constructing highways or railways spanning several cities optimally or connecting all cities with minimum total road length.

[Effects of road construction on regional vegetation types].

PubMed

Liu, Shi-Liang; Liu, Qi; Wang, Cong; Yang, Jue-Jie; Deng, Li

2013-05-01

As a regional artificial disturbance component, road exerts great effects on vegetation types, and plays a substantial role in defining vegetation distribution to a certain extent. Aiming at the tropical rainforest degradation and artificial forest expansion in Yunnan Province of Southwest China, this paper analyzed the effects of road network extension on regional vegetation types. In the Province, different classes of roads had different effects on the vegetation types, but no obvious regularity was observed in the effects on the patch areas of different vegetation types due to the great variations of road length and affected distance. However, the vegetation patch number was more affected by lower class roads because of their wide distribution. As for different vegetation types, the vegetations on cultivated land were most affected by roads, followed by Castanopsis hystrix and Schima wallichii forests. Road network formation contributed most to the vegetation fragmentation, and there existed significant correlations between the human disturbance factors including village- and road distributions.

Green infrastructure development at European Union's eastern border: Effects of road infrastructure and forest habitat loss.

PubMed

Angelstam, Per; Khaulyak, Olha; Yamelynets, Taras; Mozgeris, Gintautas; Naumov, Vladimir; Chmielewski, Tadeusz J; Elbakidze, Marine; Manton, Michael; Prots, Bohdan; Valasiuk, Sviataslau

2017-05-15

The functionality of forest patches and networks as green infrastructure may be affected negatively both by expanding road networks and forestry intensification. We assessed the effects of (1) the current and planned road infrastructure, and (2) forest loss and gain, on the remaining large forest landscape massifs as green infrastructure at the EU's eastern border region in post-socialistic transition. First, habitat patch and network functionality in 1996-98 was assessed using habitat suitability index modelling. Second, we made expert interviews about road development with planners in 10 administrative regions in Poland, Belarus and Ukraine. Third, forest loss and gain inside the forest massifs, and gain outside them during the period 2001-14 were measured. This EU cross-border region hosts four remaining forest massifs as regional green infrastructure hotspots. While Poland's road network is developing fast in terms of new freeways, city bypasses and upgrades of road quality, in Belarus and Ukraine the focus is on maintenance of existing roads, and no new corridors. We conclude that economic support from the EU, and thus rapid development of roads in Poland, is likely to reduce the permeability for wildlife of the urban and agricultural matrix around existing forest massifs. However, the four identified forest massifs themselves, forming the forest landscape green infrastructure at the EU's east border, were little affected by road development plans. In contrast, forest loss inside massifs was high, especially in Ukraine. Only in Poland forest loss was balanced by gain. Forest gain outside forest massifs was low. To conclude, pro-active and collaborative spatial planning across different sectors and countries is needed to secure functional forest green infrastructure as base for biodiversity conservation and human well-being. Copyright © 2017. Published by Elsevier Ltd.

Analysis of road development and associated agricultural land use change.

PubMed

Alphan, Hakan

2017-12-05

Development of road network is one of the strongest drivers of habitat fragmentation. It interferes with ecological processes that are based on material and energy flows between landscape patches. Therefore, changes in temporal patterns of roads may be regarded as important landscape-level environmental indicators. The aim of this study is to analyze road development and associated agricultural land use change near the town of Erdemli located in the eastern Mediterranean coast of Turkey. The study area has witnessed an unprecedented development of agriculture since the 2000s. This process has resulted with the expansion of the road network. Associations between agricultural expansion and road development were investigated. High-resolution satellite images of 2004 and 2015 were used to analyze spatial and temporal dimensions of change. Satellite images were classified using a binary approach, in which land areas were labeled as either "agriculture" or "non-agriculture." Road networks were digitized manually. The study area was divided into 23 sublandscapes using a regular grid with 1-km cell spacing. Percentage of landscape (PL) for agriculture and road density (RD) metrics were calculated for the earlier (2004) and later (2015) years. Metric calculations were performed separately for each of the 23 sublandscapes in order to understand spatial diversity of agriculture and road density. Study results showed that both RD and PL exhibited similar increasing trends between 2004 and 2015.

Road Network Extraction from Dsm by Mathematical Morphology and Reasoning

NASA Astrophysics Data System (ADS)

Li, Yan; Wu, Jianliang; Zhu, Lin; Tachibana, Kikuo

2016-06-01

The objective of this research is the automatic extraction of the road network in a scene of the urban area from a high resolution digital surface model (DSM). Automatic road extraction and modeling from remote sensed data has been studied for more than one decade. The methods vary greatly due to the differences of data types, regions, resolutions et al. An advanced automatic road network extraction scheme is proposed to address the issues of tedium steps on segmentation, recognition and grouping. It is on the basis of a geometric road model which describes a multiple-level structure. The 0-dimension element is intersection. The 1-dimension elements are central line and side. The 2-dimension element is plane, which is generated from the 1-dimension elements. The key feature of the presented approach is the cross validation for the three road elements which goes through the entire procedure of their extraction. The advantage of our model and method is that linear elements of the road can be derived directly, without any complex, non-robust connection hypothesis. An example of Japanese scene is presented to display the procedure and the performance of the approach.

A multiclass vehicular dynamic traffic flow model for main roads and dedicated lanes/roads of multimodal transport network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sossoe, K.S., E-mail: kwami.sossoe@irt-systemx.fr; Lebacque, J-P., E-mail: jean-patrick.lebacque@ifsttar.fr

2015-03-10

We present in this paper a model of vehicular traffic flow for a multimodal transportation road network. We introduce the notion of class of vehicles to refer to vehicles of different transport modes. Our model describes the traffic on highways (which may contain several lanes) and network transit for pubic transportation. The model is drafted with Eulerian and Lagrangian coordinates and uses a Logit model to describe the traffic assignment of our multiclass vehicular flow description on shared roads. The paper also discusses traffic streams on dedicated lanes for specific class of vehicles with event-based traffic laws. An Euler-Lagrangian-remap schememore » is introduced to numerically approximate the model’s flow equations.« less

Inventory of Amphibians and Reptiles in Southern Colorado Plateau National Parks

USGS Publications Warehouse

Persons, Trevor B.; Nowak, Erika M.

2006-01-01

In fiscal year 2000, the National Park Service (NPS) initiated a nationwide program to inventory vertebrates andvascular plants within the National Parks, and an inventory plan was developed for the 19 park units in the Southern Colorado Plateau Inventory & Monitoring Network. We surveyed 12 parks in this network for reptiles and amphibians between 2001 and 2003. The overall goals of our herpetofaunal inventories were to document 90% of the species present, identify park-specific species of special concern, and, based on the inventory results, make recommendations for the development of an effective monitoring program. We used the following standardized herpetological methods to complete the inventories: time-area constrained searches, visual encounter ('general') surveys, and nighttime road cruising. We also recorded incidental species sightings and surveyed existing literature and museum specimen databases. We found 50 amphibian and reptile species during fieldwork. These included 1 salamander, 11 anurans, 21 lizards, and 17 snakes. Literature reviews, museum specimen data records, and personal communications with NPS staff added an additional eight species, including one salamander, one turtle, one lizard, and five snakes. It was necessary to use a variety of methods to detect all species in each park. Randomly-generated 1-ha time-area constrained searches and night drives produced the fewest species and individuals of all the methods, while general surveys and randomly-generated 10-ha time-areas constrained searches produced the most. Inventory completeness was likely compromised by a severe drought across the region during our surveys. In most parks we did not come close to the goal of detecting 90% of the expected species present; however, we did document several species range extensions. Effective monitoring programs for herpetofauna on the Colorado Plateau should use a variety of methods to detect species, and focus on taxa-specific methods. Randomly-generated plots must take into account microhabitat and aquatic features to be effective at sampling for herpetofauna.

PANATIKI: A Network Access Control Implementation Based on PANA for IoT Devices

PubMed Central

Sanchez, Pedro Moreno; Lopez, Rafa Marin; Gomez Skarmeta, Antonio F.

2013-01-01

Internet of Things (IoT) networks are the pillar of recent novel scenarios, such as smart cities or e-healthcare applications. Among other challenges, these networks cover the deployment and interaction of small devices with constrained capabilities and Internet protocol (IP)-based networking connectivity. These constrained devices usually require connection to the Internet to exchange information (e.g., management or sensing data) or access network services. However, only authenticated and authorized devices can, in general, establish this connection. The so-called authentication, authorization and accounting (AAA) services are in charge of performing these tasks on the Internet. Thus, it is necessary to deploy protocols that allow constrained devices to verify their credentials against AAA infrastructures. The Protocol for Carrying Authentication for Network Access (PANA) has been standardized by the Internet engineering task force (IETF) to carry the Extensible Authentication Protocol (EAP), which provides flexible authentication upon the presence of AAA. To the best of our knowledge, this paper is the first deep study of the feasibility of EAP/PANA for network access control in constrained devices. We provide light-weight versions and implementations of these protocols to fit them into constrained devices. These versions have been designed to reduce the impact in standard specifications. The goal of this work is two-fold: (1) to demonstrate the feasibility of EAP/PANA in IoT devices; (2) to provide the scientific community with the first light-weight interoperable implementation of EAP/PANA for constrained devices in the Contiki operating system (Contiki OS), called PANATIKI. The paper also shows a testbed, simulations and experimental results obtained from real and simulated constrained devices. PMID:24189332

PANATIKI: a network access control implementation based on PANA for IoT devices.

PubMed

Moreno Sanchez, Pedro; Marin Lopez, Rafa; Gomez Skarmeta, Antonio F

2013-11-01

Internet of Things (IoT) networks are the pillar of recent novel scenarios, such as smart cities or e-healthcare applications. Among other challenges, these networks cover the deployment and interaction of small devices with constrained capabilities and Internet protocol (IP)-based networking connectivity. These constrained devices usually require connection to the Internet to exchange information (e.g., management or sensing data) or access network services. However, only authenticated and authorized devices can, in general, establish this connection. The so-called authentication, authorization and accounting (AAA) services are in charge of performing these tasks on the Internet. Thus, it is necessary to deploy protocols that allow constrained devices to verify their credentials against AAA infrastructures. The Protocol for Carrying Authentication for Network Access (PANA) has been standardized by the Internet engineering task force (IETF) to carry the Extensible Authentication Protocol (EAP), which provides flexible authentication upon the presence of AAA. To the best of our knowledge, this paper is the first deep study of the feasibility of EAP/PANA for network access control in constrained devices. We provide light-weight versions and implementations of these protocols to fit them into constrained devices. These versions have been designed to reduce the impact in standard specifications. The goal of this work is two-fold: (1) to demonstrate the feasibility of EAP/PANA in IoT devices; (2) to provide the scientific community with the first light-weight interoperable implementation of EAP/PANA for constrained devices in the Contiki operating system (Contiki OS), called PANATIKI. The paper also shows a testbed, simulations and experimental results obtained from real and simulated constrained devices.

Road detection in SAR images using a tensor voting algorithm

NASA Astrophysics Data System (ADS)

Shen, Dajiang; Hu, Chun; Yang, Bing; Tian, Jinwen; Liu, Jian

2007-11-01

In this paper, the problem of the detection of road networks in Synthetic Aperture Radar (SAR) images is addressed. Most of the previous methods extract the road by detecting lines and network reconstruction. Traditional algorithms such as MRFs, GA, Level Set, used in the progress of reconstruction are iterative. The tensor voting methodology we proposed is non-iterative, and non-sensitive to initialization. Furthermore, the only free parameter is the size of the neighborhood, related to the scale. The algorithm we present is verified to be effective when it's applied to the road extraction using the real Radarsat Image.

Prediction of road accidents: A Bayesian hierarchical approach.

PubMed

Deublein, Markus; Schubert, Matthias; Adey, Bryan T; Köhler, Jochen; Faber, Michael H

2013-03-01

In this paper a novel methodology for the prediction of the occurrence of road accidents is presented. The methodology utilizes a combination of three statistical methods: (1) gamma-updating of the occurrence rates of injury accidents and injured road users, (2) hierarchical multivariate Poisson-lognormal regression analysis taking into account correlations amongst multiple dependent model response variables and effects of discrete accident count data e.g. over-dispersion, and (3) Bayesian inference algorithms, which are applied by means of data mining techniques supported by Bayesian Probabilistic Networks in order to represent non-linearity between risk indicating and model response variables, as well as different types of uncertainties which might be present in the development of the specific models. Prior Bayesian Probabilistic Networks are first established by means of multivariate regression analysis of the observed frequencies of the model response variables, e.g. the occurrence of an accident, and observed values of the risk indicating variables, e.g. degree of road curvature. Subsequently, parameter learning is done using updating algorithms, to determine the posterior predictive probability distributions of the model response variables, conditional on the values of the risk indicating variables. The methodology is illustrated through a case study using data of the Austrian rural motorway network. In the case study, on randomly selected road segments the methodology is used to produce a model to predict the expected number of accidents in which an injury has occurred and the expected number of light, severe and fatally injured road users. Additionally, the methodology is used for geo-referenced identification of road sections with increased occurrence probabilities of injury accident events on a road link between two Austrian cities. It is shown that the proposed methodology can be used to develop models to estimate the occurrence of road accidents for any road network provided that the required data are available. Copyright © 2012 Elsevier Ltd. All rights reserved.

Segmentation and classification of road markings using MLS data

NASA Astrophysics Data System (ADS)

Soilán, Mario; Riveiro, Belén; Martínez-Sánchez, Joaquín; Arias, Pedro

2017-01-01

Traffic signs are one of the most important safety elements in a road network. Particularly, road markings provide information about the limits and direction of each road lane, or warn the drivers about potential danger. The optimal condition of road markings contributes to a better road safety. Mobile Laser Scanning technology can be used for infrastructure inspection and specifically for traffic sign detection and inventory. This paper presents a methodology for the detection and semantic characterization of the most common road markings, namely pedestrian crossings and arrows. The 3D point cloud data acquired by a LYNX Mobile Mapper system is filtered in order to isolate reflective points in the road, and each single element is hierarchically classified using Neural Networks. State of the art results are obtained for the extraction and classification of the markings, with F-scores of 94% and 96% respectively. Finally, data from classified markings are exported to a GIS layer and maintenance criteria based on the aforementioned data are proposed.

Using a geographic information system to enhance patient access to point-of-care diagnostics in a limited-resource setting.

PubMed

Ferguson, William J; Kemp, Karen; Kost, Gerald

2016-03-01

Rapid and accurate diagnosis drives evidence-based care in health. Point-of-care testing (POCT) aids diagnosis by bringing advanced technologies closer to patients. Health small-world networks are constrained by natural connectivity in the interactions between geography of resources and social forces. Using a geographic information system (GIS) we can understand how populations utilize their health networks, visualize their inefficiencies, and compare alternatives. This project focuses on cardiac care resource in rural Isaan, Thailand. A health care access analysis was created using ArcGIS Network Analyst 10.1 from data representing aggregated population, roads, health resource facilities, and diagnostic technologies. The analysis quantified cardiac health care access and identified ways to improve it using both widespread and resource-limited strategies. Results indicated that having diagnostic technologies closer to populations streamlines critical care paths. GIS allowed us to compare the effectiveness of the implementation strategies and put into perspective the benefits of adopting rapid POCT within health networks. Geospatial analyses derive high impact by improving alternative diagnostic placement strategies in limited-resource settings and by revealing deficiencies in health care access pathways. Additionally, the GIS provides a platform for comparing relative costs, assessing benefits, and improving outcomes. This approach can be implemented effectively by health ministries seeking to enhance cardiac care despite limited resources.

Seismic risk assessment for road in Indonesia

NASA Astrophysics Data System (ADS)

Toyfur, Mona Foralisa; Pribadi, Krishna S.

2016-05-01

Road networks in Indonesia consist of 446,000 km of national, provincial and local roads as well as toll highways. Indonesia is one of countries that exposed to various natural hazards, such as earthquakes, floods, landslides, etc. Within the Indonesian archipelago, several global tectonic plates interact, such as the Indo-Australian, Pacific, Eurasian, resulting in a complex geological setting, characterized by the existence of seismically active faults and subduction zones and a chain of more than one hundred active volcanoes. Roads in Indonesia are vital infrastructure needed for people and goods movement, thus supporting community life and economic activities, including promoting regional economic development. Road damages and losses due to earthquakes have not been studied widely, whereas road disruption caused enormous economic damage. The aim of this research is to develop a method to analyse risk caused by seismic hazard to roads. The seismic risk level of road segment is defined using an earthquake risk index, adopting the method of Earthquake Disaster Risk Index model developed by Davidson (1997). Using this method, road segments' risk level can be defined and compared, and road risk map can be developed as a tool for prioritizing risk mitigation programs for road networks in Indonesia.

Near-Road Air Quality Monitoring: Factors Affecting Network Design and Interpretation of Data

EPA Science Inventory

The growing number of health studies identifying adverse health effects for populations spending significant amounts of time near large roadways has increased the interest in monitoring air quality in this microenvironment. Designing near-road air monitoring networks or interpret...

Silk Roads or Steppe Roads? The Silk Roads in World History.

ERIC Educational Resources Information Center

Christian, David

2000-01-01

Explores the prehistory of the Silk Roads, reexamines their structure and history in the classical era, and explores shifts in their geography in the last one thousand years. Explains that a revised understanding of the Silk Roads demonstrates how the Afro-Eurasian land mass has been linked by networks of exchange since the Bronze Age. (CMK)

Recent findings related to measuring and modeling forest road erosion

Treesearch

W. J. Elliot; R. B. Foltz; P. R. Robichaud

2009-01-01

Sediment is the greatest pollutant of forest streams. In the absence of wildfire, forest road networks are usually the main source of sediment in forest watersheds. An understanding of forest road erosion processes is important to aid in predicting sediment delivery from roads to streams. The flowpath followed by runoff is the key to understanding road erosion...

Loudoun County road orders : 1757-1783.

DOT National Transportation Integrated Search

2013-05-01

The road history projects undertaken by the Virginia Center for Transportation Innovation and Research (formerly the : Virginia Transportation Research Council) establish the feasibility of studies of early road networks and their use in the : enviro...

Loudoun County road orders : 1783-1800.

DOT National Transportation Integrated Search

2015-04-01

The road history projects undertaken by the Virginia Center for Transportation Innovation and Research (formerly the : Virginia Transportation Research Council) establish the feasibility of studies of early road networks and their use in the : enviro...

Automatic Road Sign Inventory Using Mobile Mapping Systems

NASA Astrophysics Data System (ADS)

Soilán, M.; Riveiro, B.; Martínez-Sánchez, J.; Arias, P.

2016-06-01

The periodic inspection of certain infrastructure features plays a key role for road network safety and preservation, and for developing optimal maintenance planning that minimize the life-cycle cost of the inspected features. Mobile Mapping Systems (MMS) use laser scanner technology in order to collect dense and precise three-dimensional point clouds that gather both geometric and radiometric information of the road network. Furthermore, time-stamped RGB imagery that is synchronized with the MMS trajectory is also available. In this paper a methodology for the automatic detection and classification of road signs from point cloud and imagery data provided by a LYNX Mobile Mapper System is presented. First, road signs are detected in the point cloud. Subsequently, the inventory is enriched with geometrical and contextual data such as orientation or distance to the trajectory. Finally, semantic content is given to the detected road signs. As point cloud resolution is insufficient, RGB imagery is used projecting the 3D points in the corresponding images and analysing the RGB data within the bounding box defined by the projected points. The methodology was tested in urban and road environments in Spain, obtaining global recall results greater than 95%, and F-score greater than 90%. In this way, inventory data is obtained in a fast, reliable manner, and it can be applied to improve the maintenance planning of the road network, or to feed a Spatial Information System (SIS), thus, road sign information can be available to be used in a Smart City context.

Development and testing of operational incident detection algorithms : technical report

DOT National Transportation Integrated Search

2000-11-01

There are over 1.6 million miles of unpaved roads (53% of all roads) in the United States. In some nations, the road network is predominantly unpaved and generally consists of gravel roads. The purpose of this manual is to provide clear and helpful i...

Accessibility assessment of Houston's roadway network during Harvey through integration of observed flood impacts and hydrologic modeling

NASA Astrophysics Data System (ADS)

Gidaris, I.; Gori, A.; Panakkal, P.; Padgett, J.; Bedient, P. B.

2017-12-01

The record-breaking rainfall produced over the Houston region by Hurricane Harvey resulted in catastrophic and unprecedented impacts on the region's infrastructure. Notably, Houston's transportation network was crippled, with almost every major highway flooded during the five-day event. Entire neighborhoods and subdivisions were inundated, rendering them completely inaccessible to rescue crews and emergency services. Harvey has tragically highlighted the vulnerability of major thoroughfares, as well as neighborhood roads, to severe inundation during extreme precipitation events. Furthermore, it has emphasized the need for detailed accessibility characterization of road networks under extreme event scenarios in order to determine which areas of the city are most vulnerable. This analysis assesses and tracks the accessibility of Houston's major highways during Harvey's evolution by utilizing road flood/closure data from the Texas DOT. In the absence of flooded/closure data for local roads, a hybrid approach is adopted that utilizes a physics-based hydrologic model to produce high-resolution inundation estimates for selected urban watersheds in the Houston area. In particular, hydrologic output in the form of inundation depths is used to estimate the operability of local roads. Ultimately, integration of hydrologic-based estimation of road conditions with observed data from DOT supports a network accessibility analysis of selected urban neighborhoods. This accessibility analysis can identify operable routes for emergency response (rescue crews, medical services, etc.) during the storm event.

Integrating fuzzy object based image analysis and ant colony optimization for road extraction from remotely sensed images

NASA Astrophysics Data System (ADS)

Maboudi, Mehdi; Amini, Jalal; Malihi, Shirin; Hahn, Michael

2018-04-01

Updated road network as a crucial part of the transportation database plays an important role in various applications. Thus, increasing the automation of the road extraction approaches from remote sensing images has been the subject of extensive research. In this paper, we propose an object based road extraction approach from very high resolution satellite images. Based on the object based image analysis, our approach incorporates various spatial, spectral, and textural objects' descriptors, the capabilities of the fuzzy logic system for handling the uncertainties in road modelling, and the effectiveness and suitability of ant colony algorithm for optimization of network related problems. Four VHR optical satellite images which are acquired by Worldview-2 and IKONOS satellites are used in order to evaluate the proposed approach. Evaluation of the extracted road networks shows that the average completeness, correctness, and quality of the results can reach 89%, 93% and 83% respectively, indicating that the proposed approach is applicable for urban road extraction. We also analyzed the sensitivity of our algorithm to different ant colony optimization parameter values. Comparison of the achieved results with the results of four state-of-the-art algorithms and quantifying the robustness of the fuzzy rule set demonstrate that the proposed approach is both efficient and transferable to other comparable images.

ELECTRIC VEHICLE CONVERSIONS USING ALTERNATIVE ENERGY TO DRIVE ALASKAN RURAL COMMUNITIES

EPA Science Inventory

This proposal concerns sustainable transportation in rural Alaskan communities which are not part of a road or electrical network (off grid). In most off-grid communities, the road networks generally are less than 50 square miles, so transportation needs are limited. This limi...

Assessing impacts of roads: Application of a standard assessment protocol

USDA-ARS?s Scientific Manuscript database

Adaptive management of road networks depends on timely data that accurately reflect the impacts of network impacts on ecosystem processes and associated services. In the absence of reliable data, land managers are left with little more than observations and perceptions to support adaptive management...

Passive ranging redundancy reduction in diurnal weather conditions

NASA Astrophysics Data System (ADS)

Cha, Jae H.; Abbott, A. Lynn; Szu, Harold H.

2013-05-01

Ambiguity in binocular ranging (David Marr's paradox) may be resolved by using two eyes moving from side to side behind an optical bench while integrating multiple views. Moving a head from left to right with one eye closed can also help resolve the foreground and background range uncertainty. That empirical experiment implies redundancy in image data, which may be reduced by adopting a 3-D camera imaging model to perform compressive sensing. Here, the compressive sensing concept is examined from the perspective of redundancy reduction in images subject to diurnal and weather variations for the purpose of resolving range uncertainty at all weather conditions such as the dawn or dusk, the daytime with different light level or the nighttime at different spectral band. As an example, a scenario at an intersection of a country road at dawn/dusk is discussed where the location of the traffic signs needs to be resolved by passive ranging to answer whether it is located on the same side of the road or the opposite side, which is under the influence of temporal light/color level variation. A spectral band extrapolation via application of Lagrange Constrained Neural Network (LCNN) learning algorithm is discussed to address lost color restoration at dawn/dusk. A numerical simulation is illustrated along with the code example.

Road and Roadside Feature Extraction Using Imagery and LIDAR Data for Transportation Operation

NASA Astrophysics Data System (ADS)

Ural, S.; Shan, J.; Romero, M. A.; Tarko, A.

2015-03-01

Transportation agencies require up-to-date, reliable, and feasibly acquired information on road geometry and features within proximity to the roads as input for evaluating and prioritizing new or improvement road projects. The information needed for a robust evaluation of road projects includes road centerline, width, and extent together with the average grade, cross-sections, and obstructions near the travelled way. Remote sensing is equipped with a large collection of data and well-established tools for acquiring the information and extracting aforementioned various road features at various levels and scopes. Even with many remote sensing data and methods available for road extraction, transportation operation requires more than the centerlines. Acquiring information that is spatially coherent at the operational level for the entire road system is challenging and needs multiple data sources to be integrated. In the presented study, we established a framework that used data from multiple sources, including one-foot resolution color infrared orthophotos, airborne LiDAR point clouds, and existing spatially non-accurate ancillary road networks. We were able to extract 90.25% of a total of 23.6 miles of road networks together with estimated road width, average grade along the road, and cross sections at specified intervals. Also, we have extracted buildings and vegetation within a predetermined proximity to the extracted road extent. 90.6% of 107 existing buildings were correctly identified with 31% false detection rate.

Monitoring and assessing global impacts of roads and off-road vehicle traffic

USDA-ARS?s Scientific Manuscript database

Rapid increases in the number of vehicles, urban sprawl, exurban development and infrastructure development for energy and water have led to dramatic increases in both the size and extent of the global road network. Anecdotal evidence suggests that off-road vehicle traffic has also increased in many...

Road maintenance and rehabilitation : funding and allocation strategies

DOT National Transportation Integrated Search

1994-01-24

With ageing road infrastructure and sustained traffic growth, the maintenance and rehabilitation of road and motorway networks require increased funding. Adequate allocation and distribution of available resources are therefore a key policy issue. Th...

Frederick County road orders 1743-1772.

DOT National Transportation Integrated Search

2005-01-01

The road history projects undertaken by the Virginia Transportation Research Council establish the feasibility of studies of early road networks and their use in the environmental review process. These projects, by gathering and publishing the early ...

Fincastle County road orders 1773-1776.

DOT National Transportation Integrated Search

2007-01-01

The road history projects undertaken by the Virginia Transportation Research Council establish the feasibility of studies of early road networks and their use in the environmental review process. These projects, by gathering and publishing the early ...

Montgomery County road orders 1777-1806.

DOT National Transportation Integrated Search

2008-01-01

The road history projects undertaken by the Virginia Transportation Research Council establish the feasibility of studies of early road networks and their use in the environmental review process. These projects, by gathering and publishing the early ...

Amelia County road orders, 1735-1753.

DOT National Transportation Integrated Search

2002-01-01

The road history projects undertaken by the Virginia Transportation Research Council establish the feasibility of studies of early road networks and their use in the environmental review process. These projects, by gathering and publishing the early ...

Botetourt County road orders 1770-1778.

DOT National Transportation Integrated Search

2007-01-01

The road history projects undertaken by the Virginia Transportation Research Council establish the feasibility of studies of early road networks and their use in the environmental review process. These projects, by gathering and publishing the early ...

Fairfax County road orders, 1749-1800.

DOT National Transportation Integrated Search

2003-01-01

The road history projects undertaken by the Virginia Transportation Research Council establish the feasibility of studies of early road networks and their use in the environmental review process. These projects, by gathering and publishing the early ...

On the use of space photography for identifying transportation routes: A summary of problems

NASA Technical Reports Server (NTRS)

Simonett, D. S.; Henderson, F. M.; Egbert, D. D.

1970-01-01

It has been widely suggested that space photography may be used for updating maps of transportation networks. Proponents of the argument have suggested that color space photographs of the resolution obtained with Hasselblad 80 mm lenses (about 300 feet) contain enough useful information to update the extensions of major U. S. highways. The present study systematically documents for the Dallas-Fort Worth area the potential of such space photography in detecting, and to a lesser degree identifying, the existing road networks. Color separation plates and an enlargement of the color photograph were produced and all visible roads traced onto transparencies for study. Major roads and roads under construction were the most visible while lower class roads and roads in urban areas had the poorest return. Road width and classification were found to be the major determinant in visibility, varying from 100 per cent visible for divided highways to 15 per cent visible of bladed earth roads. In summary, space photographs of this resolution proved to be difficult to use for accurate road delineation. Only super highways in rural areas with the greatest road-width were completely identifiable, the width being about 1/3 that of the resolution cell.

Evaluating the Influence of Road Lighting on Traffic Safety at Accesses Using An Artificial Neural Network.

PubMed

Xu, Yueru; Ye, Zhirui; Wang, Yuan; Wang, Chao; Sun, Cuicui

2018-05-18

This paper focuses on the effect of road lighting on road safety at accesses and tries to quantitatively analyze the relationship between road lighting and road safety. An Artificial Neural Network (ANN) was applied in this study. This method is one of the most popular machine-learning methods in recent years and does not require any pre-defined assumptions. This method was applied using field data collected from ten road segments in Nanjing, Jiangsu Province, China. The results show that the impact of road lighting on road safety at accesses is significant. In addition, road lighting has greater influence when vehicle speeds are higher or the number of lanes is larger. A threshold illuminance was also found in this paper, and the results show that the safety level at accesses will become stable when reaching this value. The improvement of illuminance can decrease the speed variation among vehicles and improve the safety level. In addition, high-grade roads need better illuminance at accesses. A threshold value can also be obtained based on related variables and used to develop scientific guidelines for traffic management organizations.

Recognition of Damaged Arrow-Road Markings by Visible Light Camera Sensor Based on Convolutional Neural Network.

PubMed

Vokhidov, Husan; Hong, Hyung Gil; Kang, Jin Kyu; Hoang, Toan Minh; Park, Kang Ryoung

2016-12-16

Automobile driver information as displayed on marked road signs indicates the state of the road, traffic conditions, proximity to schools, etc. These signs are important to insure the safety of the driver and pedestrians. They are also important input to the automated advanced driver assistance system (ADAS), installed in many automobiles. Over time, the arrow-road markings may be eroded or otherwise damaged by automobile contact, making it difficult for the driver to correctly identify the marking. Failure to properly identify an arrow-road marker creates a dangerous situation that may result in traffic accidents or pedestrian injury. Very little research exists that studies the problem of automated identification of damaged arrow-road marking painted on the road. In this study, we propose a method that uses a convolutional neural network (CNN) to recognize six types of arrow-road markings, possibly damaged, by visible light camera sensor. Experimental results with six databases of Road marking dataset, KITTI dataset, Málaga dataset 2009, Málaga urban dataset, Naver street view dataset, and Road/Lane detection evaluation 2013 dataset, show that our method outperforms conventional methods.

Recognition of Damaged Arrow-Road Markings by Visible Light Camera Sensor Based on Convolutional Neural Network

PubMed Central

Vokhidov, Husan; Hong, Hyung Gil; Kang, Jin Kyu; Hoang, Toan Minh; Park, Kang Ryoung

2016-01-01

Automobile driver information as displayed on marked road signs indicates the state of the road, traffic conditions, proximity to schools, etc. These signs are important to insure the safety of the driver and pedestrians. They are also important input to the automated advanced driver assistance system (ADAS), installed in many automobiles. Over time, the arrow-road markings may be eroded or otherwise damaged by automobile contact, making it difficult for the driver to correctly identify the marking. Failure to properly identify an arrow-road marker creates a dangerous situation that may result in traffic accidents or pedestrian injury. Very little research exists that studies the problem of automated identification of damaged arrow-road marking painted on the road. In this study, we propose a method that uses a convolutional neural network (CNN) to recognize six types of arrow-road markings, possibly damaged, by visible light camera sensor. Experimental results with six databases of Road marking dataset, KITTI dataset, Málaga dataset 2009, Málaga urban dataset, Naver street view dataset, and Road/Lane detection evaluation 2013 dataset, show that our method outperforms conventional methods. PMID:27999301

Genomic signatures of evolutionary transitions from solitary to group living

PubMed Central

Kapheim, Karen M.; Pan, Hailin; Li, Cai; Salzberg, Steven L.; Puiu, Daniela; Magoc, Tanja; Robertson, Hugh M.; Hudson, Matthew E.; Venkat, Aarti; Fischman, Brielle J.; Hernandez, Alvaro; Yandell, Mark; Ence, Daniel; Holt, Carson; Yocum, George D.; Kemp, William P.; Bosch, Jordi; Waterhouse, Robert M.; Zdobnov, Evgeny M.; Stolle, Eckart; Kraus, F. Bernhard; Helbing, Sophie; Moritz, Robin F. A.; Glastad, Karl M.; Hunt, Brendan G.; Goodisman, Michael A. D.; Hauser, Frank; Grimmelikhuijzen, Cornelis J. P.; Pinheiro, Daniel Guariz; Nunes, Francis Morais Franco; Soares, Michelle Prioli Miranda; Tanaka, Érica Donato; Simões, Zilá Luz Paulino; Hartfelder, Klaus; Evans, Jay D.; Barribeau, Seth M.; Johnson, Reed M.; Massey, Jonathan H.; Southey, Bruce R.; Hasselmann, Martin; Hamacher, Daniel; Biewer, Matthias; Kent, Clement F.; Zayed, Amro; Blatti, Charles; Sinha, Saurabh; Johnston, J. Spencer; Hanrahan, Shawn J.; Kocher, Sarah D.; Wang, Jun; Robinson, Gene E.; Zhang, Guojie

2017-01-01

The evolution of eusociality is one of the major transitions in evolution, but the underlying genomic changes are unknown. We compared the genomes of 10 bee species that vary in social complexity, representing multiple independent transitions in social evolution, and report three major findings. First, many important genes show evidence of neutral evolution as a consequence of relaxed selection with increasing social complexity. Second, there is no single road map to eusociality; independent evolutionary transitions in sociality have independent genetic underpinnings. Third, though clearly independent in detail, these transitions do have similar general features, including an increase in constrained protein evolution accompanied by increases in the potential for gene regulation and decreases in diversity and abundance of transposable elements. Eusociality may arise through different mechanisms each time, but would likely always involve an increase in the complexity of gene networks. PMID:25977371

Social evolution. Genomic signatures of evolutionary transitions from solitary to group living.

PubMed

Kapheim, Karen M; Pan, Hailin; Li, Cai; Salzberg, Steven L; Puiu, Daniela; Magoc, Tanja; Robertson, Hugh M; Hudson, Matthew E; Venkat, Aarti; Fischman, Brielle J; Hernandez, Alvaro; Yandell, Mark; Ence, Daniel; Holt, Carson; Yocum, George D; Kemp, William P; Bosch, Jordi; Waterhouse, Robert M; Zdobnov, Evgeny M; Stolle, Eckart; Kraus, F Bernhard; Helbing, Sophie; Moritz, Robin F A; Glastad, Karl M; Hunt, Brendan G; Goodisman, Michael A D; Hauser, Frank; Grimmelikhuijzen, Cornelis J P; Pinheiro, Daniel Guariz; Nunes, Francis Morais Franco; Soares, Michelle Prioli Miranda; Tanaka, Érica Donato; Simões, Zilá Luz Paulino; Hartfelder, Klaus; Evans, Jay D; Barribeau, Seth M; Johnson, Reed M; Massey, Jonathan H; Southey, Bruce R; Hasselmann, Martin; Hamacher, Daniel; Biewer, Matthias; Kent, Clement F; Zayed, Amro; Blatti, Charles; Sinha, Saurabh; Johnston, J Spencer; Hanrahan, Shawn J; Kocher, Sarah D; Wang, Jun; Robinson, Gene E; Zhang, Guojie

2015-06-05

The evolution of eusociality is one of the major transitions in evolution, but the underlying genomic changes are unknown. We compared the genomes of 10 bee species that vary in social complexity, representing multiple independent transitions in social evolution, and report three major findings. First, many important genes show evidence of neutral evolution as a consequence of relaxed selection with increasing social complexity. Second, there is no single road map to eusociality; independent evolutionary transitions in sociality have independent genetic underpinnings. Third, though clearly independent in detail, these transitions do have similar general features, including an increase in constrained protein evolution accompanied by increases in the potential for gene regulation and decreases in diversity and abundance of transposable elements. Eusociality may arise through different mechanisms each time, but would likely always involve an increase in the complexity of gene networks. Copyright © 2015, American Association for the Advancement of Science.

Global Optimization of Emergency Evacuation Assignments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Han, Lee; Yuan, Fang; Chin, Shih-Miao

2006-01-01

Conventional emergency evacuation plans often assign evacuees to fixed routes or destinations based mainly on geographic proximity. Such approaches can be inefficient if the roads are congested, blocked, or otherwise dangerous because of the emergency. By not constraining evacuees to prespecified destinations, a one-destination evacuation approach provides flexibility in the optimization process. We present a framework for the simultaneous optimization of evacuation-traffic distribution and assignment. Based on the one-destination evacuation concept, we can obtain the optimal destination and route assignment by solving a one-destination traffic-assignment problem on a modified network representation. In a county-wide, large-scale evacuation case study, the one-destinationmore » model yields substantial improvement over the conventional approach, with the overall evacuation time reduced by more than 60 percent. More importantly, emergency planners can easily implement this framework by instructing evacuees to go to destinations that the one-destination optimization process selects.« less

Developments in Stochastic Fuel Efficient Cruise Control and Constrained Control with Applications to Aircraft

NASA Astrophysics Data System (ADS)

McDonough, Kevin K.

The dissertation presents contributions to fuel-efficient control of vehicle speed and constrained control with applications to aircraft. In the first part of this dissertation a stochastic approach to fuel-efficient vehicle speed control is developed. This approach encompasses stochastic modeling of road grade and traffic speed, modeling of fuel consumption through the use of a neural network, and the application of stochastic dynamic programming to generate vehicle speed control policies that are optimized for the trade-off between fuel consumption and travel time. The fuel economy improvements with the proposed policies are quantified through simulations and vehicle experiments. It is shown that the policies lead to the emergence of time-varying vehicle speed patterns that are referred to as time-varying cruise. Through simulations and experiments it is confirmed that these time-varying vehicle speed profiles are more fuel-efficient than driving at a comparable constant speed. Motivated by these results, a simpler implementation strategy that is more appealing for practical implementation is also developed. This strategy relies on a finite state machine and state transition threshold optimization, and its benefits are quantified through model-based simulations and vehicle experiments. Several additional contributions are made to approaches for stochastic modeling of road grade and vehicle speed that include the use of Kullback-Liebler divergence and divergence rate and a stochastic jump-like model for the behavior of the road grade. In the second part of the dissertation, contributions to constrained control with applications to aircraft are described. Recoverable sets and integral safe sets of initial states of constrained closed-loop systems are introduced first and computational procedures of such sets based on linear discrete-time models are given. The use of linear discrete-time models is emphasized as they lead to fast computational procedures. Examples of these sets for aircraft longitudinal and lateral aircraft dynamics are reported, and it is shown that these sets can be larger in size compared to the more commonly used safe sets. An approach to constrained maneuver planning based on chaining recoverable sets or integral safe sets is described and illustrated with a simulation example. To facilitate the application of this maneuver planning approach in aircraft loss of control (LOC) situations when the model is only identified at the current trim condition but when these sets need to be predicted at other flight conditions, the dependence trends of the safe and recoverable sets on aircraft flight conditions are characterized. The scaling procedure to estimate subsets of safe and recoverable sets at one trim condition based on their knowledge at another trim condition is defined. Finally, two control schemes that exploit integral safe sets are proposed. The first scheme, referred to as the controller state governor (CSG), resets the controller state (typically an integrator) to enforce the constraints and enlarge the set of plant states that can be recovered without constraint violation. The second scheme, referred to as the controller state and reference governor (CSRG), combines the controller state governor with the reference governor control architecture and provides the capability of simultaneously modifying the reference command and the controller state to enforce the constraints. Theoretical results that characterize the response properties of both schemes are presented. Examples are reported that illustrate the operation of these schemes on aircraft flight dynamics models and gas turbine engine dynamic models.

Prediction of surface distress using neural networks

NASA Astrophysics Data System (ADS)

Hamdi, Hadiwardoyo, Sigit P.; Correia, A. Gomes; Pereira, Paulo; Cortez, Paulo

2017-06-01

Road infrastructures contribute to a healthy economy throughout a sustainable distribution of goods and services. A road network requires appropriately programmed maintenance treatments in order to keep roads assets in good condition, providing maximum safety for road users under a cost-effective approach. Surface Distress is the key element to identify road condition and may be generated by many different factors. In this paper, a new approach is aimed to predict Surface Distress Index (SDI) values following a data-driven approach. Later this model will be accordingly applied by using data obtained from the Integrated Road Management System (IRMS) database. Artificial Neural Networks (ANNs) are used to predict SDI index using input variables related to the surface of distress, i.e., crack area and width, pothole, rutting, patching and depression. The achieved results show that ANN is able to predict SDI with high correlation factor (R2 = 0.996%). Moreover, a sensitivity analysis was applied to the ANN model, revealing the influence of the most relevant input parameters for SDI prediction, namely rutting (59.8%), crack width (29.9%) and crack area (5.0%), patching (3.0%), pothole (1.7%) and depression (0.3%).

Constraining CO2 tower measurements in an inhomogeneous area with anthropogenic emissions using a combination of car-mounted instrument campaigns, aircraft profiles, transport modeling and neural networks

NASA Astrophysics Data System (ADS)

Schmidt, A.; Rella, C.; Conley, S. A.; Goeckede, M.; Law, B. E.

2013-12-01

The NOAA CO2 observation network in Oregon has been enhanced by 3 new towers in 2012. The tallest tower in the network (270 m), located in Silverton in the Willamette Valley is affected by anthropogenic emissions from Oregon's busiest traffic routes and urban centers. In summer 2012, we conducted a measurement campaign using a car-mounted PICARRO CRDS CO2/CO analyzer. Over 3 days, the instrument was driven over 1000 miles throughout the northwestern portion of Oregon measuring the CO/ CO2 ratios on main highways, back roads in forests, agricultural sites, and Oregon's biggest urban centers. By geospatial analyses we obtained ratios of CO/ CO2 over distinct land cover types divided into 10 classes represented in the study area. Using the coupled WRF-STILT transport model we calculated the footprints of nearby CO/ CO2 observation towers for the corresponding days of mobile road measurements. Spatiotemporally assigned source areas in combination with the land use classification were then used to calculate specific ratios of CO (anthropogenic origins) and CO2 to separate the anthropogenic portion of CO2 from the mixing ratio time series measured at the tower in Silverton. The WRF modeled boundary layer heights used in out study showed some differences compared to the boundary layer heights derived from profile data of wind, temperature, and humidity measured with an airplane in August, September, and November 2012, repeatedly over 5 tower locations. A Bayesian Regularized Artificial Neural Network (BRANN) was used to correct the boundary layer height calculated with WRF with a temporal resolution of 20 minutes and a horizontal resolution of 4 km. For that purpose the BRANN was trained using height profile data from the flight campaigns and spatiotemporally corresponding meteorological data from WRF. Our analyses provide information needed to run inverse modeling of CO2 exchange in an area that is affected by sources that cannot easily be considered by biospheric models. The results help to account for regional anthropogenic influences using long-term tower data and supporting short-term campaigns. Figure 1: The footprint areas of 2 NOAA observation towers (72 m inlet at Walton and 212 m inlet at Silverton) during the 3-day campaign with the car-mounted PICARRO CRDS on July 10 (a), July 11 (b), and July 12 (c) 2012 together with the main roads and urban centers. The orange lines show the routes driven during those days.

3D road marking reconstruction from street-level calibrated stereo pairs

NASA Astrophysics Data System (ADS)

Soheilian, Bahman; Paparoditis, Nicolas; Boldo, Didier

This paper presents an automatic approach to road marking reconstruction using stereo pairs acquired by a mobile mapping system in a dense urban area. Two types of road markings were studied: zebra crossings (crosswalks) and dashed lines. These two types of road markings consist of strips having known shape and size. These geometric specifications are used to constrain the recognition of strips. In both cases (i.e. zebra crossings and dashed lines), the reconstruction method consists of three main steps. The first step extracts edge points from the left and right images of a stereo pair and computes 3D linked edges using a matching process. The second step comprises a filtering process that uses the known geometric specifications of road marking objects. The goal is to preserve linked edges that can plausibly belong to road markings and to filter others out. The final step uses the remaining linked edges to fit a theoretical model to the data. The method developed has been used for processing a large number of images. Road markings are successfully and precisely reconstructed in dense urban areas under real traffic conditions.

Automated road marking recognition system

NASA Astrophysics Data System (ADS)

Ziyatdinov, R. R.; Shigabiev, R. R.; Talipov, D. N.

2017-09-01

Development of the automated road marking recognition systems in existing and future vehicles control systems is an urgent task. One way to implement such systems is the use of neural networks. To test the possibility of using neural network software has been developed with the use of a single-layer perceptron. The resulting system based on neural network has successfully coped with the task both when driving in the daytime and at night.

Roads influence movement and home ranges of a fragmentation-sensitive carnivore, the bobcat, in an urban landscape

USGS Publications Warehouse

Poessel, Sharon A; Boydston, Erin E.; Lyren, Lisa M.; Fisher, Robert N.; Burdett, Christopher L.; Alonso, Robert S.; Crooks, Kevin R.

2014-01-01

Roads in urbanized areas can impact carnivore populations by constraining their movements and increasing mortality. Bobcats (Lynx rufus) are felids capable of living in urban environments, but are sensitive to habitat fragmentation and, thus, useful indicators of landscape connectivity; in particular, bobcat habitat selection, movement, and mortality may be affected by roads. We analyzed movement patterns of 52 bobcats in southern California in three study sites and investigated: (1) how bobcats responded to two types of roads within their home ranges; (2) how they placed their home ranges with respect to roads within the study area; and (3) whether male and female bobcats differed in their behavioral responses to roads. Within home ranges, primary and secondary roads did not influence movements, but bobcats more frequently crossed secondary roads when road densities were higher within their home ranges, thus increasing mortality risk. However, road densities within each study site were several times higher than road densities within home ranges, suggesting bobcats selected against roaded areas in home-range placement. Male home ranges bordering roads were smaller than home ranges for other males, but male home ranges containing roads were larger than those without roads. Male bobcats also were more likely to cross roads than females, potentially reflecting larger male home range sizes. Our results suggest roads have important impacts on urban bobcats, with stronger effects on males than females, and continued efforts to mitigate the effects of roads on carnivores and other fragmentation-sensitive species would help promote connectivity conservation in urban systems.

A scenario planning approach for disasters on Swiss road network

NASA Astrophysics Data System (ADS)

Mendes, G. A.; Axhausen, K. W.; Andrade, J. S.; Herrmann, H. J.

2014-05-01

We study a vehicular traffic scenario on Swiss roads in an emergency situation, calculating how sequentially roads block due to excessive traffic load until global collapse (gridlock) occurs and in this way displays the fragilities of the system. We used a database from Bundesamt für Raumentwicklung which contains length and maximum allowed speed of all roads in Switzerland. The present work could be interesting for government agencies in planning and managing for emergency logistics for a country or a big city. The model used to generate the flux on the Swiss road network was proposed by Mendes et al. [Physica A 391, 362 (2012)]. It is based on the conservation of the number of vehicles and allows for an easy and fast way to follow the formation of traffic jams in large systems. We also analyze the difference between a nonlinear and a linear model and the distribution of fluxes on the Swiss road.

Road landslide information management and forecasting system base on GIS.

PubMed

Wang, Wei Dong; Du, Xiang Gang; Xie, Cui Ming

2009-09-01

Take account of the characters of road geological hazard and its supervision, it is very important to develop the Road Landslides Information Management and Forecasting System based on Geographic Information System (GIS). The paper presents the system objective, function, component modules and key techniques in the procedure of system development. The system, based on the spatial information and attribute information of road geological hazard, was developed and applied in Guizhou, a province of China where there are numerous and typical landslides. The manager of communication, using the system, can visually inquire all road landslides information based on regional road network or on the monitoring network of individual landslide. Furthermore, the system, integrated with mathematical prediction models and the GIS's strongpoint on spatial analyzing, can assess and predict landslide developing procedure according to the field monitoring data. Thus, it can efficiently assists the road construction or management units in making decision to control the landslides and to reduce human vulnerability.

The scaling structure of the global road network

PubMed Central

Giometto, Andrea; Shai, Saray; Bertuzzo, Enrico; Mucha, Peter J.; Rinaldo, Andrea

2017-01-01

Because of increasing global urbanization and its immediate consequences, including changes in patterns of food demand, circulation and land use, the next century will witness a major increase in the extent of paved roads built worldwide. To model the effects of this increase, it is crucial to understand whether possible self-organized patterns are inherent in the global road network structure. Here, we use the largest updated database comprising all major roads on the Earth, together with global urban and cropland inventories, to suggest that road length distributions within croplands are indistinguishable from urban ones, once rescaled to account for the difference in mean road length. Such similarity extends to road length distributions within urban or agricultural domains of a given area. We find two distinct regimes for the scaling of the mean road length with the associated area, holding in general at small and at large values of the latter. In suitably large urban and cropland domains, we find that mean and total road lengths increase linearly with their domain area, differently from earlier suggestions. Scaling regimes suggest that simple and universal mechanisms regulate urban and cropland road expansion at the global scale. As such, our findings bear implications for global road infrastructure growth based on land-use change and for planning policies sustaining urban expansions. PMID:29134071

The scaling structure of the global road network.

PubMed

Strano, Emanuele; Giometto, Andrea; Shai, Saray; Bertuzzo, Enrico; Mucha, Peter J; Rinaldo, Andrea

2017-10-01

Because of increasing global urbanization and its immediate consequences, including changes in patterns of food demand, circulation and land use, the next century will witness a major increase in the extent of paved roads built worldwide. To model the effects of this increase, it is crucial to understand whether possible self-organized patterns are inherent in the global road network structure. Here, we use the largest updated database comprising all major roads on the Earth, together with global urban and cropland inventories, to suggest that road length distributions within croplands are indistinguishable from urban ones, once rescaled to account for the difference in mean road length. Such similarity extends to road length distributions within urban or agricultural domains of a given area. We find two distinct regimes for the scaling of the mean road length with the associated area, holding in general at small and at large values of the latter. In suitably large urban and cropland domains, we find that mean and total road lengths increase linearly with their domain area, differently from earlier suggestions. Scaling regimes suggest that simple and universal mechanisms regulate urban and cropland road expansion at the global scale. As such, our findings bear implications for global road infrastructure growth based on land-use change and for planning policies sustaining urban expansions.

Reconciling certification and intact forest landscape conservation.

PubMed

Kleinschroth, Fritz; Garcia, Claude; Ghazoul, Jaboury

2018-05-29

In 2014, the Forest Stewardship Council (FSC) added a new criterion to its principles that requires protection of intact forest landscapes (IFLs). An IFL is an extensive area of forest that lacks roads and other signs of human activity as detected through remote sensing. In the Congo basin, our analysis of road networks in formally approved concessionary logging areas revealed greater loss of IFL in certified than in noncertified concessions. In areas of informal (i.e., nonregulated) extraction, road networks are known to be less detectable by remote sensing. Under the current definition of IFL, companies certified under FSC standards are likely to be penalized relative to the noncertified as well as the informal logging sector on account of their planned road networks, despite an otherwise better standard of forest management. This could ultimately undermine certification and its wider adoption, with implications for the future of sustainable forest management.

The Loss of Efficiency Caused by Agents’ Uncoordinated Routing in Transport Networks

PubMed Central

Wang, Junjie; Wang, Pu

2014-01-01

Large-scale daily commuting data were combined with detailed geographical information system (GIS) data to analyze the loss of transport efficiency caused by drivers’ uncoordinated routing in urban road networks. We used Price of Anarchy (POA) to quantify the loss of transport efficiency and found that both volume and distribution of human mobility demand determine the POA. In order to reduce POA, a small number of highways require considerable decreases in traffic, and their neighboring arterial roads need to attract more traffic. The magnitude of the adjustment in traffic flow can be estimated using the fundamental measure traffic flow only, which is widely available and easy to collect. Surprisingly, the most congested roads or the roads with largest traffic flow were not those requiring the most reduction of traffic. This study can offer guidance for the optimal control of urban traffic and facilitate improvements in the efficiency of transport networks. PMID:25349995

Forest roads, chronic turbidity, and salmon

Treesearch

L. M. Reid

1998-01-01

Certain impacts of forest roads on habitats used by anadromous salmonids are widely recognized and well-understood: road-related landslides increase sediment loads and modify channel morphology, and culverts restrict access to parts of the channel network. Other influences are less obvious, but may be even more pervasive. For example, road-related erosion significantly...

Improving Societal Resilience Through Enhanced Reconnection Speed of Damaged Networks

NASA Astrophysics Data System (ADS)

Vodák, Rostislav; Bíl, Michal

2017-04-01

Road networks rank among the foundations of civilization. They enable people, services and goods to be transported to arbitrary places at any time. Its functioning can be impacted by various events, not only by natural hazards and their combinations. This can lead to the concurrent interruption of a number of roads and even cut-off parts of the network from vital services. The impact of these events can be reduced by various measures, but cannot be fully eliminated. We are aware of the fact that extreme events which result in road network break up will occur regardless of the ongoing process of hazard reduction using, for example, the improvement of the structural robustness of roads. The next problem is that many of the events are unpredictable and thus the needed costs of the improvement can easily spiral out of control. We therefore focus on the speed of the recovery process which can be optimized. This means that the time during which the damaged network is reconnected again will be as short as possible. The result of the optimization procedure is a sequence of road links which represent the routes of the repair units. The optimization process is, however, highly nontrivial because of the large number of possible routes for repair units. This prevents anyone from finding an optimal solution. We consequently introduce an approach based on the Ant Colony Optimization algorithm which is able to suggest an almost optimal solution under various constraints which can be established by the administrator of the network. We will also demonstrate its results and variability with several case examples.

Road safety alerting system with radar and GPS cooperation in a VANET environment

NASA Astrophysics Data System (ADS)

Santamaria, Amilcare Francesco; Sottile, Cesare; De Rango, Floriano; Voznak, Miroslav

2014-05-01

New applications in wireless environments are increasing and keeping even more interests from the developer companies and researchers. In particular, in these last few years the government and institutional organization for road safety spent a lot of resources and money to promote Vehicular Ad-Hoc Network (VANET) technology, also car manufactures are giving a lot of contributions on this field as well. In our paper, we propose an innovative system to increase road safety, matching the requests of the market allowing a cooperation between on-board devices. The vehicles are equipped with On Board Unit (OBU) and On Board Radar Unit (OBRU), which can spread alerting messages around the network regarding warning and dangerous situations exploiting IEEE802.llp standard. Vehicles move along roads observing the environment, traffic and road conditions, and vehicles parameters as well. These information can be elaborated and shared between neighbors, Road Side Unit (RSU)s and, of course, with Internet, allowing inter-system communications exploiting an Road Traffic Manager (RTM). Radar systems task it the detection of the environment in order to increase the knowledge of current conditions of the roads, for example it is important to identify obstacles, road accidents, dangerous situations and so on. Once detected exploiting onboard devices, such as Global Position System (GPS) receiver it is possible to know the exact location of the caught event and after a data elaboration the information is spread along the network. Once the drivers are advised, they can make some precautionary actions such as reduction of traveling speed or modification of current road path. In this work the routing algorithms, which have the main goal to rapidly disseminate information, are also been investigated.

Communicating landslide risk by combining hazard and open infrastructure data in interactive visualizations

NASA Astrophysics Data System (ADS)

Tost, Jordi; Olen, Stephanie M.; Bookhagen, Bodo; Heidmann, Frank

2017-04-01

The DIGENTI project ("DIGitaler ENtscheiderTIsch für das Naturgefahrenmanagement auf Basis von Satellitendaten und Volunteered Geographic Information") has the goal of quantifying and communicating the threat of natural hazards in the Cesar and La Guajira departments of northeast Colombia. The end-goal of the project is to provide an interactive guide for policy and decision makers, and for disaster relief coordination. Over the last years, abundant research has been done in order to analyze risk and to provide relevant information that improves effectiveness in disaster management. The communication of natural hazards risk has traditionally been built upon the estimation of hazard maps. In the context of landslides, hazard maps are used to depict potential danger from landslides and visualize the possibility of future landsliding throughout a given area. Such hazard maps provide a static snapshot of the local estimated threat in a region. However, in mountainous regions, a sufficiently large landslide in remote mountainous areas may represent a potential threat to settlements located downstream of a landslide event. The research presented here proposes an approach to visualize and interactively explore landslide risk by combining static hazard maps, hydrologic networks, and OpenStreetMap data. We estimated the potential for hillslope instabilities scenarios in the region of interest by using the TanDEM-X World DEM to calculate a suite Factor of Safety (FOS) maps. The FOS estimates the ratio of total resisting and driving forces to hillslope mass movements. By combining the World DEM with other environmental data (e.g., the Harmonized World Soil Database), we were able to create a suite of high-resolution landslide potential maps for the region of interest. The suite of FOS maps are calculated based on user-selectable parameters (e.g, total mass sliding thickness) that are not well constrained by field observations. We additionally use the TanDEM-X World DEM to calculate the hydrologic network for our study area. This allows not only to delineate the stream network, but also to calculate the area upstream of settlements located near rivers or streams that may be impacted by distal landsliding. By integrating the potential landslide hazard in the upstream area, we create a more robust threat estimate for vulnerable settlements. Disaster relief is not only affected by the physical consequences of a hazardous event, but also by the area's accessibility and mobility capability for internal displacements. We therefore also estimate the threat along roads and to other infrastructure (e.g. bridges). Decisions based on the area's road network have to be constantly taken, for instance, to send rescue teams or to coordinate humanitarian logistics. With our approach, we are able to identify critical spots along roads with high likelihood of getting damaged. Furthermore, given a particular potential landslide location and the calculation of its downstream hydrologic network, it is possible to estimate which settlements, roads or bridges may be at risk. This approach could be integrated into flooding early warning systems and into the disaster management response phase to foresee dangers and losses and plan evacuations on time.

Potential interaction between transport and stream networks over the lowland rivers in Eastern India.

PubMed

Roy, Suvendu; Sahu, Abhay Sankar

2017-07-15

Extension of transport networks supports good accessibility and associated with the development of a region. However, transport lines have fragmented the regional landscape and disturbed the natural interplay between rivers and their floodplains. Spatial analysis using multiple buffers provides information about the potential interaction between road and stream networks and their impact on channel morphology of a small watershed in the Lower Gangetic Plain. Present study is tried to understand the lateral and longitudinal disconnection in headwater stream by rural roads with the integration of geoinformatics and field survey. Significant (p < 0.001) growth of total road length and number of road-stream crossing in the last five decades (1970s-2010s) contribute to making longitudinal and lateral disconnection in the fluvial system of Kunur River Basin. Channel geometry from ten road-stream crossings shows significant (p = 0.01) differences between upstream and downstream of crossing structure and created problems like downstream scouring, increased drop height at outlet, formation of stable bars, severe bank erosion, and make barriers for river biota. The hydro-geomorphic processes are also adversely affected due to lateral disconnection and input of fine to coarse sediments from the river side growth of unpaved road (1922%). Limited streamside development, delineation of stream corridor, regular monitoring and engineering efficiency for the construction of road and road-stream crossing might be effective in managing river geomorphology and riverine landscape. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modeling and simulating networks of interdependent protein interactions.

PubMed

Stöcker, Bianca K; Köster, Johannes; Zamir, Eli; Rahmann, Sven

2018-05-21

Protein interactions are fundamental building blocks of biochemical reaction systems underlying cellular functions. The complexity and functionality of these systems emerge not only from the protein interactions themselves but also from the dependencies between these interactions, as generated by allosteric effects or mutual exclusion due to steric hindrance. Therefore, formal models for integrating and utilizing information about interaction dependencies are of high interest. Here, we describe an approach for endowing protein networks with interaction dependencies using propositional logic, thereby obtaining constrained protein interaction networks ("constrained networks"). The construction of these networks is based on public interaction databases as well as text-mined information about interaction dependencies. We present an efficient data structure and algorithm to simulate protein complex formation in constrained networks. The efficiency of the model allows fast simulation and facilitates the analysis of many proteins in large networks. In addition, this approach enables the simulation of perturbation effects, such as knockout of single or multiple proteins and changes of protein concentrations. We illustrate how our model can be used to analyze a constrained human adhesome protein network, which is responsible for the formation of diverse and dynamic cell-matrix adhesion sites. By comparing protein complex formation under known interaction dependencies versus without dependencies, we investigate how these dependencies shape the resulting repertoire of protein complexes. Furthermore, our model enables investigating how the interplay of network topology with interaction dependencies influences the propagation of perturbation effects across a large biochemical system. Our simulation software CPINSim (for Constrained Protein Interaction Network Simulator) is available under the MIT license at http://github.com/BiancaStoecker/cpinsim and as a Bioconda package (https://bioconda.github.io).

Hierarchical graph-based segmentation for extracting road networks from high-resolution satellite images

NASA Astrophysics Data System (ADS)

Alshehhi, Rasha; Marpu, Prashanth Reddy

2017-04-01

Extraction of road networks in urban areas from remotely sensed imagery plays an important role in many urban applications (e.g. road navigation, geometric correction of urban remote sensing images, updating geographic information systems, etc.). It is normally difficult to accurately differentiate road from its background due to the complex geometry of the buildings and the acquisition geometry of the sensor. In this paper, we present a new method for extracting roads from high-resolution imagery based on hierarchical graph-based image segmentation. The proposed method consists of: 1. Extracting features (e.g., using Gabor and morphological filtering) to enhance the contrast between road and non-road pixels, 2. Graph-based segmentation consisting of (i) Constructing a graph representation of the image based on initial segmentation and (ii) Hierarchical merging and splitting of image segments based on color and shape features, and 3. Post-processing to remove irregularities in the extracted road segments. Experiments are conducted on three challenging datasets of high-resolution images to demonstrate the proposed method and compare with other similar approaches. The results demonstrate the validity and superior performance of the proposed method for road extraction in urban areas.

Degree-constrained multicast routing for multimedia communications

NASA Astrophysics Data System (ADS)

Wang, Yanlin; Sun, Yugeng; Li, Guidan

2005-02-01

Multicast services have been increasingly used by many multimedia applications. As one of the key techniques to support multimedia applications, the rational and effective multicast routing algorithms are very important to networks performance. When switch nodes in networks have different multicast capability, multicast routing problem is modeled as the degree-constrained Steiner problem. We presented two heuristic algorithms, named BMSTA and BSPTA, for the degree-constrained case in multimedia communications. Both algorithms are used to generate degree-constrained multicast trees with bandwidth and end to end delay bound. Simulations over random networks were carried out to compare the performance of the two proposed algorithms. Experimental results show that the proposed algorithms have advantages in traffic load balancing, which can avoid link blocking and enhance networks performance efficiently. BMSTA has better ability in finding unsaturated links and (or) unsaturated nodes to generate multicast trees than BSPTA. The performance of BMSTA is affected by the variation of degree constraints.

Optimal policies for aggregate recycling from decommissioned forest roads.

PubMed

Thompson, Matthew; Sessions, John

2008-08-01

To mitigate the adverse environmental impact of forest roads, especially degradation of endangered salmonid habitat, many public and private land managers in the western United States are actively decommissioning roads where practical and affordable. Road decommissioning is associated with reduced long-term environmental impact. When decommissioning a road, it may be possible to recover some aggregate (crushed rock) from the road surface. Aggregate is used on many low volume forest roads to reduce wheel stresses transferred to the subgrade, reduce erosion, reduce maintenance costs, and improve driver comfort. Previous studies have demonstrated the potential for aggregate to be recovered and used elsewhere on the road network, at a reduced cost compared to purchasing aggregate from a quarry. This article investigates the potential for aggregate recycling to provide an economic incentive to decommission additional roads by reducing transport distance and aggregate procurement costs for other actively used roads. Decommissioning additional roads may, in turn, result in improved aquatic habitat. We present real-world examples of aggregate recycling and discuss the advantages of doing so. Further, we present mixed integer formulations to determine optimal levels of aggregate recycling under economic and environmental objectives. Tested on an example road network, incorporation of aggregate recycling demonstrates substantial cost-savings relative to a baseline scenario without recycling, increasing the likelihood of road decommissioning and reduced habitat degradation. We find that aggregate recycling can result in up to 24% in cost savings (economic objective) and up to 890% in additional length of roads decommissioned (environmental objective).

Road screening and distribution route multi-objective robust optimization for hazardous materials based on neural network and genetic algorithm.

PubMed

Ma, Changxi; Hao, Wei; Pan, Fuquan; Xiang, Wang

2018-01-01

Route optimization of hazardous materials transportation is one of the basic steps in ensuring the safety of hazardous materials transportation. The optimization scheme may be a security risk if road screening is not completed before the distribution route is optimized. For road screening issues of hazardous materials transportation, a road screening algorithm of hazardous materials transportation is built based on genetic algorithm and Levenberg-Marquardt neural network (GA-LM-NN) by analyzing 15 attributes data of each road network section. A multi-objective robust optimization model with adjustable robustness is constructed for the hazardous materials transportation problem of single distribution center to minimize transportation risk and time. A multi-objective genetic algorithm is designed to solve the problem according to the characteristics of the model. The algorithm uses an improved strategy to complete the selection operation, applies partial matching cross shift and single ortho swap methods to complete the crossover and mutation operation, and employs an exclusive method to construct Pareto optimal solutions. Studies show that the sets of hazardous materials transportation road can be found quickly through the proposed road screening algorithm based on GA-LM-NN, whereas the distribution route Pareto solutions with different levels of robustness can be found rapidly through the proposed multi-objective robust optimization model and algorithm.

Urban networks among Chinese cities along "the Belt and Road": A case of web search activity in cyberspace.

PubMed

Zhang, Lu; Du, Hongru; Zhao, Yannan; Wu, Rongwei; Zhang, Xiaolei

2017-01-01

"The Belt and Road" initiative has been expected to facilitate interactions among numerous city centers. This initiative would generate a number of centers, both economic and political, which would facilitate greater interaction. To explore how information flows are merged and the specific opportunities that may be offered, Chinese cities along "the Belt and Road" are selected for a case study. Furthermore, urban networks in cyberspace have been characterized by their infrastructure orientation, which implies that there is a relative dearth of studies focusing on the investigation of urban hierarchies by capturing information flows between Chinese cities along "the Belt and Road". This paper employs Baidu, the main web search engine in China, to examine urban hierarchies. The results show that urban networks become more balanced, shifting from a polycentric to a homogenized pattern. Furthermore, cities in networks tend to have both a hierarchical system and a spatial concentration primarily in regions such as Beijing-Tianjin-Hebei, Yangtze River Delta and the Pearl River Delta region. Urban hierarchy based on web search activity does not follow the existing hierarchical system based on geospatial and economic development in all cases. Moreover, urban networks, under the framework of "the Belt and Road", show several significant corridors and more opportunities for more cities, particularly western cities. Furthermore, factors that may influence web search activity are explored. The results show that web search activity is significantly influenced by the economic gap, geographical proximity and administrative rank of the city.

Physarum solver: A biologically inspired method of road-network navigation

NASA Astrophysics Data System (ADS)

Tero, Atsushi; Kobayashi, Ryo; Nakagaki, Toshiyuki

2006-04-01

We have proposed a mathematical model for the adaptive dynamics of the transport network in an amoeba-like organism, the true slime mold Physarum polycephalum. The model is based on physiological observations of this species, but can also be used for path-finding in the complicated networks of mazes and road maps. In this paper, we describe the physiological basis and the formulation of the model, as well as the results of simulations of some complicated networks. The path-finding method used by Physarum is a good example of cellular computation.

Roads Data Conflation Using Update High Resolution Satellite Images

NASA Astrophysics Data System (ADS)

Abdollahi, A.; Riyahi Bakhtiari, H. R.

2017-11-01

Urbanization, industrialization and modernization are rapidly growing in developing countries. New industrial cities, with all the problems brought on by rapid population growth, need infrastructure to support the growth. This has led to the expansion and development of the road network. A great deal of road network data has made by using traditional methods in the past years. Over time, a large amount of descriptive information has assigned to these map data, but their geometric accuracy and precision is not appropriate to today's need. In this regard, the improvement of the geometric accuracy of road network data by preserving the descriptive data attributed to them and updating of the existing geo databases is necessary. Due to the size and extent of the country, updating the road network maps using traditional methods is time consuming and costly. Conversely, using remote sensing technology and geographic information systems can reduce costs, save time and increase accuracy and speed. With increasing the availability of high resolution satellite imagery and geospatial datasets there is an urgent need to combine geographic information from overlapping sources to retain accurate data, minimize redundancy, and reconcile data conflicts. In this research, an innovative method for a vector-to-imagery conflation by integrating several image-based and vector-based algorithms presented. The SVM method for image classification and Level Set method used to extract the road the different types of road intersections extracted from imagery using morphological operators. For matching the extracted points and to find the corresponding points, matching function which uses the nearest neighborhood method was applied. Finally, after identifying the matching points rubber-sheeting method used to align two datasets. Two residual and RMSE criteria used to evaluate accuracy. The results demonstrated excellent performance. The average root-mean-square error decreased from 11.8 to 4.1 m.

The impact of roads on the timber rattlesnake (Crotalus horridus) in eastern Texas

Treesearch

D. Craig Rudolph; Shirley J. Burgdorf; Richard N. Conner; James G. Dickson

1998-01-01

Roads and associated vehicular traffic have the potential to significantly impact vertebrate populations. In eastern Texas we compared the densities of paved and unpaved roads within 2 and 4 km radii of timber rattlesnake (Crotalus horridus) ocations and of random points. Road networks were significantly more dense at random points than at snake...

Low-dimensional recurrent neural network-based Kalman filter for speech enhancement.

PubMed

Xia, Youshen; Wang, Jun

2015-07-01

This paper proposes a new recurrent neural network-based Kalman filter for speech enhancement, based on a noise-constrained least squares estimate. The parameters of speech signal modeled as autoregressive process are first estimated by using the proposed recurrent neural network and the speech signal is then recovered from Kalman filtering. The proposed recurrent neural network is globally asymptomatically stable to the noise-constrained estimate. Because the noise-constrained estimate has a robust performance against non-Gaussian noise, the proposed recurrent neural network-based speech enhancement algorithm can minimize the estimation error of Kalman filter parameters in non-Gaussian noise. Furthermore, having a low-dimensional model feature, the proposed neural network-based speech enhancement algorithm has a much faster speed than two existing recurrent neural networks-based speech enhancement algorithms. Simulation results show that the proposed recurrent neural network-based speech enhancement algorithm can produce a good performance with fast computation and noise reduction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Contraction fracture: From 90° to 120° crack intersections

NASA Astrophysics Data System (ADS)

Lazarus, V.; Gauthier, G.; Pauchard, L.

2009-12-01

Giant's Causeway, Port Arthur tessellated pavement, Bimini Road, Mars polygons (whose presence indicated past occurrence of water), fracture networks in permafrost, septarias are some more or less known examples of self-organized crack patterns that have intrigued people through out history. Even now, they are sometimes attributed to legendary figures : Giant's, Atlantis mythical citizens. These pavements are in fact formed by constrained shrinking of the media due, for instance, to cooling or drying leading to fracture. The crack networks form mostly 90° or 120° angles. Here, we report experiments allowing to control the transition between 90° and 120°. We show that the transition is governed by the linear elastic fracture mechanics energy minimization principle, hence by two parameters: the cell size and the Griffith's length (minimum crack length beyond which the bulk energy is not sufficient to allow its propagation). This was achieved by measuring the Griffith's length directly on the same type of experiments by changing the cell geometry. Example of 90 degree and 120 crack intersections. Top-left : Giant's Causeway hexagonal tessellated pavement, Ireland (courtesy A. Davaille). Top-right: Port Arthur rectangular tessellated pavement, Tasmania (courtesy Wayne Bentley). Bottom : septarias (courtesy A. Rifki and M. Toussaint)

Do unpaved, low-traffic roads affect bird communities?

NASA Astrophysics Data System (ADS)

Mammides, Christos; Kounnamas, Constantinos; Goodale, Eben; Kadis, Costas

2016-02-01

Unpaved, low traffic roads are often assumed to have minimal effects on biodiversity. To explore this assertion, we sampled the bird communities in fifteen randomly selected sites in Pafos Forest, Cyprus and used multiple regression to quantify the effects of such roads on the total species richness. Moreover, we classified birds according to their migratory status and their global population trends, and tested each category separately. Besides the total length of unpaved roads, we also tested: a. the site's habitat diversity, b. the coefficient of variation in habitat (patch) size, c. the distance to the nearest agricultural field, and d. the human population size of the nearest village. We measured our variables at six different distances from the bird point-count locations. We found a strong negative relationship between the total bird richness and the total length of unpaved roads. The human population size of the nearest village also had a negative effect. Habitat diversity was positively related to species richness. When the categories were tested, we found that the passage migrants were influenced more by the road network while resident breeders were influenced by habitat diversity. Species with increasing and stable populations were only marginally affected by the variables tested, but the effect of road networks on species with decreasing populations was large. We conclude that unpaved and sporadically used roads can have detrimental effects on the bird communities, especially on vulnerable species. We propose that actions are taken to limit the extent of road networks within protected areas, especially in sites designated for their rich avifauna, such as Pafos Forest, where several of the affected species are species of European and global importance.

Social and spatial processes associated with childhood diarrheal disease in Matlab, Bangladesh.

PubMed

Perez-Heydrich, Carolina; Furgurson, Jill M; Giebultowicz, Sophia; Winston, Jennifer J; Yunus, Mohammad; Streatfield, Peter Kim; Emch, Michael

2013-01-01

We develop novel methods for conceptualizing geographic space and social networks to evaluate their respective and combined contributions to childhood diarrheal incidence. After defining maternal networks according to direct familial linkages between females, and road networks using satellite imagery of the study area, we use a spatial econometrics model to evaluate the significance of correlation terms relating childhood diarrheal incidence to the incidence observed within respective networks. Disease was significantly clustered within road networks across time, but only inconsistently correlated within maternal networks. These methods could be widely applied to systems in which both social and spatial processes jointly influence health outcomes. Copyright © 2012 Elsevier Ltd. All rights reserved.

The role of roadsides in plant invasions: a demographic approach.

PubMed

Christen, Douglas; Matlack, Glenn

2006-04-01

Non-native plant species are common along roadsides, but presence does not necessarily indicate spread along the road axis. Roadsides may serve merely as habitat for a species spreading independently of roads. The potential conduit function of roads depends on the habitat specificity of the spreading species, its dispersal range relative to the spacing of roads in the landscape, and the relative importance of long- and short-range dispersal. We describe a demographic model of the road x species interaction and suggest methods of assessing conduit function in the field based on the model results. A species limited to roadside habitat will be constrained to spread along the road axis unless its long-range dispersal is sufficient to carry it across the intervening unfavorable area to another road. It will propagate along a road corridor at a rate determined by the scale of short-range dispersal. Effective management of an invasion requires distinguishing between the habitat and conduit functions, a distinction difficult to make with only snapshot data. Invasions can be reconstructed by several methods, but none is totally satisfactory. We suggest comparing stem distributions on transects parallel and perpendicular to the road axis, and beside the road, and away from it, with an idealized Gaussian curve. Such comparisons would allow discrimination between pattern determined by habitat suitability and pattern reflecting random and facilitated dispersal.

Mapping the optimal forest road network based on the multicriteria evaluation technique: the case study of Mediterranean Island of Thassos in Greece.

PubMed

Tampekis, Stergios; Sakellariou, Stavros; Samara, Fani; Sfougaris, Athanassios; Jaeger, Dirk; Christopoulou, Olga

2015-11-01

The sustainable management of forest resources can only be achieved through a well-organized road network designed with the optimal spatial planning and the minimum environmental impacts. This paper describes the spatial layout mapping for the optimal forest road network and the environmental impacts evaluation that are caused to the natural environment based on the multicriteria evaluation (MCE) technique at the Mediterranean island of Thassos in Greece. Data analysis and its presentation are achieved through a spatial decision support system using the MCE method with the contribution of geographic information systems (GIS). With the use of the MCE technique, we evaluated the human impact intensity to the forest ecosystem as well as the ecosystem's absorption from the impacts that are caused from the forest roads' construction. For the human impact intensity evaluation, the criteria that were used are as follows: the forest's protection percentage, the forest road density, the applied skidding means (with either the use of tractors or the cable logging systems in timber skidding), the timber skidding direction, the visitors' number and truck load, the distance between forest roads and streams, the distance between forest roads and the forest boundaries, and the probability that the forest roads are located on sights with unstable soils. In addition, for the ecosystem's absorption evaluation, we used forestry, topographical, and social criteria. The recommended MCE technique which is described in this study provides a powerful, useful, and easy-to-use implement in order to combine the sustainable utilization of natural resources and the environmental protection in Mediterranean ecosystems.

Characterizing information propagation through inter-vehicle communication on a simple network of two parallel roads

DOT National Transportation Integrated Search

2010-10-01

In this report, we study information propagation via inter-vehicle communication along two parallel : roads. By identifying an inherent Bernoulli process, we are able to derive the mean and variance of : propagation distance. A road separation distan...

Effects of off-road recreation on mule deer and elk.

Treesearch

Michael J. Wisdom; Alan A. Ager; Haiganoush K. Preisler; Norman J. Cimon; Bruce K. Johnson

2004-01-01

Off-road recreation is increasing rapidly in the United States, especially on public land (Havlick 2002, U.S. Department of Agriculture Forest Service 2004). An expansive network of roads provides easy access to much public land, which facilitates off-road uses in the form of all-terrain vehicles (ATVs), horses, mountain bikes and foot traffic. No research, however,...

Public road infrastructure inventory in degraded global navigation satellite system signal environments

NASA Astrophysics Data System (ADS)

Sokolova, N.; Morrison, A.; Haakonsen, T. A.

2015-04-01

Recent advancement of land-based mobile mapping enables rapid and cost-effective collection of highquality road related spatial information. Mobile Mapping Systems (MMS) can provide spatial information with subdecimeter accuracy in nominal operation environments. However, performance in challenging environments such as tunnels is not well characterized. The Norwegian Public Roads Administration (NPRA) manages the country's public road network and its infrastructure, a large segment of which is represented by road tunnels (there are about 1 000 road tunnels in Norway with a combined length of 800 km). In order to adopt mobile mapping technology for streamlining road network and infrastructure management and maintenance tasks, it is important to ensure that the technology is mature enough to meet existing requirements for object positioning accuracy in all types of environments, and provide homogeneous accuracy over the mapping perimeter. This paper presents results of a testing campaign performed within a project funded by the NPRA as a part of SMarter road traffic with Intelligent Transport Systems (ITS) (SMITS) program. The testing campaign objective was performance evaluation of high end commercial MMSs for inventory of public areas, focusing on Global Navigation Satellite System (GNSS) signal degraded environments.

Drawing road networks with focus regions.

PubMed

Haunert, Jan-Henrik; Sering, Leon

2011-12-01

Mobile users of maps typically need detailed information about their surroundings plus some context information about remote places. In order to avoid that the map partly gets too dense, cartographers have designed mapping functions that enlarge a user-defined focus region--such functions are sometimes called fish-eye projections. The extra map space occupied by the enlarged focus region is compensated by distorting other parts of the map. We argue that, in a map showing a network of roads relevant to the user, distortion should preferably take place in those areas where the network is sparse. Therefore, we do not apply a predefined mapping function. Instead, we consider the road network as a graph whose edges are the road segments. We compute a new spatial mapping with a graph-based optimization approach, minimizing the square sum of distortions at edges. Our optimization method is based on a convex quadratic program (CQP); CQPs can be solved in polynomial time. Important requirements on the output map are expressed as linear inequalities. In particular, we show how to forbid edge crossings. We have implemented our method in a prototype tool. For instances of different sizes, our method generated output maps that were far less distorted than those generated with a predefined fish-eye projection. Future work is needed to automate the selection of roads relevant to the user. Furthermore, we aim at fast heuristics for application in real-time systems. © 2011 IEEE

Visualization of Traffic Accidents

NASA Technical Reports Server (NTRS)

Wang, Jie; Shen, Yuzhong; Khattak, Asad

2010-01-01

Traffic accidents have tremendous impact on society. Annually approximately 6.4 million vehicle accidents are reported by police in the US and nearly half of them result in catastrophic injuries. Visualizations of traffic accidents using geographic information systems (GIS) greatly facilitate handling and analysis of traffic accidents in many aspects. Environmental Systems Research Institute (ESRI), Inc. is the world leader in GIS research and development. ArcGIS, a software package developed by ESRI, has the capabilities to display events associated with a road network, such as accident locations, and pavement quality. But when event locations related to a road network are processed, the existing algorithm used by ArcGIS does not utilize all the information related to the routes of the road network and produces erroneous visualization results of event locations. This software bug causes serious problems for applications in which accurate location information is critical for emergency responses, such as traffic accidents. This paper aims to address this problem and proposes an improved method that utilizes all relevant information of traffic accidents, namely, route number, direction, and mile post, and extracts correct event locations for accurate traffic accident visualization and analysis. The proposed method generates a new shape file for traffic accidents and displays them on top of the existing road network in ArcGIS. Visualization of traffic accidents along Hampton Roads Bridge Tunnel is included to demonstrate the effectiveness of the proposed method.

Exponential Arithmetic Based Self-Healing Group Key Distribution Scheme with Backward Secrecy under the Resource-Constrained Wireless Networks

PubMed Central

Guo, Hua; Zheng, Yandong; Zhang, Xiyong; Li, Zhoujun

2016-01-01

In resource-constrained wireless networks, resources such as storage space and communication bandwidth are limited. To guarantee secure communication in resource-constrained wireless networks, group keys should be distributed to users. The self-healing group key distribution (SGKD) scheme is a promising cryptographic tool, which can be used to distribute and update the group key for the secure group communication over unreliable wireless networks. Among all known SGKD schemes, exponential arithmetic based SGKD (E-SGKD) schemes reduce the storage overhead to constant, thus is suitable for the the resource-constrained wireless networks. In this paper, we provide a new mechanism to achieve E-SGKD schemes with backward secrecy. We first propose a basic E-SGKD scheme based on a known polynomial-based SGKD, where it has optimal storage overhead while having no backward secrecy. To obtain the backward secrecy and reduce the communication overhead, we introduce a novel approach for message broadcasting and self-healing. Compared with other E-SGKD schemes, our new E-SGKD scheme has the optimal storage overhead, high communication efficiency and satisfactory security. The simulation results in Zigbee-based networks show that the proposed scheme is suitable for the resource-restrained wireless networks. Finally, we show the application of our proposed scheme. PMID:27136550

Hydrogeomorphic connectivity on roads crossing in rural headwaters and its effect on stream dynamics.

PubMed

Thomaz, Edivaldo L; Peretto, Gustavo T

2016-04-15

Unpaved roads are ubiquitous features that have been transforming the landscape through human history. Unpaved roads affect the water and sediment pathways through a catchment and impacts the aquatic ecosystem. In this study, we describe the effect of unpaved road on the hydrogeomorphic connectivity at the rural headwater scale. Measurement was based on the stream crossing approach, i.e., road superimposing the drainage system. We installed a Parshall flume coupled with single-stage suspended sediment sampler at each stream crossing. In addition, we displayed our monitoring scheme with an upscaling perspective from second-order to third-order stream. We concluded that the road-stream coupling dramatically changed the stream dynamic. The increase of discharge caused by roads at the headwater was 50% larger compared to unaffected streams. Additionally, suspended sediment concentration enhancement at stream crossings ranged from to 413% at second-order streams to 145% at third-order streams. The landform characteristics associated with the road network produced an important hydrogeomorphic disruption in the landscape. As a result, the sediment filter function of the riparian zone was reduced dramatically. Therefore, we recommend that projects for aquatic system restoration or conservation in rural landscape consider the role of the road network on stream dynamics. Copyright © 2016 Elsevier B.V. All rights reserved.

Resilience and efficiency in transportation networks

PubMed Central

Ganin, Alexander A.; Kitsak, Maksim; Marchese, Dayton; Keisler, Jeffrey M.; Seager, Thomas; Linkov, Igor

2017-01-01

Urban transportation systems are vulnerable to congestion, accidents, weather, special events, and other costly delays. Whereas typical policy responses prioritize reduction of delays under normal conditions to improve the efficiency of urban road systems, analytic support for investments that improve resilience (defined as system recovery from additional disruptions) is still scarce. In this effort, we represent paved roads as a transportation network by mapping intersections to nodes and road segments between the intersections to links. We built road networks for 40 of the urban areas defined by the U.S. Census Bureau. We developed and calibrated a model to evaluate traffic delays using link loads. The loads may be regarded as traffic-based centrality measures, estimating the number of individuals using corresponding road segments. Efficiency was estimated as the average annual delay per peak-period auto commuter, and modeled results were found to be close to observed data, with the notable exception of New York City. Resilience was estimated as the change in efficiency resulting from roadway disruptions and was found to vary between cities, with increased delays due to a 5% random loss of road linkages ranging from 9.5% in Los Angeles to 56.0% in San Francisco. The results demonstrate that many urban road systems that operate inefficiently under normal conditions are nevertheless resilient to disruption, whereas some more efficient cities are more fragile. The implication is that resilience, not just efficiency, should be considered explicitly in roadway project selection and justify investment opportunities related to disaster and other disruptions. PMID:29291243

Finite-time convergent recurrent neural network with a hard-limiting activation function for constrained optimization with piecewise-linear objective functions.

PubMed

Liu, Qingshan; Wang, Jun

2011-04-01

This paper presents a one-layer recurrent neural network for solving a class of constrained nonsmooth optimization problems with piecewise-linear objective functions. The proposed neural network is guaranteed to be globally convergent in finite time to the optimal solutions under a mild condition on a derived lower bound of a single gain parameter in the model. The number of neurons in the neural network is the same as the number of decision variables of the optimization problem. Compared with existing neural networks for optimization, the proposed neural network has a couple of salient features such as finite-time convergence and a low model complexity. Specific models for two important special cases, namely, linear programming and nonsmooth optimization, are also presented. In addition, applications to the shortest path problem and constrained least absolute deviation problem are discussed with simulation results to demonstrate the effectiveness and characteristics of the proposed neural network.

Evaluating medical convenience in ethnic minority areas of Southwest China via road network vulnerability: a case study for Dehong autonomous prefecture.

PubMed

Wei, Xiaoyan; Liu, Xuejun; Cheng, Liang; Sun, Lele; Pan, Yingying; Zong, Wenwen

2017-11-28

Southwest China is home to more than 30 ethnic minority groups. Since most of these populations reside in mountainous areas, convenient access to medical services is an important metric of how well their livelihoods are being protected. This paper proposes a medical convenience index (MCI) and computation model for mountain residents, taking into account various conditions including topography, geology, and climate. Data on road networks were used for comprehensive evaluation from three perspectives: vulnerability, complexity, and accessibility. The model is innovative for considering road network vulnerability in mountainous areas, and proposing a method of evaluating road network vulnerability by measuring the impacts of debris flows based on only links. The model was used to compute and rank the respective MCIs for settlements of each ethnic population in the Dehong Dai and Jingpo Autonomous Prefecture of Yunnan Province, in 2009 and 2015. Data on the settlements over the two periods were also used to analyze the spatial differentiation of medical convenience levels within the study area. The medical convenience levels of many settlements improved significantly. 80 settlements were greatly improved, while another 103 showed slight improvement.Areas with obvious improvement were distributed in clusters, and mainly located in the southwestern part of Yingjiang County, northern Longchuan County, eastern Lianghe County, and the region where Lianghe and Longchuan counties and Mang City intersect. Development of the road network was found to be a major contributor to improvements in MCI for mountain residents over the six-year period.

Implementation of a national near-road NO2 monitoring network--conference

EPA Science Inventory

In recent years, a large number of health studies have identified increased risks of adverse health effects for populations spending significant time near major roads. These studies indicate that populations living, working or going to school near major roads may be subjected to ...

New Kent County and Hanover County Road Orders, 1706-1743 : transcribed from the vestry book of St. Paul's Parish.

DOT National Transportation Integrated Search

2004-01-01

The road history projects undertaken by the Virginia Transportation Research Council establish the feasibility of studies of early road networks and their use in the environmental review process. These projects, by gathering and publishing the early ...

Flow assignment model for quantitative analysis of diverting bulk freight from road to railway

PubMed Central

Liu, Chang; Wang, Jiaxi; Xiao, Jie; Liu, Siqi; Wu, Jianping; Li, Jian

2017-01-01

Since railway transport possesses the advantage of high volume and low carbon emissions, diverting some freight from road to railway will help reduce the negative environmental impacts associated with transport. This paper develops a flow assignment model for quantitative analysis of diverting truck freight to railway. First, a general network which considers road transportation, railway transportation, handling and transferring is established according to all the steps in the whole transportation process. Then general functions which embody the factors which the shippers will pay attention to when choosing mode and path are formulated. The general functions contain the congestion cost on road, the capacity constraints of railways and freight stations. Based on the general network and general cost function, a user equilibrium flow assignment model is developed to simulate the flow distribution on the general network under the condition that all shippers choose transportation mode and path independently. Since the model is nonlinear and challenging, we adopt a method that uses tangent lines to constitute envelope curve to linearize it. Finally, a numerical example is presented to test the model and show the method of making quantitative analysis of bulk freight modal shift between road and railway. PMID:28771536

Prediction of road traffic death rate using neural networks optimised by genetic algorithm.

PubMed

Jafari, Seyed Ali; Jahandideh, Sepideh; Jahandideh, Mina; Asadabadi, Ebrahim Barzegari

2015-01-01

Road traffic injuries (RTIs) are realised as a main cause of public health problems at global, regional and national levels. Therefore, prediction of road traffic death rate will be helpful in its management. Based on this fact, we used an artificial neural network model optimised through Genetic algorithm to predict mortality. In this study, a five-fold cross-validation procedure on a data set containing total of 178 countries was used to verify the performance of models. The best-fit model was selected according to the root mean square errors (RMSE). Genetic algorithm, as a powerful model which has not been introduced in prediction of mortality to this extent in previous studies, showed high performance. The lowest RMSE obtained was 0.0808. Such satisfactory results could be attributed to the use of Genetic algorithm as a powerful optimiser which selects the best input feature set to be fed into the neural networks. Seven factors have been known as the most effective factors on the road traffic mortality rate by high accuracy. The gained results displayed that our model is very promising and may play a useful role in developing a better method for assessing the influence of road traffic mortality risk factors.

A three-stage heuristic for harvest scheduling with access road network development

Treesearch

Mark M. Clark; Russell D. Meller; Timothy P. McDonald

2000-01-01

In this article we present a new model for the scheduling of forest harvesting with spatial and temporal constraints. Our approach is unique in that we incorporate access road network development into the harvest scheduling selection process. Due to the difficulty of solving the problem optimally, we develop a heuristic that consists of a solution construction stage...

Taking Their Show on the Road: Becky Hebert & Siobhan Champ-Blackwell--National Network of Libraries of Medicine

ERIC Educational Resources Information Center

Library Journal, 2005

2005-01-01

They're two very different women with the same mission: outreach to medically underserved populations. Both work for the National Network of Libraries of Medicine. Becky Hebert (left) covers the Southeast/Atlantic region, and Siobhan Champ-Blackwell, the mid-continental region. They spend much of their lives on the road, exhibiting at minority…

Modeling, analysis, and simulation of the co-development of road networks and vehicle ownership

NASA Astrophysics Data System (ADS)

Xu, Mingtao; Ye, Zhirui; Shan, Xiaofeng

2016-01-01

A two-dimensional logistic model is proposed to describe the co-development of road networks and vehicle ownership. The endogenous interaction between road networks and vehicle ownership and how natural market forces and policies transformed into their co-development are considered jointly in this model. If the involved parameters satisfy a certain condition, the proposed model can arrive at a steady equilibrium level and the final development scale will be within the maximum capacity of an urban traffic system; otherwise, the co-development process will be unstable and even manifest chaotic behavior. Then sensitivity tests are developed to determine the proper values for a series of parameters in this model. Finally, a case study, using Beijing City as an example, is conducted to explore the applicability of the proposed model to the real condition. Results demonstrate that the proposed model can effectively simulate the co-development of road network and vehicle ownership for Beijing City. Furthermore, we can obtain that their development process will arrive at a stable equilibrium level in the years 2040 and 2045 respectively, and the equilibrium values are within the maximum capacity.

How Travel Demand Affects Detection of Non-Recurrent Traffic Congestion on Urban Road Networks

NASA Astrophysics Data System (ADS)

Anbaroglu, B.; Heydecker, B.; Cheng, T.

2016-06-01

Occurrence of non-recurrent traffic congestion hinders the economic activity of a city, as travellers could miss appointments or be late for work or important meetings. Similarly, for shippers, unexpected delays may disrupt just-in-time delivery and manufacturing processes, which could lose them payment. Consequently, research on non-recurrent congestion detection on urban road networks has recently gained attention. By analysing large amounts of traffic data collected on a daily basis, traffic operation centres can improve their methods to detect non-recurrent congestion rapidly and then revise their existing plans to mitigate its effects. Space-time clusters of high link journey time estimates correspond to non-recurrent congestion events. Existing research, however, has not considered the effect of travel demand on the effectiveness of non-recurrent congestion detection methods. Therefore, this paper investigates how travel demand affects detection of non-recurrent traffic congestion detection on urban road networks. Travel demand has been classified into three categories as low, normal and high. The experiments are carried out on London's urban road network, and the results demonstrate the necessity to adjust the relative importance of the component evaluation criteria depending on the travel demand level.

Costs of performance based maintenance for local roads: Case study Albania

NASA Astrophysics Data System (ADS)

Jokanović, Igor; Grujić, Bojana; Zeljić, Dragana; Grujić, Žarko; Svilar, Mila

2017-12-01

The provision and maintenance of road infrastructure is a major global business, consequently it is essential that road maintenance services are provided in the most cost effective manner. Without regular maintenance, roads can rapidly fall into disrepair, preventing realization of the longer term impacts of road improvements on development, such as increased agricultural production and growth in school enrollment, which is of particular importance for a network of local (access) roads. Inadequate local roads maintenance in Albania is proposed to be solved by implementing performance based maintenance approach for which the costing exercise is presented within the paper.

Responses of Roadside Soil Cation Pools to Vehicular Emission Deposition in Southern California

NASA Astrophysics Data System (ADS)

Rossi, R.; Bain, D. J.; Jenerette, D.; Clarke, L. W.; Wilson, K.

2013-12-01

Roadside soils are heavily loaded with NO3- due to vehicular emissions. This deposition likely acidifies these soils, potentially mobilizing cationic species from soil exchange sites. Acidification driven mobilization is well documented in forest soils, but poorly understood in roadside soils. Metal concentrations in park and garden soils collected from Southern California were examined across gradients of soil chemistry, road network density, climate, and geology to examine cation mobilization effects. In our samples, soil pH is not clearly related to distance from the roadside or underlying geology. However, the depletion of several elements (Al, K) is clearly observed in near-road environments. These depletion trends occur despite contrary trends, including increased soil surface areas and soil organic matter in near-road environments. Additionally, inputs from the weathering of road building materials appear to affect soil chemistry. For example, soil Ca patterns remain relatively consistent relative to roads, suggesting Ca bearing weathering products replenish soil Ca pools in near-road areas. Simple mixing models constructed using elemental ratios are consistent with road material Ca source contributions. Observed near-road patterns in soil chemistry likely influence local ecological function, shifting plant communities and soil functions. Clear understanding of these shifts is essential to the effective use of green infrastructure and other strategies utilized to control road-sourced nutrients. This analytical framework can be applied globally as road networks continue to expand and affect larger ecosystems.

MQ-MAC: A Multi-Constrained QoS-Aware Duty Cycle MAC for Heterogeneous Traffic in Wireless Sensor Networks

PubMed Central

Monowar, Muhammad Mostafa; Rahman, Md. Obaidur; Hong, Choong Seon; Lee, Sungwon

2010-01-01

Energy conservation is one of the striking research issues now-a-days for power constrained wireless sensor networks (WSNs) and hence, several duty-cycle based MAC protocols have been devised for WSNs in the last few years. However, assimilation of diverse applications with different QoS requirements (i.e., delay and reliability) within the same network also necessitates in devising a generic duty-cycle based MAC protocol that can achieve both the delay and reliability guarantee, termed as multi-constrained QoS, while preserving the energy efficiency. To address this, in this paper, we propose a Multi-constrained QoS-aware duty-cycle MAC for heterogeneous traffic in WSNs (MQ-MAC). MQ-MAC classifies the traffic based on their multi-constrained QoS demands. Through extensive simulation using ns-2 we evaluate the performance of MQ-MAC. MQ-MAC provides the desired delay and reliability guarantee according to the nature of the traffic classes as well as achieves energy efficiency. PMID:22163439

Thermodynamic Constraints Improve Metabolic Networks.

PubMed

Krumholz, Elias W; Libourel, Igor G L

2017-08-08

In pursuit of establishing a realistic metabolic phenotypic space, the reversibility of reactions is thermodynamically constrained in modern metabolic networks. The reversibility constraints follow from heuristic thermodynamic poise approximations that take anticipated cellular metabolite concentration ranges into account. Because constraints reduce the feasible space, draft metabolic network reconstructions may need more extensive reconciliation, and a larger number of genes may become essential. Notwithstanding ubiquitous application, the effect of reversibility constraints on the predictive capabilities of metabolic networks has not been investigated in detail. Instead, work has focused on the implementation and validation of the thermodynamic poise calculation itself. With the advance of fast linear programming-based network reconciliation, the effects of reversibility constraints on network reconciliation and gene essentiality predictions have become feasible and are the subject of this study. Networks with thermodynamically informed reversibility constraints outperformed gene essentiality predictions compared to networks that were constrained with randomly shuffled constraints. Unconstrained networks predicted gene essentiality as accurately as thermodynamically constrained networks, but predicted substantially fewer essential genes. Networks that were reconciled with sequence similarity data and strongly enforced reversibility constraints outperformed all other networks. We conclude that metabolic network analysis confirmed the validity of the thermodynamic constraints, and that thermodynamic poise information is actionable during network reconciliation. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Introduction to special issue on hydrologic and geomorphic effects of forest roads

Treesearch

Charles H. Luce; Beverley C. Wemple

2001-01-01

Roads have been a part of human landscapes for more than 40 centuries. During the 20th century, technological advances have increased our ability to construct new roads at unprecedented rates and into steeper terrain. In the last half of that century, an extensive network of roads has been constructed in forests and other wildlands to facilitate use and management of...

Vulnerability Analysis and Evaluation of Urban Road System in Tianjin

NASA Astrophysics Data System (ADS)

Liu, Y. Q.; Wu, X.

In recent years, with the development of economy, the road construction of our country has entered into a period of rapid growth. The road transportation network has been expanding and the risk of disasters is increasing. In this paper we study the vulnerability of urban road system in Tianjin. After analyzed many risk factors of the urban road system security, including road construction, road traffic and the natural environment, we proposed an evaluation index of vulnerability of urban road system and established the corresponding evaluation index system. Based on the results of analysis and comprehensive evaluation, appropriate improvement measures and suggestions which may reduce the vulnerability of the road system and improve the safety and reliability of the road system are proposed.

Performance Analysis of Constrained Loosely Coupled GPS/INS Integration Solutions

PubMed Central

Falco, Gianluca; Einicke, Garry A.; Malos, John T.; Dovis, Fabio

2012-01-01

The paper investigates approaches for loosely coupled GPS/INS integration. Error performance is calculated using a reference trajectory. A performance improvement can be obtained by exploiting additional map information (for example, a road boundary). A constrained solution has been developed and its performance compared with an unconstrained one. The case of GPS outages is also investigated showing how a Kalman filter that operates on the last received GPS position and velocity measurements provides a performance benefit. Results are obtained by means of simulation studies and real data. PMID:23202241

Safety analysis of urban arterials at the meso level.

PubMed

Li, Jia; Wang, Xuesong

2017-11-01

Urban arterials form the main structure of street networks. They typically have multiple lanes, high traffic volume, and high crash frequency. Classical crash prediction models investigate the relationship between arterial characteristics and traffic safety by treating road segments and intersections as isolated units. This micro-level analysis does not work when examining urban arterial crashes because signal spacing is typically short for urban arterials, and there are interactions between intersections and road segments that classical models do not accommodate. Signal spacing also has safety effects on both intersections and road segments that classical models cannot fully account for because they allocate crashes separately to intersections and road segments. In addition, classical models do not consider the impact on arterial safety of the immediately surrounding street network pattern. This study proposes a new modeling methodology that will offer an integrated treatment of intersections and road segments by combining signalized intersections and their adjacent road segments into a single unit based on road geometric design characteristics and operational conditions. These are called meso-level units because they offer an analytical approach between micro and macro. The safety effects of signal spacing and street network pattern were estimated for this study based on 118 meso-level units obtained from 21 urban arterials in Shanghai, and were examined using CAR (conditional auto regressive) models that corrected for spatial correlation among the units within individual arterials. Results showed shorter arterial signal spacing was associated with higher total and PDO (property damage only) crashes, while arterials with a greater number of parallel roads were associated with lower total, PDO, and injury crashes. The findings from this study can be used in the traffic safety planning, design, and management of urban arterials. Copyright © 2017 Elsevier Ltd. All rights reserved.

Network Structure as a Modulator of Disturbance Impacts in Streams

NASA Astrophysics Data System (ADS)

Warner, S.; Tullos, D. D.

2017-12-01

This study examines how river network structure affects the propagation of geomorphic and anthropogenic disturbances through streams. Geomorphic processes such as debris flows can alter channel morphology and modify habitat for aquatic biota. Anthropogenic disturbances such as road construction can interact with the geomorphology and hydrology of forested watersheds to change sediment and water inputs to streams. It was hypothesized that the network structure of streams within forested watersheds would influence the location and magnitude of the impacts of debris flows and road construction on sediment size and channel width. Longitudinal surveys were conducted every 50 meters for 11 kilometers of third-to-fifth order streams in the H.J. Andrews Experimental Forest in the Western Cascade Range of Oregon. Particle counts and channel geometry measurements were collected to characterize the geomorphic impacts of road crossings and debris flows as disturbances. Sediment size distributions and width measurements were plotted against the distance of survey locations through the network to identify variations in longitudinal trends of channel characteristics. Thresholds for the background variation in sediment size and channel width, based on the standard deviations of sample points, were developed for sampled stream segments characterized by location as well as geomorphic and land use history. Survey locations were classified as "disturbed" when they deviated beyond the reference thresholds in expected sediment sizes and channel widths, as well as flow-connected proximity to debris flows and road crossings. River network structure was quantified by drainage density and centrality of nodes upstream of survey locations. Drainage density and node centrality were compared between survey locations with similar channel characteristic classifications. Cluster analysis was used to assess the significance of survey location, proximity of survey location to debris flows and road crossings, drainage density and node centrality in predicting sediment size and channel width classifications for locations within the watershed. Results contribute to the understanding of susceptibility and responses of streams supporting critical habitat for aquatic species to debris flows and forest road disturbances.

Constrained Low-Interference Relay Node Deployment for Underwater Acoustic Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Li, Deying; Li, Zheng; Ma, Wenkai; Chen, Wenping

An Underwater Acoustic Wireless Sensor Network (UA-WSN) consists of many resource-constrained Underwater Sensor Nodes (USNs), which are deployed to perform collaborative monitoring tasks over a given region. One way to preserve network connectivity while guaranteing other network QoS is to deploy some Relay Nodes (RNs) in the networks, in which RNs' function is more powerful than USNs and their cost is more expensive. This paper addresses Constrained Low-interference Relay Node Deployment (C-LRND) problem for 3-D UA-WSNs in which the RNs are placed at a subset of candidate locations to ensure connectivity between the USNs, under both the number of RNs deployed and the value of total incremental interference constraints. We first prove that it is NP-hard, then present a general approximation algorithm framework and get two polynomial time O(1)-approximation algorithms.

Distributed Cognition on the road: Using EAST to explore future road transportation systems.

PubMed

Banks, Victoria A; Stanton, Neville A; Burnett, Gary; Hermawati, Setia

2018-04-01

Connected and Autonomous Vehicles (CAV) are set to revolutionise the way in which we use our transportation system. However, we do not fully understand how the integration of wireless and autonomous technology into the road transportation network affects overall network dynamism. This paper uses the theoretical principles underlying Distributed Cognition to explore the dependencies and interdependencies that exist between system agents located within the road environment, traffic management centres and other external agencies in both non-connected and connected transportation systems. This represents a significant step forward in modelling complex sociotechnical systems as it shows that the principles underlying Distributed Cognition can be applied to macro-level systems using the visual representations afforded by the Event Analysis of Systemic Teamwork (EAST) method. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Fault Tolerance Mechanism for On-Road Sensor Networks

PubMed Central

Feng, Lei; Guo, Shaoyong; Sun, Jialu; Yu, Peng; Li, Wenjing

2016-01-01

On-Road Sensor Networks (ORSNs) play an important role in capturing traffic flow data for predicting short-term traffic patterns, driving assistance and self-driving vehicles. However, this kind of network is prone to large-scale communication failure if a few sensors physically fail. In this paper, to ensure that the network works normally, an effective fault-tolerance mechanism for ORSNs which mainly consists of backup on-road sensor deployment, redundant cluster head deployment and an adaptive failure detection and recovery method is proposed. Firstly, based on the N − x principle and the sensors’ failure rate, this paper formulates the backup sensor deployment problem in the form of a two-objective optimization, which explains the trade-off between the cost and fault resumption. In consideration of improving the network resilience further, this paper introduces a redundant cluster head deployment model according to the coverage constraint. Then a common solving method combining integer-continuing and sequential quadratic programming is explored to determine the optimal location of these two deployment problems. Moreover, an Adaptive Detection and Resume (ADR) protocol is deigned to recover the system communication through route and cluster adjustment if there is a backup on-road sensor mismatch. The final experiments show that our proposed mechanism can achieve an average 90% recovery rate and reduce the average number of failed sensors at most by 35.7%. PMID:27918483

A network model to help land managers predict and prevent spread of invasive plants from roads to river systems in Alaska

Treesearch

Matthew J. Macander; Tricia L. Wurtz

2007-01-01

Alaska has relatively few invasive plants, and most of them are found only along the state's limited road system. Melilotus alba, or sweetclover, is one of the most widely distributed invasives in the state. Melilotus has recently moved from roadsides to the flood plains of at least three glacial rivers. We developed a network...

Pavement type and wear condition classification from tire cavity acoustic measurements with artificial neural networks.

PubMed

Masino, Johannes; Foitzik, Michael-Jan; Frey, Michael; Gauterin, Frank

2017-06-01

Tire road noise is the major contributor to traffic noise, which leads to general annoyance, speech interference, and sleep disturbances. Standardized methods to measure tire road noise are expensive, sophisticated to use, and they cannot be applied comprehensively. This paper presents a method to automatically classify different types of pavement and the wear condition to identify noisy road surfaces. The methods are based on spectra of time series data of the tire cavity sound, acquired under normal vehicle operation. The classifier, an artificial neural network, correctly predicts three pavement types, whereas there are few bidirectional mis-classifications for two pavements, which have similar physical characteristics. The performance measures of the classifier to predict a new or worn out condition are over 94.6%. One could create a digital map with the output of the presented method. On the basis of these digital maps, road segments with a strong impact on tire road noise could be automatically identified. Furthermore, the method can estimate the road macro-texture, which has an impact on the tire road friction especially on wet conditions. Overall, this digital map would have a great benefit for civil engineering departments, road infrastructure operators, and for advanced driver assistance systems.

Cluster categorization of urban roads to optimize their noise monitoring.

PubMed

Zambon, G; Benocci, R; Brambilla, G

2016-01-01

Road traffic in urban areas is recognized to be associated with urban mobility and public health, and it is often the main source of noise pollution. Lately, noise maps have been considered a powerful tool to estimate the population exposure to environmental noise, but they need to be validated by measured noise data. The project Dynamic Acoustic Mapping (DYNAMAP), co-funded in the framework of the LIFE 2013 program, is aimed to develop a statistically based method to optimize the choice and the number of monitoring sites and to automate the noise mapping update using the data retrieved from a low-cost monitoring network. Indeed, the first objective should improve the spatial sampling based on the legislative road classification, as this classification is mainly based on the geometrical characteristics of the road, rather than its noise emission. The present paper describes the statistical approach of the methodology under development and the results of its preliminary application to a limited sample of roads in the city of Milan. The resulting categorization of roads, based on clustering the 24-h hourly L Aeqh, looks promising to optimize the spatial sampling of noise monitoring toward a description of the noise pollution due to complex urban road networks more efficient than that based on the legislative road classification.

Spatial mismatch analysis among hotspots of alien plant species, road and railway networks in Germany and Austria

PubMed Central

Morelli, Federico

2017-01-01

Road and railway networks are pervasive elements of all environments, which have expanded intensively over the last century in all European countries. These transportation infrastructures have major impacts on the surrounding landscape, representing a threat to biodiversity. Roadsides and railways may function as corridors for dispersal of alien species in fragmented landscapes. However, only few studies have explored the spread of invasive species in relationship to transport network at large spatial scales. We performed a spatial mismatch analysis, based on a spatially explicit correlation test, to investigate whether alien plant species hotspots in Germany and Austria correspond to areas of high density of roads and railways. We tested this independently of the effects of dominant environments in each spatial unit, in order to focus just on the correlation between occurrence of alien species and density of linear transportation infrastructures. We found a significant spatial association between alien plant species hotspots distribution and roads and railways density in both countries. As expected, anthropogenic landscapes, such as urban areas, harbored more alien plant species, followed by water bodies. However, our findings suggested that the distribution of neobiota is strongest correlated to road/railways density than to land use composition. This study provides new evidence, from a transnational scale, that alien plants can use roadsides and rail networks as colonization corridors. Furthermore, our approach contributes to the understanding on alien plant species distribution at large spatial scale by the combination with spatial modeling procedures. PMID:28829818

Forest Roadidentification and Extractionof Through Advanced Log Matching Techniques

NASA Astrophysics Data System (ADS)

Zhang, W.; Hu, B.; Quist, L.

2017-10-01

A novel algorithm for forest road identification and extraction was developed. The algorithm utilized Laplacian of Gaussian (LoG) filter and slope calculation on high resolution multispectral imagery and LiDAR data respectively to extract both primary road and secondary road segments in the forest area. The proposed method used road shape feature to extract the road segments, which have been further processed as objects with orientation preserved. The road network was generated after post processing with tensor voting. The proposed method was tested on Hearst forest, located in central Ontario, Canada. Based on visual examination against manually digitized roads, the majority of roads from the test area have been identified and extracted from the process.

Road Accident Prevention with Instant Emergency Warning Message Dissemination in Vehicular Ad-Hoc Network.

PubMed

Gokulakrishnan, P; Ganeshkumar, P

2015-01-01

A Road Accident Prevention (RAP) scheme based on Vehicular Backbone Network (VBN) structure is proposed in this paper for Vehicular Ad-hoc Network (VANET). The RAP scheme attempts to prevent vehicles from highway road traffic accidents and thereby reduces death and injury rates. Once the possibility of an emergency situation (i.e. an accident) is predicted in advance, instantly RAP initiates a highway road traffic accident prevention scheme. The RAP scheme constitutes the following activities: (i) the Road Side Unit (RSU) constructs a Prediction Report (PR) based on the status of the vehicles and traffic in the highway roads, (ii) the RSU generates an Emergency Warning Message (EWM) based on an abnormal PR, (iii) the RSU forms a VBN structure and (iv) the RSU disseminates the EWM to the vehicles that holds the high Risk Factor (RF) and travels in High Risk Zone (HRZ). These vehicles might reside either within the RSU's coverage area or outside RSU's coverage area (reached using VBN structure). The RAP scheme improves the performance of EWM dissemination in terms of increase in notification and decrease in end-to-end delay. The RAP scheme also reduces infrastructure cost (number of RSUs) by formulating and deploying the VBN structure. The RAP scheme with VBN structure improves notification by 19 percent and end-to-end delay by 14.38 percent for a vehicle density of 160 vehicles. It is also proved from the simulation experiment that the performance of RAP scheme is promising in 4-lane highway roads.

Road Accident Prevention with Instant Emergency Warning Message Dissemination in Vehicular Ad-Hoc Network

PubMed Central

P, Gokulakrishnan; P, Ganeshkumar

2015-01-01

A Road Accident Prevention (RAP) scheme based on Vehicular Backbone Network (VBN) structure is proposed in this paper for Vehicular Ad-hoc Network (VANET). The RAP scheme attempts to prevent vehicles from highway road traffic accidents and thereby reduces death and injury rates. Once the possibility of an emergency situation (i.e. an accident) is predicted in advance, instantly RAP initiates a highway road traffic accident prevention scheme. The RAP scheme constitutes the following activities: (i) the Road Side Unit (RSU) constructs a Prediction Report (PR) based on the status of the vehicles and traffic in the highway roads, (ii) the RSU generates an Emergency Warning Message (EWM) based on an abnormal PR, (iii) the RSU forms a VBN structure and (iv) the RSU disseminates the EWM to the vehicles that holds the high Risk Factor (RF) and travels in High Risk Zone (HRZ). These vehicles might reside either within the RSU’s coverage area or outside RSU’s coverage area (reached using VBN structure). The RAP scheme improves the performance of EWM dissemination in terms of increase in notification and decrease in end-to-end delay. The RAP scheme also reduces infrastructure cost (number of RSUs) by formulating and deploying the VBN structure. The RAP scheme with VBN structure improves notification by 19 percent and end-to-end delay by 14.38 percent for a vehicle density of 160 vehicles. It is also proved from the simulation experiment that the performance of RAP scheme is promising in 4-lane highway roads. PMID:26636576

RUPOK - a web-map application for assessment of impacts of natural hazards on the transportation infrastructure

NASA Astrophysics Data System (ADS)

Bíl, Michal; Kubeček, Jan; Andrášik, Richard; Bílová, Martina; Sedoník, Jiří

2016-04-01

We present a web-map application (www.rupok.cz) designed for visualization of losses caused by natural hazards to the transportation infrastructure. This application is an output of a project in which we analyzed direct, indirect and network-wide impacts of major natural disasters which hit the CZ as of 1997. When natural disasters hit a road network the results are often a number of closed road sections. Certain roads may be, however, destroyed, whereas the majority of them are usually only closed and can be reopened after a short period of time. While the computation of direct losses (the cost of remedial works) is fairly simple, the evaluation of indirect and network-wide costs is much more difficult. We created a database of interrupted road and highway sections due to natural processes which includes data since 1997 and which is automatically updated. 6,828 records concerning interrupted communications located on 2,879 road sections are included in the database for the 1997 - 2014 time period. Flooding caused 37 % of the traffic interruptions, followed by fallen trees (22 %), landsliding (5 %) and rockfalls (2 %). The RUPOK webpage contains information on the probabilities of transportation section interruptions due to natural processes as well as the impacts of possible interruptions. The direct losses are depicted as monetary values per road section unit. The values are calculated on the basis of official tables including the prices for construction works. The indirect losses were calculated on the basis of the best alternative route expenses and as traffic intensities affected by a road section interruption.

4. What do we need to know about roads?

Treesearch

Leslie M. Reid; Robert R. Ziemer; Michael J. Furniss

1994-01-01

Abstract - Roads facilitate forest management activities, recreational access, and fire suppression. At the same time, they damage wildlife habitat, destroy the remoteness many seek in wildland recreation, produce sediment, alter aquatic ecosystems, and abet the dispersal of noxious weeds. Design of appropriate road networks is thus a controversial task for land...

Recognition Stage for a Speed Supervisor Based on Road Sign Detection

PubMed Central

Carrasco, Juan-Pablo; de la Escalera, Arturo; Armingol, José María

2012-01-01

Traffic accidents are still one of the main health problems in the World. A number of measures have been applied in order to reduce the number of injuries and fatalities in roads, i.e., implementation of Advanced Driver Assistance Systems (ADAS) based on image processing. In this paper, a real time speed supervisor based on road sign recognition that can work both in urban and non-urban environments is presented. The system is able to recognize 135 road signs, belonging to the danger, yield, prohibition obligation and indication types, and sends warning messages to the driver upon the combination of two pieces of information: the current speed of the car and the road sign symbol. The core of this paper is the comparison between the two main methods which have been traditionally used for detection and recognition of road signs: template matching (TM) and neural networks (NN). The advantages and disadvantages of the two approaches will be shown and commented. Additionally we will show how the use of well-known algorithms to avoid illumination issues reduces the amount of images needed to train a neural network.

The influence of the infrastructure characteristics in urban road accidents occurrence.

PubMed

Vieira Gomes, Sandra

2013-11-01

This paper summarizes the result of a study regarding the creation of tools that can be used in intervention methods in the planning and management of urban road networks in Portugal. The first tool relates the creation of a geocoded database of road accidents occurred in Lisbon between 2004 and 2007, which allowed the definition of digital maps, with the possibility of a wide range of consultations and crossing of information. The second tool concerns the development of models to estimate the frequency of accidents on urban networks, according to different desegregations: road element (intersections and segments); type of accident (accidents with and without pedestrians); and inclusion of explanatory variables related to the road environment. Several methods were used to assess the goodness of fit of the developed models, allowing more robust conclusions. This work aims to contribute to the scientific knowledge of accidents phenomenon in Portugal, with detailed and accurate information on the factors affecting its occurrence. This allows to explicitly include safety aspects in planning and road management tasks. Copyright © 2013 Elsevier Ltd. All rights reserved.

Morphological similarities between DBM and a microeconomic model of sprawl

NASA Astrophysics Data System (ADS)

Caruso, Geoffrey; Vuidel, Gilles; Cavailhès, Jean; Frankhauser, Pierre; Peeters, Dominique; Thomas, Isabelle

2011-03-01

We present a model that simulates the growth of a metropolitan area on a 2D lattice. The model is dynamic and based on microeconomics. Households show preferences for nearby open spaces and neighbourhood density. They compete on the land market. They travel along a road network to access the CBD. A planner ensures the connectedness and maintenance of the road network. The spatial pattern of houses, green spaces and road network self-organises, emerging from agents individualistic decisions. We perform several simulations and vary residential preferences. Our results show morphologies and transition phases that are similar to Dieletric Breakdown Models (DBM). Such similarities were observed earlier by other authors, but we show here that it can be deducted from the functioning of the land market and thus explicitly connected to urban economic theory.

Characterisation of traffic-generated particulate matter in Copenhagen

NASA Astrophysics Data System (ADS)

Wåhlin, Peter; Berkowicz, Ruwim; Palmgren, Finn

Fine and coarse fraction PM was simultaneously sampled with Dichotomous Stacked Filter Units at a road site and at an urban background site during both summer and winter periods. The collected mass was determined gravimetrically, and the contents of 26 elements were measured by Proton-Induced X-ray Emission (PIXE). NO x was monitored continuously at both sites. The road increments (road concentrations minus urban background concentrations) of PIXE elements, PM and NO x were analysed using the Constrained Physical Receptor Model (COPREM). Good agreement between the measured data and the model was achieved in both size fractions using four well-separated source profiles representing the emissions from exhaust, road/tyres, brakes and road salt. The analysis showed that the particles created by brake abrasion have aerodynamic diameters in the inhalable size range around 2.8 μm. This particle diameter is common mass median for a long list of heavy metals that are apportioned to the brakes source: Cr, Fe, Cu, Zn, Zr, Mo, Sn, Sb, Ba and Pb. Other significant contributions of Al, Si, K, Ca, Ti, Mn, Fe, Zn and Sr, mostly in the coarse particle fraction, are apportioned to the road/tyres source.

Dynamics of functional failures and recovery in complex road networks

NASA Astrophysics Data System (ADS)

Zhan, Xianyuan; Ukkusuri, Satish V.; Rao, P. Suresh C.

2017-11-01

We propose a new framework for modeling the evolution of functional failures and recoveries in complex networks, with traffic congestion on road networks as the case study. Differently from conventional approaches, we transform the evolution of functional states into an equivalent dynamic structural process: dual-vertex splitting and coalescing embedded within the original network structure. The proposed model successfully explains traffic congestion and recovery patterns at the city scale based on high-resolution data from two megacities. Numerical analysis shows that certain network structural attributes can amplify or suppress cascading functional failures. Our approach represents a new general framework to model functional failures and recoveries in flow-based networks and allows understanding of the interplay between structure and function for flow-induced failure propagation and recovery.

Assessing impacts of roads: application of a standard assessment protocol

USGS Publications Warehouse

Duniway, Michael C.; Herrick, Jeffrey E.

2013-01-01

Adaptive management of road networks depends on timely data that accurately reflect the impacts those systems are having on ecosystem processes and associated services. In the absence of reliable data, land managers are left with little more than observations and perceptions to support management decisions of road-associated disturbances. Roads can negatively impact the soil, hydrologic, plant, and animal processes on which virtually all ecosystem services depend. The Interpreting Indicators of Rangeland Health (IIRH) protocol is a qualitative method that has been demonstrated to be effective in characterizing impacts of roads. The goal of this study were to develop, describe, and test an approach for using IIRH to systematically evaluate road impacts across large, diverse arid and semiarid landscapes. We developed a stratified random sampling approach to plot selection based on ecological potential, road inventory data, and image interpretation of road impacts. The test application on a semiarid landscape in southern New Mexico, United States, demonstrates that the approach developed is sensitive to road impacts across a broad range of ecological sites but that not all the types of stratification were useful. Ecological site and road inventory strata accounted for significant variability in the functioning of ecological processes but stratification based on apparent impact did not. Analysis of the repeatability of IIRH applied to road plots indicates that the method is repeatable but consensus evaluations based on multiple observers should be used to minimize risk of bias. Landscape-scale analysis of impacts by roads of contrasting designs (maintained dirt or gravel roads vs. non- or infrequently maintained roads) suggests that future travel management plans for the study area should consider concentrating traffic on fewer roads that are well designed and maintained. Application of the approach by land managers will likely provide important insights into minimizing impacts of road networks on key ecosystem services.

Finding topological center of a geographic space via road network

NASA Astrophysics Data System (ADS)

Gao, Liang; Miao, Yanan; Qin, Yuhao; Zhao, Xiaomei; Gao, Zi-You

2015-02-01

Previous studies show that the center of a geographic space is of great importance in urban and regional studies, including study of population distribution, urban growth modeling, and scaling properties of urban systems, etc. But how to well define and how to efficiently extract the center of a geographic space are still largely unknown. Recently, Jiang et al. have presented a definition of topological center by their block detection (BD) algorithm. Despite the fact that they first introduced the definition and discovered the 'true center', in human minds, their algorithm left several redundancies in its traversal process. Here, we propose an alternative road-cycle detection (RCD) algorithm to find the topological center, which extracts the outmost road-cycle recursively. To foster the application of the topological center in related research fields, we first reproduce the BD algorithm in Python (pyBD), then implement the RCD algorithm in two ways: the ArcPy implementation (arcRCD) and the Python implementation (pyRCD). After the experiments on twenty-four typical road networks, we find that the results of our RCD algorithm are consistent with those of Jiang's BD algorithm. We also find that the RCD algorithm is at least seven times more efficient than the BD algorithm on all the ten typical road networks.

A remote sensing and geographic information system approach to sampling malaria vector habitats in Chiapas, Mexico

NASA Astrophysics Data System (ADS)

Beck, L.; Wood, B.; Whitney, S.; Rossi, R.; Spanner, M.; Rodriguez, M.; Rodriguez-Ramirez, A.; Salute, J.; Legters, L.; Roberts, D.; Rejmankova, E.; Washino, R.

1993-08-01

This paper describes a procedure whereby remote sensing and geographic information system (GIS) technologies are used in a sample design to study the habitat of Anopheles albimanus, one of the principle vectors of malaria in Central America. This procedure incorporates Landsat-derived land cover maps with digital elevation and road network data to identify a random selection of larval habitats accessible for field sampling. At the conclusion of the sampling season, the larval counts will be used to determine habitat productivity, and then integrated with information on human settlement to assess where people are at high risk of malaria. This aproach would be appropriate in areas where land cover information is lacking and problems of access constrain field sampling. The use of a GIS also permits other data (such as insecticide spraying data) to the incorporated in the sample design as they arise. This approach would also be pertinent for other tropical vector-borne diseases, particularly where human activities impact disease vector habitat.

Use of Energy Efficient Sensor Networks to Enhance Dynamic Data Gathering Systems: A Comparative Study between Bluetooth and ZigBee.

PubMed

Gheorghiu, Razvan Andrei; Iordache, Valentin

2018-06-03

As road traffic conditions worsen due to the constantly increasing number of cars, traffic management systems are struggling to provide a suitable environment, by gathering all the relevant information from the road network. However, in most cases these are obtained via traffic detectors placed near road junctions, thus providing no information on the conditions in between. A large-scale sensor network using detectors on the majority of vehicles would certainly be capable of providing useful data, but has two major impediments: the equipment installed on the vehicles should be cheap enough (assuming the willingness of private car owners to be a part of the network) and be capable of transferring the required amount of data in due time, as the vehicle passes by the road side unit that acts as interface with the traffic management system. These restrictions reduce the number of technologies that can be used. In this article a series of comprehensive tests have been performed to evaluate the Bluetooth and ZigBee protocols for this purpose from many points of view: handshake time, static and dynamic data transfer (in laboratory conditions and in real traffic conditions). An assessment of the environmental conditions (during tests and probable to be encountered in real conditions) was also provided.

Traffic safety effects of new speed limits in Sweden.

PubMed

Vadeby, Anna; Forsman, Åsa

2018-05-01

The effects of speed, both positive and negative, make speed a primary target for policy action. Driving speeds affect the risk of being involved in a crash and the injury severity as well as the noise and exhaust emissions. Starting 2008, the Swedish Transport Administration performed a review of the speed limits on the national rural road network. This review resulted in major changes of the speed limits on the rural road network. It was predominantly roads with a low traffic safety standard and unsatisfactory road sides that were selected for reduced speed limits, as well as roads with a good traffic safety record being selected for an increase in speed limits. During 2008 and 2009, speed limit changed on approximately 20,500km of roads, out of which approximately 2700km were assigned an increase, and 17,800km were assigned a reduction in speed limits. The aim of this study is predominantly to describe and analyse the longterm traffic safety effect of increased, as well as, reduced speed limits, but also to analyse the changes in actual driving speeds due to the changed speed limits. Traffic safety effects are investigated by means of a before and after study with control group and the effects on actual mean speeds are measured by a sampling survey in which speed was measured at randomly selected sites before and after the speed limit changes. Results show a reduction in fatalities on rural roads with reduced speed limit from 90 to 80km/h where the number of fatalities decreased by 14 per year, while no significant changes were seen for the seriously injured. On motorways with an increased speed limit to 120km/h, the number of seriously injured increased by about 15 per year, but no significant changes were seen for the number of deaths. The number of seriously injured increased on all types of motorways, but the worst development was seen for narrow motorways (21.5m wide). For 2+1 roads (a continuous three-lane cross-section with alternating passing lanes and the two directions of travel separated by a median barrier) with decreased speed limit from 110 to 100km/h, the seriously injured decreased by about 16 per year. As regards the change of mean speeds, a decrease in speed limit with 10km/h led to a decrease of mean speeds of around 2-3km/h and an increase of the speed limit with 10km/h resulted in an increase of mean speed by 3km/h. In conclusion, the results show that in total about 17 lives per year have been saved on the road network with changed speed limits. For comparison, 397 road users were killed in total during 2008. The number of seriously injured remain in principle unchanged. It should also be noted that the results are obtained for the road network which changed the speed limits during 2008 and 2009, and it is not certain that the results can be generalised to another road network. Copyright © 2017 Elsevier Ltd. All rights reserved.

Implementing evidence-based policy in a network setting: road safety policy in the Netherlands.

PubMed

Bax, Charlotte; de Jong, Martin; Koppenjan, Joop

2010-01-01

In the early 1990s, in order to improve road safety in The Netherlands, the Institute for Road Safety Research (SWOV) developed an evidence-based "Sustainable Safety" concept. Based on this concept, Dutch road safety policy, was seen as successful and as a best practice in Europe. In The Netherlands, the policy context has now changed from a sectoral policy setting towards a fragmented network in which safety is a facet of other transport-related policies. In this contribution, it is argued that the implementation strategy underlying Sustainable Safety should be aligned with the changed context. In order to explore the adjustments needed, two perspectives of policy implementation are discussed: (1) national evidence-based policies with sectoral implementation; and (2) decentralized negotiation on transport policy in which road safety is but one aspect. We argue that the latter approach matches the characteristics of the newly evolved policy context best, and conclude with recommendations for reformulating the implementation strategy.

Transforming GIS data into functional road models for large-scale traffic simulation.

PubMed

Wilkie, David; Sewall, Jason; Lin, Ming C

2012-06-01

There exists a vast amount of geographic information system (GIS) data that model road networks around the world as polylines with attributes. In this form, the data are insufficient for applications such as simulation and 3D visualization-tools which will grow in power and demand as sensor data become more pervasive and as governments try to optimize their existing physical infrastructure. In this paper, we propose an efficient method for enhancing a road map from a GIS database to create a geometrically and topologically consistent 3D model to be used in real-time traffic simulation, interactive visualization of virtual worlds, and autonomous vehicle navigation. The resulting representation provides important road features for traffic simulations, including ramps, highways, overpasses, legal merge zones, and intersections with arbitrary states, and it is independent of the simulation methodologies. We test the 3D models of road networks generated by our algorithm on real-time traffic simulation using both macroscopic and microscopic techniques.

CDOT thermal mapping report.

DOT National Transportation Integrated Search

2014-06-01

Thermal Mapping surveys were carried out on approximately 1000 miles of the Colorado Department : of Transportations (CDOTs) roads. The purpose of these surveys was to identify road surface : variations across the network to determine whether f...

CHAPTER 17: STORMWATER

EPA Science Inventory

The process of urbanization causes significant changes to the hydrologic regime of catchments through increased impervious areas (roads, roofs, etc) and alterations to the natural drainage network. Some examples of urbanization processes include: increasing surface area of road ...

Carbon emissions tax policy of urban road traffic and its application in Panjin, China

PubMed Central

Yang, Longhai; Fang, Lin

2018-01-01

How to effectively solve traffic congestion and transportation pollution in urban development is a main research emphasis for transportation management agencies. A carbon emissions tax can affect travelers’ generalized costs and will lead to changes in passenger demand, mode choice and traffic flow equilibrium in road networks, which are of significance in green travel and low-carbon transportation management. This paper first established a mesoscopic model to calculate the carbon emissions tax and determined the value of this charge in China, which was based on road traffic flow, vehicle speed, and carbon emissions. Referring to existing research results to calibrate the value of time, this paper modified the traveler’s generalized cost function, including the carbon emissions tax, fuel surcharge and travel time cost, which can be used in the travel impedance model with the consideration of the carbon emissions tax. Then, a method for analyzing urban road network traffic flow distribution was put forward, and a joint traffic distribution model was established, which considered the relationship between private cars and taxis. Finally, this paper took the city of Panjin as an example to analyze the road traffic carbon emissions tax’s impact. The results illustrated that the carbon emissions tax has a positive effect on road network flow equilibrium and carbon emission reduction. This paper will have good reference value and practical significance for the calculation and implementation of urban traffic carbon emissions taxes in China. PMID:29738580

Carbon emissions tax policy of urban road traffic and its application in Panjin, China.

PubMed

Yang, Longhai; Hu, Xiaowei; Fang, Lin

2018-01-01

How to effectively solve traffic congestion and transportation pollution in urban development is a main research emphasis for transportation management agencies. A carbon emissions tax can affect travelers' generalized costs and will lead to changes in passenger demand, mode choice and traffic flow equilibrium in road networks, which are of significance in green travel and low-carbon transportation management. This paper first established a mesoscopic model to calculate the carbon emissions tax and determined the value of this charge in China, which was based on road traffic flow, vehicle speed, and carbon emissions. Referring to existing research results to calibrate the value of time, this paper modified the traveler's generalized cost function, including the carbon emissions tax, fuel surcharge and travel time cost, which can be used in the travel impedance model with the consideration of the carbon emissions tax. Then, a method for analyzing urban road network traffic flow distribution was put forward, and a joint traffic distribution model was established, which considered the relationship between private cars and taxis. Finally, this paper took the city of Panjin as an example to analyze the road traffic carbon emissions tax's impact. The results illustrated that the carbon emissions tax has a positive effect on road network flow equilibrium and carbon emission reduction. This paper will have good reference value and practical significance for the calculation and implementation of urban traffic carbon emissions taxes in China.

Promising evidence of impact on road safety by changing at-risk behavior process at Union Pacific

DOT National Transportation Integrated Search

2008-06-01

Changing At-risk Behavior (CAB) is a safety process that is being conducted at Union Pacifics San Antonio Service Unit with the aim of improving locomotive cab safety related to constraining signals. CAB is an example of a risk reduction method th...

Scaling roads and wildlife: The Cinderella principle

USGS Publications Warehouse

Bissonette, J.A.

2002-01-01

It is clear that a reduction in both direct and indirect effects of roads and road networks must be the goal of management agencies. However, increased permeability of roaded landscapes can only be achieved by up-front planning and subsequent mitigative actions. The key is to understand that roads must be made permeable to the movement of animals. More profoundly, ecosystem services, i.e., clean water, clean air, uncontaminated soil, natural landscapes, recreation opportunities, abundant wildlife, and life sustaining ecological processes must not be seriously impacted. In other words, quality of life as measured by ecosystem services should be a major component of the planning process when roads are constructed or improved. Mitigative structures exist to increase permeability of roads. Wildlife overpasses and underpasses, often referred to as ecoducts or green bridges, with associated structures to enable larger animals to exit the road right of way, e.g., earthen escape ramps (BISSONETTE and HAMMER, 2001), various culvert designs for smaller animals including badger pipes and amphibian and reptile tunnels, and fish ladders are but a small sampling of the structures already in place around the world. What is needed is attention to the big picture. Landscapes need to be reconnected and made more permeable. Responsible agencies and organizations need to be aggressive about promoting mitigations and a conservation ethic into road planning. Only with a broad based effort between a concerned public, a database to work from, and a willingness of responsible agencies, will the now very large virtual footprint of roads and road networks be reduced to more closely approximate the physical footprint. By embracing the Cinderella Principle of making the virtual shoe fit more closely the actual physical footprint of roads, we will be able to achieve a closer connection with ecological harmony with its resultant effect of abundant wildlife.

Forest access roads: design, maintenance, and soil loss

Treesearch

Lloyd W. Swift

1988-01-01

The Regional Guide for,the South (United States Department of Agriculture 1984b) recognizes that roads and skid trails are the major sources of sediment from forestry-related activities. The overall environmental impact statement for Region 8 (United States Department of Agriculture 1984a) estimates an existing national forest road network of 56,300 km (3 1,000 miles)...

The importance of accurate road data for spatial applications in public health: customizing a road network

PubMed Central

Frizzelle, Brian G; Evenson, Kelly R; Rodriguez, Daniel A; Laraia, Barbara A

2009-01-01

Background Health researchers have increasingly adopted the use of geographic information systems (GIS) for analyzing environments in which people live and how those environments affect health. One aspect of this research that is often overlooked is the quality and detail of the road data and whether or not it is appropriate for the scale of analysis. Many readily available road datasets, both public domain and commercial, contain positional errors or generalizations that may not be compatible with highly accurate geospatial locations. This study examined the accuracy, completeness, and currency of four readily available public and commercial sources for road data (North Carolina Department of Transportation, StreetMap Pro, TIGER/Line 2000, TIGER/Line 2007) relative to a custom road dataset which we developed and used for comparison. Methods and Results A custom road network dataset was developed to examine associations between health behaviors and the environment among pregnant and postpartum women living in central North Carolina in the United States. Three analytical measures were developed to assess the comparative accuracy and utility of four publicly and commercially available road datasets and the custom dataset in relation to participants' residential locations over three time periods. The exclusion of road segments and positional errors in the four comparison road datasets resulted in between 5.9% and 64.4% of respondents lying farther than 15.24 meters from their nearest road, the distance of the threshold set by the project to facilitate spatial analysis. Agreement, using a Pearson's correlation coefficient, between the customized road dataset and the four comparison road datasets ranged from 0.01 to 0.82. Conclusion This study demonstrates the importance of examining available road datasets and assessing their completeness, accuracy, and currency for their particular study area. This paper serves as an example for assessing the feasibility of readily available commercial or public road datasets, and outlines the steps by which an improved custom dataset for a study area can be developed. PMID:19409088

Identifying network representation issues with the network trip.

DOT National Transportation Integrated Search

2012-04-23

The purpose of this study was to evaluate the effects of road-network representation on the application of the Network Robustness Index (NRI), using the Chittenden County Regional Transportation Model. The results are expected to improve the requirem...

Driver fatigue and road safety on Poland's national roads.

PubMed

Jamroz, Kazimierz; Smolarek, Leszek

2013-01-01

This paper presents an overview of factors causing driver fatigue as described in the literature. Next, a traffic crash database for 2003-2007 is used to identify the causes, circumstances and consequences of accidents caused by driver fatigue on Poland's national roads. The results of the study were used to build a model showing the relationship between the concentration of road accidents and casualties, and the time of day. Finally, the level of relative accident risk at night-time versus daytime is defined. A map shows the risk of death and severe injury on the network of Poland's national roads. The paper suggests to road authorities steps to reduce fatigue-related road accidents in Poland.

Modeling and query the uncertainty of network constrained moving objects based on RFID data

NASA Astrophysics Data System (ADS)

Han, Liang; Xie, Kunqing; Ma, Xiujun; Song, Guojie

2007-06-01

The management of network constrained moving objects is more and more practical, especially in intelligent transportation system. In the past, the location information of moving objects on network is collected by GPS, which cost high and has the problem of frequent update and privacy. The RFID (Radio Frequency IDentification) devices are used more and more widely to collect the location information. They are cheaper and have less update. And they interfere in the privacy less. They detect the id of the object and the time when moving object passed by the node of the network. They don't detect the objects' exact movement in side the edge, which lead to a problem of uncertainty. How to modeling and query the uncertainty of the network constrained moving objects based on RFID data becomes a research issue. In this paper, a model is proposed to describe the uncertainty of network constrained moving objects. A two level index is presented to provide efficient access to the network and the data of movement. The processing of imprecise time-slice query and spatio-temporal range query are studied in this paper. The processing includes four steps: spatial filter, spatial refinement, temporal filter and probability calculation. Finally, some experiments are done based on the simulated data. In the experiments the performance of the index is studied. The precision and recall of the result set are defined. And how the query arguments affect the precision and recall of the result set is also discussed.

Interior view, looking northeast in computer room OvertheHorizon Backscatter ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Interior view, looking northeast in computer room - Over-the-Horizon Backscatter Radar Network, Tulelake Radar Site Receive Sector Five Receiver Building, Unnamed Road West of Double Head Road, Tulelake, Siskiyou County, CA

Interior view, looking south in computer room OvertheHorizon Backscatter ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Interior view, looking south in computer room - Over-the-Horizon Backscatter Radar Network, Tulelake Radar Site Receive Sector Six Receiver Building, Unnamed Road West of Double Head Road, Tulelake, Siskiyou County, CA

Detail of antenna array, looking northnorthwest OvertheHorizon Backscatter Radar ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Detail of antenna array, looking north-northwest - Over-the-Horizon Backscatter Radar Network, Tulelake Radar Site Receive Sector Five Antenna Array, Unnamed Road West of Double Head Road, Tulelake, Siskiyou County, CA

General view of Antenna Array, looking west OvertheHorizon Backscatter ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

General view of Antenna Array, looking west - Over-the-Horizon Backscatter Radar Network, Tulelake Radar Site Receive Sector Six Antenna Array, Unnamed Road West of Double Head Road, Tulelake, Siskiyou County, CA

Detail of antenna tower structure, looking northnorthwest OvertheHorizon Backscatter ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Detail of antenna tower structure, looking north-northwest - Over-the-Horizon Backscatter Radar Network, Tulelake Radar Site Receive Sector Five Antenna Array, Unnamed Road West of Double Head Road, Tulelake, Siskiyou County, CA

Real-Time (Vision-Based) Road Sign Recognition Using an Artificial Neural Network.

PubMed

Islam, Kh Tohidul; Raj, Ram Gopal

2017-04-13

Road sign recognition is a driver support function that can be used to notify and warn the driver by showing the restrictions that may be effective on the current stretch of road. Examples for such regulations are 'traffic light ahead' or 'pedestrian crossing' indications. The present investigation targets the recognition of Malaysian road and traffic signs in real-time. Real-time video is taken by a digital camera from a moving vehicle and real world road signs are then extracted using vision-only information. The system is based on two stages, one performs the detection and another one is for recognition. In the first stage, a hybrid color segmentation algorithm has been developed and tested. In the second stage, an introduced robust custom feature extraction method is used for the first time in a road sign recognition approach. Finally, a multilayer artificial neural network (ANN) has been created to recognize and interpret various road signs. It is robust because it has been tested on both standard and non-standard road signs with significant recognition accuracy. This proposed system achieved an average of 99.90% accuracy with 99.90% of sensitivity, 99.90% of specificity, 99.90% of f-measure, and 0.001 of false positive rate (FPR) with 0.3 s computational time. This low FPR can increase the system stability and dependability in real-time applications.

Real-Time (Vision-Based) Road Sign Recognition Using an Artificial Neural Network

PubMed Central

Islam, Kh Tohidul; Raj, Ram Gopal

2017-01-01

Road sign recognition is a driver support function that can be used to notify and warn the driver by showing the restrictions that may be effective on the current stretch of road. Examples for such regulations are ‘traffic light ahead’ or ‘pedestrian crossing’ indications. The present investigation targets the recognition of Malaysian road and traffic signs in real-time. Real-time video is taken by a digital camera from a moving vehicle and real world road signs are then extracted using vision-only information. The system is based on two stages, one performs the detection and another one is for recognition. In the first stage, a hybrid color segmentation algorithm has been developed and tested. In the second stage, an introduced robust custom feature extraction method is used for the first time in a road sign recognition approach. Finally, a multilayer artificial neural network (ANN) has been created to recognize and interpret various road signs. It is robust because it has been tested on both standard and non-standard road signs with significant recognition accuracy. This proposed system achieved an average of 99.90% accuracy with 99.90% of sensitivity, 99.90% of specificity, 99.90% of f-measure, and 0.001 of false positive rate (FPR) with 0.3 s computational time. This low FPR can increase the system stability and dependability in real-time applications. PMID:28406471

A Wi-Fi based Electronic Road Sign for Enhancing the Awareness of Vehicle Driver

NASA Astrophysics Data System (ADS)

Bhawiyuga, A.; Sabriansyah, R. A.; Yahya, W.; E Putra, R.

2017-01-01

Reducing the road accident rate is one of the city goal in the area of transportation. One of the effort to reach that goal is done by deploying various signs across the road. However, the role of those road signs can be diminished once the vehicle drivers intentionally or unintentionally disobey the rule indicated on those signs. In order to increase the awareness of the driver, we can employ the vehicular network concept in which a vehicle can communicate with another vehicles or with the infrastructure installed along the road. For realizing that idea, we propose the implementation of communication equipped road sign system which consists of two components: Road Side Unit (RSU) module deployed at road sign and On Board Unit (OBU) module deployed at each vehicle. In our proposed scheme, both of the devices communicate each other through the widely-used Wi-Fi protocol (IEEE 802.11n) operating in ad-hoc mode. While a OBU equipped vehicle is moving towards the communication range of RSU, it will make an association to a predefined wireless ad-hoc network. Once it is associated, the OBU can receive message broadcast by the RSU. Upon reception, OBU display alert message indicating that the vehicle is approaching a road sign. From performance testing we observe that the proposed system can give relatively good service the vehicle moving as fast as speed 90km/h with the distance as far as 90m.

Butterfly Encryption Scheme for Resource-Constrained Wireless Networks †

PubMed Central

Sampangi, Raghav V.; Sampalli, Srinivas

2015-01-01

Resource-constrained wireless networks are emerging networks such as Radio Frequency Identification (RFID) and Wireless Body Area Networks (WBAN) that might have restrictions on the available resources and the computations that can be performed. These emerging technologies are increasing in popularity, particularly in defence, anti-counterfeiting, logistics and medical applications, and in consumer applications with growing popularity of the Internet of Things. With communication over wireless channels, it is essential to focus attention on securing data. In this paper, we present an encryption scheme called Butterfly encryption scheme. We first discuss a seed update mechanism for pseudorandom number generators (PRNG), and employ this technique to generate keys and authentication parameters for resource-constrained wireless networks. Our scheme is lightweight, as in it requires less resource when implemented and offers high security through increased unpredictability, owing to continuously changing parameters. Our work focuses on accomplishing high security through simplicity and reuse. We evaluate our encryption scheme using simulation, key similarity assessment, key sequence randomness assessment, protocol analysis and security analysis. PMID:26389899

Butterfly Encryption Scheme for Resource-Constrained Wireless Networks.

PubMed

Sampangi, Raghav V; Sampalli, Srinivas

2015-09-15

Resource-constrained wireless networks are emerging networks such as Radio Frequency Identification (RFID) and Wireless Body Area Networks (WBAN) that might have restrictions on the available resources and the computations that can be performed. These emerging technologies are increasing in popularity, particularly in defence, anti-counterfeiting, logistics and medical applications, and in consumer applications with growing popularity of the Internet of Things. With communication over wireless channels, it is essential to focus attention on securing data. In this paper, we present an encryption scheme called Butterfly encryption scheme. We first discuss a seed update mechanism for pseudorandom number generators (PRNG), and employ this technique to generate keys and authentication parameters for resource-constrained wireless networks. Our scheme is lightweight, as in it requires less resource when implemented and offers high security through increased unpredictability, owing to continuously changing parameters. Our work focuses on accomplishing high security through simplicity and reuse. We evaluate our encryption scheme using simulation, key similarity assessment, key sequence randomness assessment, protocol analysis and security analysis.

Reliability analysis of degradable networks with modified BPR

NASA Astrophysics Data System (ADS)

Wang, Yu-Qing; Zhou, Chao-Fan; Jia, Bin; Zhu, Hua-Bing

2017-12-01

In this paper, the effect of the speed limit on degradable networks with capacity restrictions and the forced flow is investigated. The link performance function considering the road capacity is proposed. Additionally, the probability density distribution and the cumulative distribution of link travel time are introduced in the degradable network. By the mean of distinguishing the value of the speed limit, four cases are discussed, respectively. Means and variances of link travel time and route one of the degradable road network are calculated. Besides, by the mean of performing numerical simulation experiments in a specific network, it is found that the speed limit strategy can reduce the travel time budget and mean travel time of link and route. Moreover, it reveals that the speed limit strategy can cut down variances of the travel time of networks to some extent.

Comments on "The multisynapse neural network and its application to fuzzy clustering".

PubMed

Yu, Jian; Hao, Pengwei

2005-05-01

In the above-mentioned paper, Wei and Fahn proposed a neural architecture, the multisynapse neural network, to solve constrained optimization problems including high-order, logarithmic, and sinusoidal forms, etc. As one of its main applications, a fuzzy bidirectional associative clustering network (FBACN) was proposed for fuzzy-partition clustering according to the objective-functional method. The connection between the objective-functional-based fuzzy c-partition algorithms and FBACN is the Lagrange multiplier approach. Unfortunately, the Lagrange multiplier approach was incorrectly applied so that FBACN does not equivalently minimize its corresponding constrained objective-function. Additionally, Wei and Fahn adopted traditional definition of fuzzy c-partition, which is not satisfied by FBACN. Therefore, FBACN can not solve constrained optimization problems, either.

Uncertainty of OpenStreetMap data for the road network in Cyprus

NASA Astrophysics Data System (ADS)

Demetriou, Demetris

2016-08-01

Volunteered geographic information (VGI) refers to the geographic data compiled and created by individuals which are rendered on the Internet through specific web-based tools for diverse areas of interest. One of the most well-known VGI projects is the OpenStreetMap (OSM) that provides worldwide free geospatial data representing a variety of features. A critical issue for all VGI initiatives is the quality of the information offered. Thus, this report looks into the uncertainty of the OSM dataset for the main road network in Cyprus. The evaluation is based on three basic quality standards, namely positional accuracy, completeness and attribute accuracy. The work has been carried out by employing the Model Builder of ArcGIS which facilitated the comparison between the OSM data and the authoritative data provided by the Public Works Department (PWD). Findings showed that the positional accuracy increases with the hierarchical level of a road, it varies per administrative District and around 70% of the roads have a positional accuracy within 6m compared to the reference dataset. Completeness in terms of road length difference is around 25% for three out of four road categories examined and road name completeness is 100% and around 40% for higher and lower level roads, respectively. Attribute accuracy focusing on road name is very high for all levels of roads. These outputs indicate that OSM data are good enough if they fit for the purpose of use. Furthermore, the study revealed some weaknesses of the methods used for calculating the positional accuracy, suggesting the need for methodological improvements.

Protecting soil and water in forest road management

Treesearch

Johnny M. III Grace; Barton D. Clinton

2007-01-01

The National Forest road system is the network that supports public recreation, which has become the primary use of the public lands. The pattern of use of National Forest roads for recreation has increased dramatically since the late 1940s and is expected to continue to increase beyond the rates observed today. However, research over the past 60 years clearly presents...

Effects of roads on elk: implications for management in forested ecosystems.

Treesearch

Mary M. Rowland; Michael J. Wisdom; Bruce K. Johnson; Mark A. Penninger

2004-01-01

The effects of roads on both habitat and population responses of elk (Cervus elaphus) have been of keen interest to foresters and ungulate biologists for the last half century. Increased timber harvest in national forests, beginning in the 1960s, led to a proliferation of road networks in forested ecosystems inhabited by elk (Hieb 1976, Lyon and...

Influence of forest and rangeland management on anadromous fish habitat in Western North America: planning forest roads to protect salmonid habitat.

Treesearch

Carlton S. Yee; Terry D. Roelofs

1980-01-01

The construction and existence of forest roads, landings, and decking areas may have significant effects on anadromous fish habitat . Major effects discussed in this paper are increased sedimentation from transportation networks, the hindrance to fish migration of drainage structures, and possible changes in water quality from road stabilization additives. Guidelines...

General view of Antenna Array and building complex, looking northeast ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

General view of Antenna Array and building complex, looking northeast - Over-the-Horizon Backscatter Radar Network, Tulelake Radar Site Receive Sector Six Antenna Array, Unnamed Road West of Double Head Road, Tulelake, Siskiyou County, CA

General view of Antenna Array and building complex, looking southwest ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

General view of Antenna Array and building complex, looking southwest - Over-the-Horizon Backscatter Radar Network, Tulelake Radar Site Receive Sector Six Antenna Array, Unnamed Road West of Double Head Road, Tulelake, Siskiyou County, CA

Relating Diarrheal Disease to Social Networks and the Geographic Configuration of Communities in Rural Ecuador

PubMed Central

Bates, Sarah J.; Trostle, James; Cevallos, William T.; Hubbard, Alan; Eisenberg, Joseph N. S.

2008-01-01

Social networks and geographic structures of communities are important predictors of infectious disease transmission. To examine their joint effects on diarrheal disease and how these effects might develop, the authors analyzed social network and geographic data from northern coastal Ecuador and examined associations with diarrhea prevalence. Between July 2003 and May 2005, 113 cases of diarrhea were identified in nine communities. Concurrently, sociometric surveys were conducted, and households were mapped with geographic information systems. Spatial distribution metrics of households within communities and of communities with respect to roads were developed that predict social network degree in casual contact (“contact”) and food-sharing (“food”) networks. The mean degree is 25-40% lower in communities with versus without road access and 66-94% lower in communities with lowest versus highest housing density. Associations with diarrheal disease were found for housing density (comparing dense with dispersed communities: risk ratio = 3.3, 95% confidence interval (CI): 1.1, 10.0) and social connectedness (comparing lowest with highest degree communities: risk ratio = 3.4, 95% CI: 1.1, 10.1 in the contact network and risk ratio = 4.9, 95% CI: 1.1, 21.9 in the food network). Some of these differences may be related to more new residents, lower housing density, and less social connectedness in road communities. PMID:17690221

Evaluating the impact and risk of pluvial flash flood on intra-urban road network: A case study in the city center of Shanghai, China

NASA Astrophysics Data System (ADS)

Yin, Jie; Yu, Dapeng; Yin, Zhane; Liu, Min; He, Qing

2016-06-01

Urban pluvial flood are attracting growing public concern due to rising intense precipitation and increasing consequences. Accurate risk assessment is critical to an efficient urban pluvial flood management, particularly in transportation sector. This paper describes an integrated methodology, which initially makes use of high resolution 2D inundation modeling and flood depth-dependent measure to evaluate the potential impact and risk of pluvial flash flood on road network in the city center of Shanghai, China. Intensity-Duration-Frequency relationships of Shanghai rainstorm and Chicago Design Storm are combined to generate ensemble rainfall scenarios. A hydrodynamic model (FloodMap-HydroInundation2D) is used to simulate overland flow and flood inundation for each scenario. Furthermore, road impact and risk assessment are respectively conducted by a new proposed algorithm and proxy. Results suggest that the flood response is a function of spatio-temporal distribution of precipitation and local characteristics (i.e. drainage and topography), and pluvial flash flood is found to lead to proportionate but nonlinear impact on intra-urban road inundation risk. The approach tested here would provide more detailed flood information for smart management of urban street network and may be applied to other big cities where road flood risk is evolving in the context of climate change and urbanization.

Teaching Structured Design of Network Algorithms in Enhanced Versions of SQL

ERIC Educational Resources Information Center

de Brock, Bert

2004-01-01

From time to time developers of (database) applications will encounter, explicitly or implicitly, structures such as trees, graphs, and networks. Such applications can, for instance, relate to bills of material, organization charts, networks of (rail)roads, networks of conduit pipes (e.g., plumbing, electricity), telecom networks, and data…

Research on Closed Residential Area Based on Balanced Distribution Theory

NASA Astrophysics Data System (ADS)

Lan, Si; Fang, Ni; Lin, Hai Peng; Ye, Shi Qi

2018-06-01

With the promotion of the street system, residential quarters and units of the compound gradually open. In this paper, the relationship between traffic flow and traffic flow is established for external roads, and the road resistance model is established by internal roads. We propose a balanced distribution model from the two aspects of road opening conditions and traffic flow inside and outside the district, and quantitatively analyze the impact of the opening and closing on the surrounding roads. Finally, it puts forward feasible suggestions to improve the traffic situation and optimize the network structure.

Improving Service Management in the Internet of Things

PubMed Central

Sammarco, Chiara; Iera, Antonio

2012-01-01

In the Internet of Things (IoT) research arena, many efforts are devoted to adapt the existing IP standards to emerging IoT nodes. This is the direction followed by three Internet Engineering Task Force (IETF) Working Groups, which paved the way for research on IP-based constrained networks. Through a simplification of the whole TCP/IP stack, resource constrained nodes become direct interlocutors of application level entities in every point of the network. In this paper we analyze some side effects of this solution, when in the presence of large amounts of data to transmit. In particular, we conduct a performance analysis of the Constrained Application Protocol (CoAP), a widely accepted web transfer protocol for the Internet of Things, and propose a service management enhancement that improves the exploitation of the network and node resources. This is specifically thought for constrained nodes in the abovementioned conditions and proves to be able to significantly improve the node energetic performance when in the presence of large resource representations (hence, large data transmissions).

A Mechanism for Reliable Mobility Management for Internet of Things Using CoAP

PubMed Central

Chun, Seung-Man; Park, Jong-Tae

2017-01-01

Under unreliable constrained wireless networks for Internet of Things (IoT) environments, the loss of the signaling message may frequently occur. Mobile Internet Protocol version 6 (MIPv6) and its variants do not consider this situation. Consequently, as a constrained device moves around different wireless networks, its Internet Protocol (IP) connectivity may be frequently disrupted and power can be drained rapidly. This can result in the loss of important sensing data or a large delay for time-critical IoT services such as healthcare monitoring and disaster management. This paper presents a reliable mobility management mechanism in Internet of Things environments with lossy low-power constrained device and network characteristics. The idea is to use the Internet Engineering Task Force (IETF) Constrained Application Protocol (CoAP) retransmission mechanism to achieve both reliability and simplicity for reliable IoT mobility management. Detailed architecture, algorithms, and message extensions for reliable mobility management are presented. Finally, performance is evaluated using both mathematical analysis and simulation. PMID:28085109

A Mechanism for Reliable Mobility Management for Internet of Things Using CoAP.

PubMed

Chun, Seung-Man; Park, Jong-Tae

2017-01-12

Under unreliable constrained wireless networks for Internet of Things (IoT) environments, the loss of the signaling message may frequently occur. Mobile Internet Protocol version 6 (MIPv6) and its variants do not consider this situation. Consequently, as a constrained device moves around different wireless networks, its Internet Protocol (IP) connectivity may be frequently disrupted and power can be drained rapidly. This can result in the loss of important sensing data or a large delay for time-critical IoT services such as healthcare monitoring and disaster management. This paper presents a reliable mobility management mechanism in Internet of Things environments with lossy low-power constrained device and network characteristics. The idea is to use the Internet Engineering Task Force (IETF) Constrained Application Protocol (CoAP) retransmission mechanism to achieve both reliability and simplicity for reliable IoT mobility management. Detailed architecture, algorithms, and message extensions for reliable mobility management are presented. Finally, performance is evaluated using both mathematical analysis and simulation.

Evaluating drug trafficking on the Tor Network: Silk Road 2, the sequel.

PubMed

Dolliver, Diana S

2015-11-01

Housing an illicit, online drug retail market generating sales in the millions of USD, the Silk Road was a profitable marketplace with a growing and loyal consumer base. Following its FBI-forced shut down in October 2013, the Silk Road enjoyed newfound fame that contributed to an increase in new users downloading and accessing the Tor Network; however, with this particular marketplace out of order, Silk Road 2 was launched to fill the void. The goals of this study were to (1) compare the metrics of Silk Road 2 to the original site, and to (2) determine if there were any indications of the presence of more sophisticated drug trafficking operations. Data were collected from Silk Road 2 during the months of August and September 2014 using webcrawling software. Silk Road 2 was a much smaller marketplace than the original Silk Road. Of the 1834 unique items for sale, 348 were drug items sold by 145 distinct vendors shipping from 19 countries. Of the drug items advertised, most were stimulants and hallucinogens. The United States is both the number one country of origin for drug sales on Silk Road 2 and the number one destination country. Interestingly, 73% of all vendor accounts on Silk Road 2 advertised drug items, even though drugs only constituted 19% of all items advertised. This study was the first to research Silk Road 2, the replacement illicit marketplace to the original virtual Silk Road. This study was also the first to examine indications of the presence of more coordinated drug trafficking efforts in an online setting. The findings indicated that while Silk Road 2 was not primarily a drug market, there were indications that some vendor accounts may have connections reaching beyond a base retail market. Copyright © 2015 Elsevier B.V. All rights reserved.

Thermal mapping as a valuable tool for road weather forecast and winter road maintenance: an example from the Italian Alps

NASA Astrophysics Data System (ADS)

Todeschini, Ilaria; Di Napoli, Claudia; Pretto, Ilaria; Merler, Giacomo; Cavaliere, Roberto; Apolloni, Roberto; Antonacci, Gianluca; Piazza, Andrea; Benedetti, Guido

2016-08-01

During the winter period ice is likely to form on roads, making pavement surfaces slippery and increasing accident risk. Road surface temperature (RST) is one of the most important parameters in ice formation. The LIFE+ "CLEANROADS" project aims to forecast RSTs in advance in order to support road maintenance services in the timely and effective preparation of preventive anti-icing measures. This support is provided through a novel MDSS (Maintenance Decision Support System). The final goal of the project is to quantitatively demonstrate that the implemented MDSS is capable to minimize the consumption of chemical anti-icing reagents (e.g. sodium chloride) and the associated environmental (water and air) impact while maintaining the current high levels of road safety. In the CLEAN-ROADS system RSTs have been forecast by applying the numerical model METRo (Model of the Environment and Temperature of Roads) to a network of RWIS (Road Weather Information System) stations installed on a test route in the Adige Valley (Italy). This forecast is however local and does not take into account typical peculiarities along road network, such as the presence of road sections that are particularly prone to ice formation. Thermal mapping, i.e. the acquisition of mobile RST measurements through infrared thermometry, permits to (i) identify and map those sections, and (ii) extend the forecast from a RWIS station to adjacent areas. The processing of thermal mapping signals is however challenging because of random variations in the road surface emissivity. To overcome this we have acquired several thermal mapping traces along the test route during winter seasons 2014-2015 and 2015-2016. We have then defined a "characteristic" thermal fingerprint as a function of all its historical thermal mapping signals, and used it to spatialize local METRo forecasts. Preliminary results suggest the high potential of such a technique for winter road applications.

Sources and timing of anthropogenic pollution in the Ensenada de San Simon (inner Ria de Vigo), Galicia, NW Spain: an application of mixture-modelling and nonlinear optimization to recent sedimentation.

PubMed

Howarth, Richard J; Evans, Graham; Croudace, Ian W; Cundy, Andrew B

2005-03-20

The Ensenada de San Simon is the inner part of the Ria de Vigo, one of the major mesotidal rias of the Galician coast, NW Spain. The geochemistry of its bottom sediments can be accounted for in terms of both natural and anthropogenic sources. Mixture-modelling enables much of the Cr, Ni, V, Cu, Pb and Zn concentrations of the bottom and subaqueous sediments to be explained by sediment input from the river systems and faecal matter from manmade mussel rafts. The compositions and relative contributions of additional, unknown, sources of anomalous heavy-metal concentrations are quantified using constrained nonlinear optimization. The pattern of metal enrichment is attributed to: material carried in solution and suspension in marine water entering the Ensenada from the polluted industrial areas of the adjacent Ria de Vigo; wind-borne urban dusts and/or vehicular emissions from the surrounding network of roads and a motorway road-bridge over the Estrecho de Rande; industrial and agricultural pollution from the R. Redondela; and waste from a former ceramics factory near the mouth of the combined R. Oitaben and R. Verdugo. Using (137)Cs dating, it is suggested that heavy metal build-up in the sediments since the late 1970s followed development of inshore fisheries and introduction of the mussel rafts (ca. 1960) and increasing industrialisation.

Optimal synchronization in space

NASA Astrophysics Data System (ADS)

Brede, Markus

2010-02-01

In this Rapid Communication we investigate spatially constrained networks that realize optimal synchronization properties. After arguing that spatial constraints can be imposed by limiting the amount of “wire” available to connect nodes distributed in space, we use numerical optimization methods to construct networks that realize different trade offs between optimal synchronization and spatial constraints. Over a large range of parameters such optimal networks are found to have a link length distribution characterized by power-law tails P(l)∝l-α , with exponents α increasing as the networks become more constrained in space. It is also shown that the optimal networks, which constitute a particular type of small world network, are characterized by the presence of nodes of distinctly larger than average degree around which long-distance links are centered.

Performance of alternative diamond interchange forms : volume I -- research report.

DOT National Transportation Integrated Search

2017-01-01

Service interchanges connect freeways to arterial roads and are the backbone of the U.S. road network. Improving the operations of service interchanges is possible by applying one of several new solutions: diverging diamond, single point interchanges...

Improving the Wyoming road weather information system

DOT National Transportation Integrated Search

1998-11-01

Studies in other states and countries have shown that Road Weather Information Systems (RWIS) can improve the efficiency of snow and ice control operations and reduce accidents. The RWIS network in Wyoming is presently comprised of 27 roadside weathe...

View to the eastnortheast of the Sounder Antenna OvertheHorizon ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

View to the east-northeast of the Sounder Antenna - Over-the-Horizon Backscatter Radar Network, Christmas Valley Radar Site Transmit Sector Five Sounder Antennas, On unnamed road west of Lost Forest Road, Christmas Valley, Lake County, OR

View to the northeast of the antenna array OvertheHorizon ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

View to the northeast of the antenna array - Over-the-Horizon Backscatter Radar Network, Christmas Valley Radar Site Transmit Sector Four Antenna Array, On unnamed road west of Lost Forest Road, Christmas Valley, Lake County, OR

View to the eastnortheast of the Antenna Array OvertheHorizon ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

View to the east-northeast of the Antenna Array - Over-the-Horizon Backscatter Radar Network, Christmas Valley Radar Site Transmit Sector Six Antenna Array, On unnamed road west of Lost Forest Road, Christmas Valley, Lake County, OR

General view to the south of the antenna array ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

General view to the south of the antenna array - Over-the-Horizon Backscatter Radar Network, Christmas Valley Radar Site Transmit Sector Five Antenna Array, On unnamed road west of Lost Forest Road, Christmas Valley, Lake County, OR

Detail view to the east of the Antenna Array ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Detail view to the east of the Antenna Array - Over-the-Horizon Backscatter Radar Network, Christmas Valley Radar Site Transmit Sector Six Antenna Array, On unnamed road west of Lost Forest Road, Christmas Valley, Lake County, OR

View to the east of the Antenna Array OvertheHorizon ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

View to the east of the Antenna Array - Over-the-Horizon Backscatter Radar Network, Christmas Valley Radar Site Transmit Sector Six Antenna Array, On unnamed road west of Lost Forest Road, Christmas Valley, Lake County, OR

Oblique view to the northwest of the Antenna Array ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Oblique view to the northwest of the Antenna Array - Over-the-Horizon Backscatter Radar Network, Christmas Valley Radar Site Transmit Sector Six Antenna Array, On unnamed road west of Lost Forest Road, Christmas Valley, Lake County, OR

View to the north of the Two Communications Antenna ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

View to the north of the Two Communications Antenna - Over-the-Horizon Backscatter Radar Network, Christmas Valley Radar Site Transmit Sector Four Communications Antennas, On unnamed road west of Lost Forest Road, Christmas Valley, Lake County, OR

General view to the northwest of the antenna array ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

General view to the northwest of the antenna array - Over-the-Horizon Backscatter Radar Network, Christmas Valley Radar Site Transmit Sector Five Antenna Array, On unnamed road west of Lost Forest Road, Christmas Valley, Lake County, OR

View to the northeast of the Sounder Antenna OvertheHorizon ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

View to the northeast of the Sounder Antenna - Over-the-Horizon Backscatter Radar Network, Christmas Valley Radar Site Transmit Sector Five Sounder Antennas, On unnamed road west of Lost Forest Road, Christmas Valley, Lake County, OR

Constrained State Estimation for Individual Localization in Wireless Body Sensor Networks

PubMed Central

Feng, Xiaoxue; Snoussi, Hichem; Liang, Yan; Jiao, Lianmeng

2014-01-01

Wireless body sensor networks based on ultra-wideband radio have recently received much research attention due to its wide applications in health-care, security, sports and entertainment. Accurate localization is a fundamental problem to realize the development of effective location-aware applications above. In this paper the problem of constrained state estimation for individual localization in wireless body sensor networks is addressed. Priori knowledge about geometry among the on-body nodes as additional constraint is incorporated into the traditional filtering system. The analytical expression of state estimation with linear constraint to exploit the additional information is derived. Furthermore, for nonlinear constraint, first-order and second-order linearizations via Taylor series expansion are proposed to transform the nonlinear constraint to the linear case. Examples between the first-order and second-order nonlinear constrained filters based on interacting multiple model extended kalman filter (IMM-EKF) show that the second-order solution for higher order nonlinearity as present in this paper outperforms the first-order solution, and constrained IMM-EKF obtains superior estimation than IMM-EKF without constraint. Another brownian motion individual localization example also illustrates the effectiveness of constrained nonlinear iterative least square (NILS), which gets better filtering performance than NILS without constraint. PMID:25390408

A neural-network-based model for the dynamic simulation of the tire/suspension system while traversing road irregularities.

PubMed

Guarneri, Paolo; Rocca, Gianpiero; Gobbi, Massimiliano

2008-09-01

This paper deals with the simulation of the tire/suspension dynamics by using recurrent neural networks (RNNs). RNNs are derived from the multilayer feedforward neural networks, by adding feedback connections between output and input layers. The optimal network architecture derives from a parametric analysis based on the optimal tradeoff between network accuracy and size. The neural network can be trained with experimental data obtained in the laboratory from simulated road profiles (cleats). The results obtained from the neural network demonstrate good agreement with the experimental results over a wide range of operation conditions. The NN model can be effectively applied as a part of vehicle system model to accurately predict elastic bushings and tire dynamics behavior. Although the neural network model, as a black-box model, does not provide a good insight of the physical behavior of the tire/suspension system, it is a useful tool for assessing vehicle ride and noise, vibration, harshness (NVH) performance due to its good computational efficiency and accuracy.

With Geospatial in Path of Smart City

NASA Astrophysics Data System (ADS)

Homainejad, A. S.

2015-04-01

With growth of urbanisation, there is a requirement for using the leverage of smart city in city management. The core of smart city is Information and Communication Technologies (ICT), and one of its elements is smart transport which includes sustainable transport and Intelligent Transport Systems (ITS). Cities and especially megacities are facing urgent transport challenge in traffic management. Geospatial can provide reliable tools for monitoring and coordinating traffic. In this paper a method for monitoring and managing the ongoing traffic in roads using aerial images and CCTV will be addressed. In this method, the road network was initially extracted and geo-referenced and captured in a 3D model. The aim is to detect and geo-referenced any vehicles on the road from images in order to assess the density and the volume of vehicles on the roads. If a traffic jam was recognised from the images, an alternative route would be suggested for easing the traffic jam. In a separate test, a road network was replicated in the computer and a simulated traffic was implemented in order to assess the traffic management during a pick time using this method.

Controllability of switched singular mix-valued logical control networks with constraints

NASA Astrophysics Data System (ADS)

Deng, Lei; Gong, Mengmeng; Zhu, Peiyong

2018-03-01

The present paper investigates the controllability problem of switched singular mix-valued logical control networks (SSMLCNs) with constraints on states and controls. First, using the semi-tenser product (STP) of matrices, the SSMLCN is expressed in an algebraic form, based on which a necessary and sufficient condition is given for the uniqueness of solution of SSMLCNs. Second, a necessary and sufficient criteria is derived for the controllability of constrained SSMLCNs, by converting a constrained SSMLCN into a parallel constrained switched mix-valued logical control network. Third, an algorithm is presented to design a proper switching sequence and a control scheme which force a state to a reachable state. Finally, a numerical example is given to demonstrate the efficiency of the results obtained in this paper.

Forest road management to protect soil and water

Treesearch

J. McFero Grace; Barton D. Clinton

2006-01-01

The National Forest road system is the network that supports recreation which has become the primary use of the public lands. The pattern of use of National Forest roads for recreation by the public has increased dramatically since the late 1940’s and is expected to continue to increase beyond the rates observed today. However, research over the past 60 years clearly...

Roadless Wilderness Area Determines Forest Elephant Movements in the Congo Basin

PubMed Central

Blake, Stephen; Deem, Sharon L.; Strindberg, Samantha; Maisels, Fiona; Momont, Ludovic; Isia, Inogwabini-Bila; Douglas-Hamilton, Iain; Karesh, William B.; Kock, Michael D.

2008-01-01

A dramatic expansion of road building is underway in the Congo Basin fuelled by private enterprise, international aid, and government aspirations. Among the great wilderness areas on earth, the Congo Basin is outstanding for its high biodiversity, particularly mobile megafauna including forest elephants (Loxodonta africana cyclotis). The abundance of many mammal species in the Basin increases with distance from roads due to hunting pressure, but the impacts of road proliferation on the movements of individuals are unknown. We investigated the ranging behaviour of forest elephants in relation to roads and roadless wilderness by fitting GPS telemetry collars onto a sample of 28 forest elephants living in six priority conservation areas. We show that the size of roadless wilderness is a strong determinant of home range size in this species. Though our study sites included the largest wilderness areas in central African forests, none of 4 home range metrics we calculated, including core area, tended toward an asymptote with increasing wilderness size, suggesting that uninhibited ranging in forest elephants no longer exists. Furthermore we show that roads outside protected areas which are not protected from hunting are a formidable barrier to movement while roads inside protected areas are not. Only 1 elephant from our sample crossed an unprotected road. During crossings her mean speed increased 14-fold compared to normal movements. Forest elephants are increasingly confined and constrained by roads across the Congo Basin which is reducing effective habitat availability and isolating populations, significantly threatening long term conservation efforts. If the current road development trajectory continues, forest wildernesses and the forest elephants they contain will collapse. PMID:18958284

Modeling the effects of different fuel treatment mosaics on wildfire spread and behavior in a Mediterranean agro-pastoral area.

PubMed

Salis, Michele; Del Giudice, Liliana; Arca, Bachisio; Ager, Alan A; Alcasena-Urdiroz, Fermin; Lozano, Olga; Bacciu, Valentina; Spano, Donatella; Duce, Pierpaolo

2018-04-15

Wildfire spread and behavior can be limited by fuel treatments, even if their effects can vary according to a number of factors including type, intensity, extension, and spatial arrangement. In this work, we simulated the response of key wildfire exposure metrics to variations in the percentage of treated area, treatment unit size, and spatial arrangement of fuel treatments under different wind intensities. The study was carried out in a fire-prone 625 km 2 agro-pastoral area mostly covered by herbaceous fuels, and located in Northern Sardinia, Italy. We constrained the selection of fuel treatment units to areas covered by specific herbaceous land use classes and low terrain slope (<10%). We treated 2%, 5% and 8% of the landscape area, and identified priority sites to locate the fuel treatment units for all treatment alternatives. The fuel treatment alternatives were designed create diverse mosaics of disconnected treatment units with different sizes (0.5-10 ha, LOW strategy; 10-25 ha, MED strategy; 25-50 ha, LAR strategy); in addition, treatment units in a 100-m buffer around the road network (ROAD strategy) were tested. We assessed pre- and post-treatment wildfire behavior by the Minimum Travel Time (MTT) fire spread algorithm. The simulations replicated a set of southwestern wind speed scenarios (16, 24 and 32 km h -1 ) and the driest fuel moisture conditions observed in the study area. Our results showed that fuel treatments implemented near the existing road network were significantly more efficient than the other alternatives, and this difference was amplified at the highest wind speed. Moreover, the largest treatment unit sizes were the most effective in containing wildfire growth. As expected, increasing the percentage of the landscape treated and reducing wind speed lowered fire exposure profiles for all fuel treatment alternatives, and this was observed at both the landscape scale and for highly valued resources. The methodology presented in this study can support the design and optimization of fuel management programs and policies in agro-pastoral areas of the Mediterranean Basin and herbaceous type landscapes elsewhere, where recurrent grassland fires pose a threat to rural communities, farms and infrastructures. Copyright © 2018 Elsevier Ltd. All rights reserved.

Unofficial Road Building in the Brazilian Amazon: Dilemmas and Models for Road Governance

NASA Technical Reports Server (NTRS)

Perz, Stephen G.; Overdevest, Christine; Caldas, Marcellus M.; Walker, Robert T.; Arima, Eugenio Y.

2007-01-01

Unofficial roads form dense networks in landscapes, generating a litany of negative ecological outcomes, but unofficial roads in frontier areas are also instrumental in local livelihoods and community development. This trade-off poses dilemmas for the governance of unofficial roads. Unofficial road building in frontier areas of the Brazilian Amazon illustrates the challenges of 'road governance.' Both state-based and community based governance models exhibit important liabilities for governing unofficial roads. Whereas state-based governance has experienced difficulties in adapting to specific local contexts and interacting effectively with local interest groups, community-based governance has a mixed record owing to social inequalities and conflicts among local interest groups. A state-community hybrid model may offer more effective governance of unofficial road building by combining the oversight capacity of the state with locally grounded community management via participatory decision-making.

Automatic detection of zebra crossings from mobile LiDAR data

NASA Astrophysics Data System (ADS)

Riveiro, B.; González-Jorge, H.; Martínez-Sánchez, J.; Díaz-Vilariño, L.; Arias, P.

2015-07-01

An algorithm for the automatic detection of zebra crossings from mobile LiDAR data is developed and tested to be applied for road management purposes. The algorithm consists of several subsequent processes starting with road segmentation by performing a curvature analysis for each laser cycle. Then, intensity images are created from the point cloud using rasterization techniques, in order to detect zebra crossing using the Standard Hough Transform and logical constrains. To optimize the results, image processing algorithms are applied to the intensity images from the point cloud. These algorithms include binarization to separate the painting area from the rest of the pavement, median filtering to avoid noisy points, and mathematical morphology to fill the gaps between the pixels in the border of white marks. Once the road marking is detected, its position is calculated. This information is valuable for inventorying purposes of road managers that use Geographic Information Systems. The performance of the algorithm has been evaluated over several mobile LiDAR strips accounting for a total of 30 zebra crossings. That test showed a completeness of 83%. Non-detected marks mainly come from painting deterioration of the zebra crossing or by occlusions in the point cloud produced by other vehicles on the road.

Interior view to the east of an empty computer room ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Interior view to the east of an empty computer room - Over-the-Horizon Backscatter Radar Network, Christmas Valley Radar Site Transmit Sector Six Transmitter Building, On unnamed road west of Lost Forest Road, Christmas Valley, Lake County, OR

Traffic Data Collection And Use In The Mexican Interurban Road Network

DOT National Transportation Integrated Search

2000-08-01

This paper describes how in the past, road construction in Mexico was linked more to sociopolitical concerns than to technical or economic studies to justify their construction. Now, new approaches are considered for the planning, construction, maint...

Solar potential scaling and the urban road network topology

NASA Astrophysics Data System (ADS)

Najem, Sara

2017-01-01

We explore the scaling of cities' solar potentials with their number of buildings and reveal a latent dependence between the solar potential and the length of the corresponding city's road network. This scaling is shown to be valid at the grid and block levels and is attributed to a common street length distribution. Additionally, we compute the buildings' solar potential correlation function and length in order to determine the set of critical exponents typifying the urban solar potential universality class.

The Road Traffic Injuries Research Network: a decade of research capacity strengthening in low- and middle-income countries.

PubMed

Hyder, Adnan A; Norton, Robyn; Pérez-Núñez, Ricardo; Mojarro-Iñiguez, Francisco R; Peden, Margie; Kobusingye, Olive

2016-02-27

Road traffic crashes have been an increasing threat to the wellbeing of road users worldwide; an unacceptably high number of people die or become disabled from them. While high-income countries have successfully implemented effective interventions to help reduce the burden of road traffic injuries (RTIs) in their countries, low- and middle-income countries (LMICs) have not yet achieved similar results. Both scientific research and capacity development have proven to be useful for preventing RTIs in high-income countries. In 1999, a group of leading researchers from different countries decided to join efforts to help promote research on RTIs and develop the capacity of professionals from LMICs. This translated into the creation of the Road Traffic Injuries Research Network (RTIRN) - a partnership of over 1,100 road safety professionals from 114 countries collaborating to facilitate reductions in the burden of RTIs in LMICs by identifying and promoting effective, evidenced-based interventions and supporting research capacity building in road safety research in LMICs. This article presents the work that RTIRN has done over more than a decade, including production of a dozen scientific papers, support of nearly 100 researchers, training of nearly 1,000 people and 35 scholarships granted to researchers from LMICs to attend world conferences, as well as lessons learnt and future challenges to maximize its work.

[Emission Characteristics of Vehicle Exhaust in Beijing Based on Actual Traffic Flow Information].

PubMed

Fan, Shou-bin; Tian, Ling-di; Zhang, Dong-xu; Qu, Song

2015-08-01

The basic data of traffic volume, vehicle type constitute and speed on road networks in Beijing was obtained fly modei simulation and field survey. Based on actual traffic flow information and. emission factors data with temporal and spatial distribution features, emission inventory of motor vehicle exhaust in Beijing was built on the ArcGIS platform, meanwhile, the actual road emission characteristics and spatial distribution of the pollutant emissions were analyzed. The results showed that the proportion of passenger car was higher than 89% on each type of road in the urban, and the proportion of passenger car was the highest in suburban roads as well while the pickup truck, medium truck, heavy truck, motorbus, tractor and motorcycle also occupied a certain proportion. There was a positive correlation between the pollutant emission intensity and traffic volume, and the emission intensity was generally higher in daytime than nighttime, but the diurnal variation trend of PM emission was not clear for suburban roads and the emission intensity was higher in nighttime than daytime for highway. The emission intensities in urban area, south, southeast and northeast areas near urban were higher than those in the western and northern mountainous areas with lower density of road network. The ring roads in urban and highways in suburban had higher emission intensity because of the heavy traffic volume.

Risk-based flood-planning strategy for Vermont's roadway network.

DOT National Transportation Integrated Search

2015-06-01

In this project, the authors extend the use of a previously established measure of link-specific criticality, the Network Robustness Index (NRI), to address disruptions in Vermonts federal-aid road network caused by summertime flooding. The goal o...

Performance of alternative diamond interchange forms : Volume II--guidelines for selecting alternative diamond interchanges.

DOT National Transportation Integrated Search

2017-01-01

Service interchanges connect freeways to arterial roads and are the backbone of the U.S. road network. Improving the operations of service interchanges is possible by applying one of several new solutions: diverging diamond, single point interchanges...

Quantifying the effects of network improvement actions on the value of new and existing toll road projects.

DOT National Transportation Integrated Search

2010-02-01

Development, delivery, and operation of public infrastructure are becoming increasingly dependent on : participation of the private sector. While revenue generating projects, such as toll roads, were traditionally : developed and funded from the publ...

View north of the antenna array, note the communications antenna ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

View north of the antenna array, note the communications antenna in the middleground - Over-the-Horizon Backscatter Radar Network, Christmas Valley Radar Site Transmit Sector Four Antenna Array, On unnamed road west of Lost Forest Road, Christmas Valley, Lake County, OR

View to the southwest of the Two Communications Antenna and ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

View to the southwest of the Two Communications Antenna and their associated structures - Over-the-Horizon Backscatter Radar Network, Christmas Valley Radar Site Transmit Sector Four Communications Antennas, On unnamed road west of Lost Forest Road, Christmas Valley, Lake County, OR

View to the south with the Two Sounder Antennas on ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

View to the south with the Two Sounder Antennas on the left - Over-the-Horizon Backscatter Radar Network, Christmas Valley Radar Site Transmit Sector Four Sounder Antennas, On unnamed road west of Lost Forest Road, Christmas Valley, Lake County, OR

General view of Sector Six Compound, looking east. Water Storage ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

General view of Sector Six Compound, looking east. Water Storage Tank is at left - Over-the-Horizon Backscatter Radar Network, Tulelake Radar Site Receive Sector Six Water Storage Plant, Unnamed Road West of Double Head Road, Tulelake, Siskiyou County, CA

State estimation with incomplete nonlinear constraint

NASA Astrophysics Data System (ADS)

Huang, Yuan; Wang, Xueying; An, Wei

2017-10-01

A problem of state estimation with a new constraints named incomplete nonlinear constraint is considered. The targets are often move in the curve road, if the width of road is neglected, the road can be considered as the constraint, and the position of sensors, e.g., radar, is known in advance, this info can be used to enhance the performance of the tracking filter. The problem of how to incorporate the priori knowledge is considered. In this paper, a second-order sate constraint is considered. A fitting algorithm of ellipse is adopted to incorporate the priori knowledge by estimating the radius of the trajectory. The fitting problem is transformed to the nonlinear estimation problem. The estimated ellipse function is used to approximate the nonlinear constraint. Then, the typical nonlinear constraint methods proposed in recent works can be used to constrain the target state. Monte-Carlo simulation results are presented to illustrate the effectiveness proposed method in state estimation with incomplete constraint.

Identifying security checkpoints locations to protect the major U.S. urban areas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cuellar-Hengartner, Leticia; Watkins, Daniel; Kubicek, Deborah A.

Transit networks are integral to the economy and to society, but at the same time they could allow terrorists to transport weapons of mass destruction into any city. Road networks are especially vulnerable, because they lack natural checkpoints unlike air networks that have security measures in place at all major airports. One approach to mitigate this risk is ensuring that every road route passes through at least one security checkpoint. Using the Ford-Fulkerson maximum-flow algorithm, we generate a minimum set of checkpoint locations within a ring-shaped buffer area surrounding the 50 largest US urban areas. We study how the numbermore » of checkpoints changes as we increase the buffer width to perform a cost-benefit analysis and to identify groups of cities that behave similarly. The set of required checkpoints is surprisingly small (10-124) despite the hundreds of thousands of road arcs in those areas, making it feasible to protect all major cities.« less

Realistic Data-Driven Traffic Flow Animation Using Texture Synthesis.

PubMed

Chao, Qianwen; Deng, Zhigang; Ren, Jiaping; Ye, Qianqian; Jin, Xiaogang

2018-02-01

We present a novel data-driven approach to populate virtual road networks with realistic traffic flows. Specifically, given a limited set of vehicle trajectories as the input samples, our approach first synthesizes a large set of vehicle trajectories. By taking the spatio-temporal information of traffic flows as a 2D texture, the generation of new traffic flows can be formulated as a texture synthesis process, which is solved by minimizing a newly developed traffic texture energy. The synthesized output captures the spatio-temporal dynamics of the input traffic flows, and the vehicle interactions in it strictly follow traffic rules. After that, we position the synthesized vehicle trajectory data to virtual road networks using a cage-based registration scheme, where a few traffic-specific constraints are enforced to maintain each vehicle's original spatial location and synchronize its motion in concert with its neighboring vehicles. Our approach is intuitive to control and scalable to the complexity of virtual road networks. We validated our approach through many experiments and paired comparison user studies.

Identifying security checkpoints locations to protect the major U.S. urban areas

DOE PAGES

Cuellar-Hengartner, Leticia; Watkins, Daniel; Kubicek, Deborah A.; ...

2015-09-01

Transit networks are integral to the economy and to society, but at the same time they could allow terrorists to transport weapons of mass destruction into any city. Road networks are especially vulnerable, because they lack natural checkpoints unlike air networks that have security measures in place at all major airports. One approach to mitigate this risk is ensuring that every road route passes through at least one security checkpoint. Using the Ford-Fulkerson maximum-flow algorithm, we generate a minimum set of checkpoint locations within a ring-shaped buffer area surrounding the 50 largest US urban areas. We study how the numbermore » of checkpoints changes as we increase the buffer width to perform a cost-benefit analysis and to identify groups of cities that behave similarly. The set of required checkpoints is surprisingly small (10-124) despite the hundreds of thousands of road arcs in those areas, making it feasible to protect all major cities.« less

Individual- and area-level disparities in access to the road network, subway system and a public bicycle share program on the Island of Montreal, Canada.

PubMed

Fuller, Daniel; Gauvin, Lise; Kestens, Yan

2013-02-01

Few studies have examined potential disparities in access to transportation infrastructures, an important determinant of population health. To examine individual- and area-level disparities in access to the road network, public transportation system, and a public bicycle share program in Montreal, Canada. Examining associations between sociodemographic variables and access to the road network, public transportation system, and a public bicycle share program, 6,495 adult respondents (mean age, 48.7 years; 59.0 % female) nested in 33 areas were included in a multilevel analysis. Individuals with lower incomes lived significantly closer to public transportation and the bicycle share program. At the area level, the interaction between low-education and low-income neighborhoods showed that these areas were significantly closer to public transportation and the bicycle share program controlling for individual and urbanicity variables. More deprived areas of the Island of Montreal have better access to transportation infrastructure than less-deprived areas.

Neural Network Assisted Inverse Dynamic Guidance for Terminally Constrained Entry Flight

PubMed Central

Chen, Wanchun

2014-01-01

This paper presents a neural network assisted entry guidance law that is designed by applying Bézier approximation. It is shown that a fully constrained approximation of a reference trajectory can be made by using the Bézier curve. Applying this approximation, an inverse dynamic system for an entry flight is solved to generate guidance command. The guidance solution thus gotten ensures terminal constraints for position, flight path, and azimuth angle. In order to ensure terminal velocity constraint, a prediction of the terminal velocity is required, based on which, the approximated Bézier curve is adjusted. An artificial neural network is used for this prediction of the terminal velocity. The method enables faster implementation in achieving fully constrained entry flight. Results from simulations indicate improved performance of the neural network assisted method. The scheme is expected to have prospect for further research on automated onboard control of terminal velocity for both reentry and terminal guidance laws. PMID:24723821

Ancient trade routes shaped the genetic structure of horses in eastern Eurasia.

PubMed

Warmuth, Vera M; Campana, Michael G; Eriksson, Anders; Bower, Mim; Barker, Graeme; Manica, Andrea

2013-11-01

Animal exchange networks have been shown to play an important role in determining gene flow among domestic animal populations. The Silk Road is one of the oldest continuous exchange networks in human history, yet its effectiveness in facilitating animal exchange across large geographical distances and topographically challenging landscapes has never been explicitly studied. Horses are known to have been traded along the Silk Roads; however, extensive movement of horses in connection with other human activities may have obscured the genetic signature of the Silk Roads. To investigate the role of the Silk Roads in shaping the genetic structure of horses in eastern Eurasia, we analysed microsatellite genotyping data from 455 village horses sampled from 17 locations. Using least-cost path methods, we compared the performance of models containing the Silk Roads as corridors for gene flow with models containing single landscape features. We also determined whether the recent isolation of former Soviet Union countries from the rest of Eurasia has affected the genetic structure of our samples. The overall level of genetic differentiation was low, consistent with historically high levels of gene flow across the study region. The spatial genetic structure was characterized by a significant, albeit weak, pattern of isolation by distance across the continent with no evidence for the presence of distinct genetic clusters. Incorporating landscape features considerably improved the fit of the data; however, when we controlled for geographical distance, only the correlation between genetic differentiation and the Silk Roads remained significant, supporting the effectiveness of this ancient trade network in facilitating gene flow across large geographical distances in a topographically complex landscape. © 2013 John Wiley & Sons Ltd.

Detecting New Pedestrian Facilities from VGI Data Sources

NASA Astrophysics Data System (ADS)

Zhong, S.; Xie, Z.

2017-12-01

Pedestrian facility (e.g. footbridge, pedestrian crossing and underground passage) information is an important basic data of location based service (LBS) for pedestrians. However, timely updating pedestrian facility information challenges due to facilities change frequently. Previous pedestrian facility information collecting and updating tasks are mainly completed by highly trained specialized persons. However, this conventional approach has several disadvantages such as high cost, long update cycle and so on. Volunteered Geographic Information (VGI) has proven efficiency to provide new, free and fast growing spatial data. Pedestrian trajectory, which can be seen as measurements of real pedestrian road, is one of the most valuable information of VGI data. Although the accuracy of the trajectories is not too high, due to the large number of measurements, an improvement of quality of the road information can be achieved. Thus, we develop a method for detecting new pedestrian facilities based on the current road network and pedestrian trajectories. Specifically, 1) by analyzing speed, distance and direction, those outliers of pedestrian trajectories are removed, 2) a road network matching algorithm is developed for eliminating redundant trajectories, and 3) a space-time cluster algorithm is adopted for detecting new walking facilities. The performance of the method is evaluated with a series of experiments conducted on a part of the road network of Heifei and a large number of real pedestrian trajectories, and verified the results by using Tencent Street map. The results show that the proposed method is able to detecting new pedestrian facilities from VGI data accurately. We believe that the proposed method provides an alternative way for general road data acquisition, and can improve the quality of LBS for pedestrians.

Runoff thresholds and land-to-marine ecosystem connectivity in a dry tropical setting: St. John, US Virgin Islands

NASA Astrophysics Data System (ADS)

Ramos-Scharron, C. E.; LaFevor, M. C.; Roy, J.

2017-12-01

Developing a conceptually sound yet practical understanding of runoff and sediment delivery from human occupied lands to tropical ocean waters still represents a pivotal need of coral reef management worldwide. In the dry tropical and ephemeral streamflow setting that typifies the small watersheds ( 1s km2) draining the US Virgin Islands, changes in hydrologic and sediment delivery dynamics provoked by unsurfaced road networks represent a major threat to coral reefs and other sensitive marine ecosystems. Through a combined empirical and modeling approach, this study evaluates how road building and associated stormflow restoration strategies affect rainfall thresholds for runoff generation at varying spatial scales and their impact on land-to-sea connectivity. Rainfall thresholds and runoff coefficients for precipitation excess on unpaved roads are 2-3 mm and 22-30% (respectively) or a full order of magnitude different from those for undisturbed hillslopes and watersheds. Here we discuss the use of a `volume-to-breakthrough' inspired index to predict the potential of road runoff to reach downslope portions of the watershed and the coastline as runon. The index integrates the effects of storm-by-storm runoff accumulation for every road drainage point with its flow distance to specific locations along the stream network. While large runoff volumes and short flow distances imply a relatively high connectivity potential, small volumes and long distances are associated to low delivery potential. The index has proven able to discern observed runoff responses under a variety of road-stream network scenarios and rainfall conditions. These results enhance our understanding of ephemeral stream hydrology and are serving to improve coral reef management strategies throughout the Northeastern Caribbean.

The Physics of Traffic Congestion and Road Pricing in Transportation Planning

NASA Astrophysics Data System (ADS)

Levinson, David

2010-03-01

This presentation develops congestion theory and congestion pricing theory from its micro- foundations, the interaction of two or more vehicles. Using game theory, with a two- player game it is shown that the emergence of congestion depends on the players' relative valuations of early arrival, late arrival, and journey delay. Congestion pricing can be used as a cooperation mechanism to minimize total costs (if returned to the players). The analysis is then extended to the case of the three- player game, which illustrates congestion as a negative externality imposed on players who do not themselves contribute to it. A multi-agent model of travelers competing to utilize a roadway in time and space is presented. To realize the spillover effect among travelers, N-player games are constructed in which the strategy set includes N+1 strategies. We solve the N-player game (for N = 7) and find Nash equilibria if they exist. This model is compared to the bottleneck model. The results of numerical simulation show that the two models yield identical results in terms of lowest total costs and marginal costs when a social optimum exists. Moving from temporal dynamics to spatial complexity, using consistent agent- based techniques, we model the decision-making processes of users and infrastructure owner/operators to explore the welfare consequence of price competition, capacity choice, and product differentiation on congested transportation networks. Component models include: (1) An agent-based travel demand model wherein each traveler has learning capabilities and unique characteristics (e.g. value of time); (2) Econometric facility provision cost models; and (3) Representations of road authorities making pricing and capacity decisions. Different from small-network equilibrium models in prior literature, this agent- based model is applicable to pricing and investment analyses on large complex networks. The subsequent economic analysis focuses on the source, evolution, measurement, and impact of product differentiation with heterogeneous users on a mixed ownership network (with tolled and untolled roads). Two types of product differentiation in the presence of toll roads, path differentiation and space differentiation, are defined and measured for a base case and several variants with different types of price and capacity competition and with various degrees of user heterogeneity. The findings favor a fixed-rate road pricing policy compared to complete pricing freedom on toll roads. It is also shown that the relationship between net social benefit and user heterogeneity is not monotonic on a complex network with toll roads.

Intersection delay estimation from floating car data via principal curves: a case study on Beijing's road network

NASA Astrophysics Data System (ADS)

Liu, Xiliang; Lu, Feng; Zhang, Hengcai; Qiu, Peiyuan

2013-06-01

It is a pressing task to estimate the real-time travel time on road networks reliably in big cities, even though floating car data has been widely used to reflect the real traffic. Currently floating car data are mainly used to estimate the real-time traffic conditions on road segments, and has done little for turn delay estimation. However, turn delays on road intersections contribute significantly to the overall travel time on road networks in modern cities. In this paper, we present a technical framework to calculate the turn delays on road networks with float car data. First, the original floating car data collected with GPS equipped taxies was cleaned and matched to a street map with a distributed system based on Hadoop and MongoDB. Secondly, the refined trajectory data set was distributed among 96 time intervals (from 0: 00 to 23: 59). All of the intersections where the trajectories passed were connected with the trajectory segments, and constituted an experiment sample, while the intersections on arterial streets were specially selected to form another experiment sample. Thirdly, a principal curve-based algorithm was presented to estimate the turn delays at the given intersections. The algorithm argued is not only statistically fitted the real traffic conditions, but also is insensitive to data sparseness and missing data problems, which currently are almost inevitable with the widely used floating car data collecting technology. We adopted the floating car data collected from March to June in Beijing city in 2011, which contains more than 2.6 million trajectories generated from about 20000 GPS-equipped taxicabs and accounts for about 600 GB in data volume. The result shows the principal curve based algorithm we presented takes precedence over traditional methods, such as mean and median based approaches, and holds a higher estimation accuracy (about 10%-15% higher in RMSE), as well as reflecting the changing trend of traffic congestion. With the estimation result for the travel delay at intersections, we analyzed the spatio-temporal distribution of turn delays in three time scenarios (0: 00-0: 15, 8: 15-8: 30 and 12: 00-12: 15). It indicates that during one's single trip in Beijing, average 60% of the travel time on the road networks is wasted on the intersections, and this situation is even worse in daytime. Although the 400 main intersections take only 2.7% of all the intersections, they occupy about 18% travel time.

Genes under weaker stabilizing selection increase network evolvability and rapid regulatory adaptation to an environmental shift.

PubMed

Laarits, T; Bordalo, P; Lemos, B

2016-08-01

Regulatory networks play a central role in the modulation of gene expression, the control of cellular differentiation, and the emergence of complex phenotypes. Regulatory networks could constrain or facilitate evolutionary adaptation in gene expression levels. Here, we model the adaptation of regulatory networks and gene expression levels to a shift in the environment that alters the optimal expression level of a single gene. Our analyses show signatures of natural selection on regulatory networks that both constrain and facilitate rapid evolution of gene expression level towards new optima. The analyses are interpreted from the standpoint of neutral expectations and illustrate the challenge to making inferences about network adaptation. Furthermore, we examine the consequence of variable stabilizing selection across genes on the strength and direction of interactions in regulatory networks and in their subsequent adaptation. We observe that directional selection on a highly constrained gene previously under strong stabilizing selection was more efficient when the gene was embedded within a network of partners under relaxed stabilizing selection pressure. The observation leads to the expectation that evolutionarily resilient regulatory networks will contain optimal ratios of genes whose expression is under weak and strong stabilizing selection. Altogether, our results suggest that the variable strengths of stabilizing selection across genes within regulatory networks might itself contribute to the long-term adaptation of complex phenotypes. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Direction based Hazard Routing Protocol (DHRP) for disseminating road hazard information using road side infrastructures in VANETs.

PubMed

Berlin, M A; Anand, Sheila

2014-01-01

This paper presents Direction based Hazard Routing Protocol (DHRP) for disseminating information about fixed road hazards such as road blocks, tree fall, boulders on road, snow pile up, landslide, road maintenance work and other obstacles to the vehicles approaching the hazardous location. The proposed work focuses on dissemination of hazard messages on highways with sparse traffic. The vehicle coming across the hazard would report the presence of the hazard. It is proposed to use Road Side fixed infrastructure Units for reliable and timely delivery of hazard messages to vehicles. The vehicles can then take appropriate safety action to avoid the hazardous location. The proposed protocol has been implemented and tested using SUMO simulator to generate road traffic and NS 2.33 network simulator to analyze the performance of DHRP. The performance of the proposed protocol was also compared with simple flooding protocol and the results are presented.

View to the southwest of the antenna array, note the ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

View to the southwest of the antenna array, note the site fence in the foreground - Over-the-Horizon Backscatter Radar Network, Christmas Valley Radar Site Transmit Sector Four Antenna Array, On unnamed road west of Lost Forest Road, Christmas Valley, Lake County, OR

Pilot project for a hybrid road-flooding forecasting system on Squaw Creek.

DOT National Transportation Integrated Search

2014-09-01

A network of 25 sonic stage sensors were deployed in the Squaw Creek basin upstream from Ames Iowa to determine : if the state-of-the-art distributed hydrological model CUENCAS can produce reliable information for all road crossings : including those...

Impacts of a road network on a semiarid grassland

USDA-ARS?s Scientific Manuscript database

An unprecedented amount of road, trail, and other infrastructure development is currently occurring or planned for many arid and semiarid ecosystems nationally. This is due to a variety of factors, including energy resources development (oil, gas, wind, solar, coaled methane, and others), recreation...

LiteNet: Lightweight Neural Network for Detecting Arrhythmias at Resource-Constrained Mobile Devices.

PubMed

He, Ziyang; Zhang, Xiaoqing; Cao, Yangjie; Liu, Zhi; Zhang, Bo; Wang, Xiaoyan

2018-04-17

By running applications and services closer to the user, edge processing provides many advantages, such as short response time and reduced network traffic. Deep-learning based algorithms provide significantly better performances than traditional algorithms in many fields but demand more resources, such as higher computational power and more memory. Hence, designing deep learning algorithms that are more suitable for resource-constrained mobile devices is vital. In this paper, we build a lightweight neural network, termed LiteNet which uses a deep learning algorithm design to diagnose arrhythmias, as an example to show how we design deep learning schemes for resource-constrained mobile devices. Compare to other deep learning models with an equivalent accuracy, LiteNet has several advantages. It requires less memory, incurs lower computational cost, and is more feasible for deployment on resource-constrained mobile devices. It can be trained faster than other neural network algorithms and requires less communication across different processing units during distributed training. It uses filters of heterogeneous size in a convolutional layer, which contributes to the generation of various feature maps. The algorithm was tested using the MIT-BIH electrocardiogram (ECG) arrhythmia database; the results showed that LiteNet outperforms comparable schemes in diagnosing arrhythmias, and in its feasibility for use at the mobile devices.

LiteNet: Lightweight Neural Network for Detecting Arrhythmias at Resource-Constrained Mobile Devices

PubMed Central

Zhang, Xiaoqing; Cao, Yangjie; Liu, Zhi; Zhang, Bo; Wang, Xiaoyan

2018-01-01

By running applications and services closer to the user, edge processing provides many advantages, such as short response time and reduced network traffic. Deep-learning based algorithms provide significantly better performances than traditional algorithms in many fields but demand more resources, such as higher computational power and more memory. Hence, designing deep learning algorithms that are more suitable for resource-constrained mobile devices is vital. In this paper, we build a lightweight neural network, termed LiteNet which uses a deep learning algorithm design to diagnose arrhythmias, as an example to show how we design deep learning schemes for resource-constrained mobile devices. Compare to other deep learning models with an equivalent accuracy, LiteNet has several advantages. It requires less memory, incurs lower computational cost, and is more feasible for deployment on resource-constrained mobile devices. It can be trained faster than other neural network algorithms and requires less communication across different processing units during distributed training. It uses filters of heterogeneous size in a convolutional layer, which contributes to the generation of various feature maps. The algorithm was tested using the MIT-BIH electrocardiogram (ECG) arrhythmia database; the results showed that LiteNet outperforms comparable schemes in diagnosing arrhythmias, and in its feasibility for use at the mobile devices. PMID:29673171

Nomadic ecology shaped the highland geography of Asia's Silk Roads.

PubMed

Frachetti, Michael D; Smith, C Evan; Traub, Cynthia M; Williams, Tim

2017-03-08

There are many unanswered questions about the evolution of the ancient 'Silk Roads' across Asia. This is especially the case in their mountainous stretches, where harsh terrain is seen as an impediment to travel. Considering the ecology and mobility of inner Asian mountain pastoralists, we use 'flow accumulation' modelling to calculate the annual routes of nomadic societies (from 750 m to 4,000 m elevation). Aggregating 500 iterations of the model reveals a high-resolution flow network that simulates how centuries of seasonal nomadic herding could shape discrete routes of connectivity across the mountains of Asia. We then compare the locations of known high-elevation Silk Road sites with the geography of these optimized herding flows, and find a significant correspondence in mountainous regions. Thus, we argue that highland Silk Road networks (from 750 m to 4,000 m) emerged slowly in relation to long-established mobility patterns of nomadic herders in the mountains of inner Asia.

Road Risk Modeling and Cloud-Aided Safety-Based Route Planning.

PubMed

Li, Zhaojian; Kolmanovsky, Ilya; Atkins, Ella; Lu, Jianbo; Filev, Dimitar P; Michelini, John

2016-11-01

This paper presents a safety-based route planner that exploits vehicle-to-cloud-to-vehicle (V2C2V) connectivity. Time and road risk index (RRI) are considered as metrics to be balanced based on user preference. To evaluate road segment risk, a road and accident database from the highway safety information system is mined with a hybrid neural network model to predict RRI. Real-time factors such as time of day, day of the week, and weather are included as correction factors to the static RRI prediction. With real-time RRI and expected travel time, route planning is formulated as a multiobjective network flow problem and further reduced to a mixed-integer programming problem. A V2C2V implementation of our safety-based route planning approach is proposed to facilitate access to real-time information and computing resources. A real-world case study, route planning through the city of Columbus, Ohio, is presented. Several scenarios illustrate how the "best" route can be adjusted to favor time versus safety metrics.

Network-optimized congestion pricing : a parable, model and algorithm

DOT National Transportation Integrated Search

1995-05-31

This paper recites a parable, formulates a model and devises an algorithm for optimizing tolls on a road network. Such tolls induce an equilibrium traffic flow that is at once system-optimal and user-optimal. The parable introduces the network-wide c...

Data fusion for target tracking and classification with wireless sensor network

NASA Astrophysics Data System (ADS)

Pannetier, Benjamin; Doumerc, Robin; Moras, Julien; Dezert, Jean; Canevet, Loic

2016-10-01

In this paper, we address the problem of multiple ground target tracking and classification with information obtained from a unattended wireless sensor network. A multiple target tracking (MTT) algorithm, taking into account road and vegetation information, is proposed based on a centralized architecture. One of the key issue is how to adapt classical MTT approach to satisfy embedded processing. Based on track statistics, the classification algorithm uses estimated location, velocity and acceleration to help to classify targets. The algorithms enables tracking human and vehicles driving both on and off road. We integrate road or trail width and vegetation cover, as constraints in target motion models to improve performance of tracking under constraint with classification fusion. Our algorithm also presents different dynamic models, to palliate the maneuvers of targets. The tracking and classification algorithms are integrated into an operational platform (the fusion node). In order to handle realistic ground target tracking scenarios, we use an autonomous smart computer deposited in the surveillance area. After the calibration step of the heterogeneous sensor network, our system is able to handle real data from a wireless ground sensor network. The performance of system is evaluated in a real exercise for intelligence operation ("hunter hunt" scenario).

Critical Robotic Lunar Missions

NASA Astrophysics Data System (ADS)

Plescia, J. B.

2018-04-01

Perhaps the most critical missions to understanding lunar history are in situ dating and network missions. These would constrain the volcanic and thermal history and interior structure. These data would better constrain lunar evolution models.

Effects of logging on roadless space in intact forest landscapes of the Congo Basin.

PubMed

Kleinschroth, Fritz; Healey, John R; Gourlet-Fleury, Sylvie; Mortier, Frédéric; Stoica, Radu S

2017-04-01

Forest degradation in the tropics is often associated with roads built for selective logging. The protection of intact forest landscapes (IFL) that are not accessible by roads is high on the biodiversity conservation agenda and a challenge for logging concessions certified by the Forest Stewardship Council (FSC). A frequently advocated conservation objective is to maximize the retention of roadless space, a concept that is based on distance to the nearest road from any point. We developed a novel use of the empty-space function - a general statistical tool based on stochastic geometry and random sets theory - to calculate roadless space in a part of the Congo Basin where road networks have been expanding rapidly. We compared the temporal development of roadless space in certified and uncertified logging concessions inside and outside areas declared IFL in 2000. Inside IFLs, road-network expansion led to a decrease in roadless space by more than half from 1999 to 2007. After 2007, loss leveled out in most areas to close to 0 due to an equilibrium between newly built roads and abandoned roads that became revegetated. However, concessions in IFL certified by FSC since around 2007 continuously lost roadless space and reached a level comparable to all other concessions. Only national parks remained mostly roadless. We recommend that forest-management policies make the preservation of large connected forest areas a top priority by effectively monitoring - and limiting - the occupation of space by roads that are permanently accessible. © 2016 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

GIS as a tool for efficient management of transport streams

NASA Astrophysics Data System (ADS)

Zatserkovnyi, V. I.; Kobrin, O. V.

2015-10-01

The transport network, which is an ideal object for the automation and the increase of efficiency using geographic information systems (GIS), is considered. The transport problems, which have a lot of mathematical models of the traffic flow for their solution, are enumerated. GIS analysis tools that allow one to build optimal routes in the real road network with its capabilities and limitations are presented. They can solve the extremely important problem of modern Ukraine - the rapid increase of the number of cars and the glut of road network vehicles. The intelligent transport systems, which are created and developed on the basis of GPS, GIS, modern communications and telecommunications facilities, are considered.

­­Estimating Forest Management Units from Road Network Maps in the Southeastern U.S.

NASA Astrophysics Data System (ADS)

Yang, D.; Hall, J.; Fu, C. S.; Binford, M. W.

2015-12-01

The most important factor affecting forest structure and function is the type of management undertaken in forest stands. Owners manage forests using appropriately sized areas to meet management objectives, which include economic return, sustainability, recreation, or esthetic enjoyment. Thus, the socio-environmental unit of study for forests should be the management unit. To study the ecological effects of different kinds of management activities, we must identify individual management units. Road networks, which provide access for human activities, are widely used in managing forests in the southeastern U.S. Coastal Plain and Piedmont (SEUS). Our research question in this study is: How can we identify individual forest management units in an entire region? To answer it, we hypothesize that the road network defines management units on the landscape. Road-caused canopy openings are not always captured by satellite sensors, so it is difficult to delineate ecologically relevant patches based only on remote sensing data. We used a reliable, accurate and freely available road network data, OpenStreetMap (OSM), and the National Land Cover Database (NLCD) to delineate management units in a section of the SEUS defined by Landsat Wprldwide Reference System (WRS) II footprint path 17 row 39. The spatial frequency distributions of forest management units indicate that while units < 0.5 Ha comprised 64% of the units, these small units covered only 0.98% of the total forest area. Management units ≥ 0.5 Ha ranged from 0.5 to 160,770 Ha (the Okefenokee National Wildlife Refuge). We compared the size-frequency distributions of management units with four independently derived management types: production, ecological, preservation, and passive management. Preservation and production management had the largest units, at 40.5 ± 2196.7 (s.d.) and 41.3 ± 273.5 Ha, respectively. Ecological and passive averaged about half as large at 19.2 ± 91.5 and 22.4 ± 96.0 Ha, respectively. This result supports the hypothesis that the road network defines management units in SEUS. If this way of delineating management units stands under further testing, it will provide a way of subdividing the landscape so that we can study the effects of different management on forest ecosystems.

A one-layer recurrent neural network for constrained pseudoconvex optimization and its application for dynamic portfolio optimization.

PubMed

Liu, Qingshan; Guo, Zhishan; Wang, Jun

2012-02-01

In this paper, a one-layer recurrent neural network is proposed for solving pseudoconvex optimization problems subject to linear equality and bound constraints. Compared with the existing neural networks for optimization (e.g., the projection neural networks), the proposed neural network is capable of solving more general pseudoconvex optimization problems with equality and bound constraints. Moreover, it is capable of solving constrained fractional programming problems as a special case. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed as long as the designed parameters in the model are larger than the derived lower bounds. Numerical examples with simulation results illustrate the effectiveness and characteristics of the proposed neural network. In addition, an application for dynamic portfolio optimization is discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.

75 FR 82075 - Notice of Quarterly Report (July 1, 2010-September 30, 2010)

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-29

... Project. transportation to annual daily traffic)-- increase tourism Efate: Ring Road. and business Traffic... tourism pottery workshops. and artisan Construction and sectors. rehabilitation of Fez Medina Sites... through investments in the road network. Rural Land Governance Project.... $59,934,615 Increase investment...

The US Strategic Logistics Plan In The CBI Theater And Its Contemporary Significance

DTIC Science & Technology

2016-05-26

SUBJECT TERMS CBI Theater, Logistics, Lend-Lease Aid, LOC Network, Ledo Road, Burma Road, The Hump, AMMISCA 16. SECURITY CLASSIFICATION OF: a...19 Stilwell versus Chennault………………………………………………….………………………….......26 Efficiency of the LOC Network... LOC Line of Communication NATO North Atlantic Treaty Organization SLOC Sea Line of Communication SME Subject Matter Expert SOS Services of Supply SPOD

Road safety and simulation conferences: an interdisciplinary network for safer roads.

PubMed

Benedetto, Andrea; Calvi, Alessandro

2014-06-01

From 23rd to 25th October 2013 more than 300 researchers attended the 4th International Conference on Road Safety and Simulation (RSS 2013) in Rome, Italy, hosted by the Inter Universities Research Centre for Road Safety (CRISS) at the Department of Engineering of Roma Tre University. The aim of the Conference was to create a common interdisciplinary arena for researchers and professionals involved in road safety, facilitate the exchange of know-how and progress in the last advanced techniques, methods and tools and their applications to safety analysis. This special issue highlights some of the research presented at the Conference. Copyright © 2014 Elsevier B.V. All rights reserved.

Indirect economic impact of landslide hazards by disruption to national road transportation networks; Scotland, United Kingdom.

NASA Astrophysics Data System (ADS)

Postance, Benjamin; Hillier, John; Dijkstra, Tom; Dixon, Neil

2016-04-01

The failure of engineered or natural slopes which support or are adjacent to transportation systems often inflicts costly direct physical damage and indirect system disruption. The consequences and severity of indirect impacts vary according to which links, nodes or network facilities are physically disrupted. Moreover, it is often the case that multiple slope failure disruptions are triggered simultaneously following prolonged or intense precipitation events due to a degree of local homogeneity of slope characteristics and materials. This study investigates the application of national commuter statistics and network agent simulation to evaluate indirect impacts of landslide events disrupting the Scottish trunk road transportation network (UK). Previous studies often employ shortest pathway analysis whereas agent simulation has received relatively little attention. British Geological Survey GeoSure landslide susceptibility data is used to select 35 susceptible trunk road segments by means of neighbouring total area at risk. For each of the candidate 35 segments the network and zonal variation in travel time is calculated for a single day of disruption, economic impact is approximated using established governmental and industry transport planning and appraisal values. The results highlight that a number of trunk road segments incur indirect economic losses in the order of tens of thousands of pounds for each day of closure. Calculated losses at the A83 Rest and Be Thankful are 50% greater than previous estimates at £75 thousand per day of closure. Also highlighted are events in which economic impact is relatively minor, yet concentrating on particular communities that can become substantially isolated as a consequence of a single event. The findings of this study are of interest and support wider investigations exploring cost considerations for decision makers and mitigation strategies, in addition to identifying network topological and demand indicators conducive to high indirect economic cost events.

An Authentication and Key Management Mechanism for Resource Constrained Devices in IEEE 802.11-based IoT Access Networks.

PubMed

Kim, Ki-Wook; Han, Youn-Hee; Min, Sung-Gi

2017-09-21

Many Internet of Things (IoT) services utilize an IoT access network to connect small devices with remote servers. They can share an access network with standard communication technology, such as IEEE 802.11ah. However, an authentication and key management (AKM) mechanism for resource constrained IoT devices using IEEE 802.11ah has not been proposed as yet. We therefore propose a new AKM mechanism for an IoT access network, which is based on IEEE 802.11 key management with the IEEE 802.1X authentication mechanism. The proposed AKM mechanism does not require any pre-configured security information between the access network domain and the IoT service domain. It considers the resource constraints of IoT devices, allowing IoT devices to delegate the burden of AKM processes to a powerful agent. The agent has sufficient power to support various authentication methods for the access point, and it performs cryptographic functions for the IoT devices. Performance analysis shows that the proposed mechanism greatly reduces computation costs, network costs, and memory usage of the resource-constrained IoT device as compared to the existing IEEE 802.11 Key Management with the IEEE 802.1X authentication mechanism.

An Authentication and Key Management Mechanism for Resource Constrained Devices in IEEE 802.11-based IoT Access Networks

PubMed Central

Han, Youn-Hee; Min, Sung-Gi

2017-01-01

Many Internet of Things (IoT) services utilize an IoT access network to connect small devices with remote servers. They can share an access network with standard communication technology, such as IEEE 802.11ah. However, an authentication and key management (AKM) mechanism for resource constrained IoT devices using IEEE 802.11ah has not been proposed as yet. We therefore propose a new AKM mechanism for an IoT access network, which is based on IEEE 802.11 key management with the IEEE 802.1X authentication mechanism. The proposed AKM mechanism does not require any pre-configured security information between the access network domain and the IoT service domain. It considers the resource constraints of IoT devices, allowing IoT devices to delegate the burden of AKM processes to a powerful agent. The agent has sufficient power to support various authentication methods for the access point, and it performs cryptographic functions for the IoT devices. Performance analysis shows that the proposed mechanism greatly reduces computation costs, network costs, and memory usage of the resource-constrained IoT device as compared to the existing IEEE 802.11 Key Management with the IEEE 802.1X authentication mechanism. PMID:28934152

Safety performance functions for intersections : final report, December 2009.

DOT National Transportation Integrated Search

2009-12-01

Road safety management activities include screening the network for sites with a potential for safety improvement (Network : Screening), diagnosing safety problems at specific sites, and evaluating the safety effectiveness of implemented : countermea...

The Immunological Genome Project: networks of gene expression in immune cells.

PubMed

Heng, Tracy S P; Painter, Michio W

2008-10-01

The Immunological Genome Project combines immunology and computational biology laboratories in an effort to establish a complete 'road map' of gene-expression and regulatory networks in all immune cells.

76 FR 19131 - Notice of Quarterly Report (October 1, 2010-December 31, 2010)

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-06

...: Ring tourism and Road. business Traffic Volume development. (average annual daily traffic)--Santo: East...,083,742 Average revenue of SME added to tourism pottery workshops. and artisan sectors. Construction... road network. Rural Land Governance Project.. $59,934,615 Increase $6,348,245 TBD. investment in land...

75 FR 56580 - Notice of Quarterly Report (April 1, 2010-June 30, 2010)

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-16

... annual daily traffic)-- increase tourism Efate: Ring Road. and business Traffic Volume (average... Average revenue of SME added to tourism pottery workshops. and artisan Construction and sectors... in the road network. Rural Land Governance Project... 60,392,771 Increase investment 2,185,845 TBD...

General view of Sector Four Compound, looking north. Antenna Array ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

General view of Sector Four Compound, looking north. Antenna Array is in background, behind Communications Antennas, Receiver Building, and Water Storage Tank - Over-the-Horizon Backscatter Radar Network, Tulelake Radar Site Receive Sector Four Antenna Array, Unnamed Road West of Double Head Road, Tulelake, Siskiyou County, CA

The New Burma Road(s): How a Networked System of Roads will Best Orient Myanmar towards Economic Success

DTIC Science & Technology

2014-10-30

figure calculated by reviewing a country’s performance in a number of factors such as customs clearance efficiency and tracking capabilities. 76...the transportation sector, marginal costs are calculated based on the total costs per one additional mile of a particular transportation mode. For...Myanmar: KPMG Advisory (Myanmar) Limited, 2013. Kubo , Koji. “Myanmar’s Two Decades of Partial Transition to a Market Economy: A Negative

Application of the network robustness index to identifying critical road-network links in Chittenden County, Vermont.

DOT National Transportation Integrated Search

2010-06-01

The purpose of this project is to conduct a pilot application of the Network : Robustness Index (NRI) for the Chittenden County Regional Transportation Model. : Using the results, improvements to the method to increase its effectiveness for more : wi...

Modeling and simulation of emergent behavior in transportation infrastructure restoration

USGS Publications Warehouse

Ojha, Akhilesh; Corns, Steven; Shoberg, Thomas G.; Qin, Ruwen; Long, Suzanna K.

2018-01-01

The objective of this chapter is to create a methodology to model the emergent behavior during a disruption in the transportation system and that calculates economic losses due to such a disruption, and to understand how an extreme event affects the road transportation network. The chapter discusses a system dynamics approach which is used to model the transportation road infrastructure system to evaluate the different factors that render road segments inoperable and calculate economic consequences of such inoperability. System dynamics models have been integrated with business process simulation model to evaluate, design, and optimize the business process. The chapter also explains how different factors affect the road capacity. After identifying the various factors affecting the available road capacity, a causal loop diagram (CLD) is created to visually represent the causes leading to a change in the available road capacity and the effects on travel costs when the available road capacity changes.

Assessment of ecological passages along road networks within the Mediterranean forest using GIS-based multi criteria evaluation approach.

PubMed

Gülci, Sercan; Akay, Abdullah Emin

2015-12-01

Major roads cause barrier effect and fragmentation on wildlife habitats that are suitable places for feeding, mating, socializing, and hiding. Due to wildlife collisions (Wc), human-wildlife conflicts result in lost lives and loss of biodiversity. Geographical information system (GIS)-based multi criteria evaluation (MCE) methods have been successfully used in short-term planning of road networks considering wild animals. Recently, wildlife passages have been effectively utilized as road engineering structures provide quick and certain solutions for traffic safety and wildlife conservation problems. GIS-based MCE methods provide decision makers with optimum location for ecological passages based on habitat suitability models (HSMs) that classify the areas based on ecological requirements of target species. In this study, ecological passages along Motorway 52 within forested areas in Mediterranean city of Osmaniye in Turkey were evaluated. Firstly, HSM coupled with nine eco-geographic decision variables were developed based on ecological requirements of roe deer (Capreolus capreolus) that were chosen as target species. Then specified decision variables were evaluated using GIS-based weighted linear combination (WLC) method to estimate movement corridors and mitigation points along the motorway. In the solution process, two linkage nodes were evaluated for eco-passages which were determined based on the least-cost movement corridor intersecting with the motorway. One of the passages was identified as a natural wildlife overpass while the other was suggested as underpass construction. The results indicated that computer-based models provide accurate and quick solutions for positioning ecological passages to reduce environmental effects of road networks on wild animals.

Cooperation-Induced Topological Complexity: A Promising Road to Fault Tolerance and Hebbian Learning

DTIC Science & Technology

2012-03-16

topological complexity a way to compare the efficiency of a scale-free network to the random network of Erdos and Renyi . All this is extensively dis- cussed in...an excellent review paper byArenas et al. (2008) showing very interesting comparisons of Erdos– Renyi networks and scale- free networks as a function

Statistical Analysis of Bus Networks in India

PubMed Central

2016-01-01

In this paper, we model the bus networks of six major Indian cities as graphs in L-space, and evaluate their various statistical properties. While airline and railway networks have been extensively studied, a comprehensive study on the structure and growth of bus networks is lacking. In India, where bus transport plays an important role in day-to-day commutation, it is of significant interest to analyze its topological structure and answer basic questions on its evolution, growth, robustness and resiliency. Although the common feature of small-world property is observed, our analysis reveals a wide spectrum of network topologies arising due to significant variation in the degree-distribution patterns in the networks. We also observe that these networks although, robust and resilient to random attacks are particularly degree-sensitive. Unlike real-world networks, such as Internet, WWW and airline, that are virtual, bus networks are physically constrained. Our findings therefore, throw light on the evolution of such geographically and constrained networks that will help us in designing more efficient bus networks in the future. PMID:27992590

The importance of artificial wetlands for birds: A case study from Cyprus

PubMed Central

Giosa, Efthymia; Zotos, Savvas

2018-01-01

The degradation of natural wetlands has significant effects on the ecosystem services they provide and the biodiversity they sustain. Under certain conditions, these negative effects can be mitigated by the presence of artificial wetlands. However, the conservation value of artificial wetlands needs to be explored further. In addition, it is unclear how certain anthropogenic variables, such as road networks and hunting reserves (i.e., areas where hunting of birds is prohibited) affect biodiversity in both artificial and natural wetlands. Here, we use data from thirteen artificial and six natural wetlands in Cyprus, to assess their similarities in bird species diversity and composition, and to quantify the relationship between species diversity and the density of road networks, hunting reserves, wetland size, and wetland depth. We found that while on average natural wetlands have more species and support higher abundances, certain artificial wetlands have the potential to support similarly diverse communities. Overall, regardless of the type, larger wetlands, with shallower waters tend to be more biodiverse. The same is true for wetlands surrounded by a higher percentage of hunting reserves and a lower density of road networks, albeit the effect of road networks was weaker. We conclude, from our results, that although the conservation value of natural wetlands is higher, artificial wetlands have the potential to play a complimentary role in the conservation of bird communities, assuming those wetlands have the right characteristics (e.g., in terms of size and depth) and assuming that the disturbances resulting from high-impact human-activities (e.g., hunting) are minimized. PMID:29746545

Landslide susceptibility and risk assessment: specificities for road networks

NASA Astrophysics Data System (ADS)

Pellicani, Roberta; Argentiero, Ilenia; Parisi, Alessandro; Spilotro, Giuseppe

2017-04-01

A regional-scale assessment of landslide susceptibility and risk along the main road corridors crossing the provincial territory of Matera (Basilicata Region, Southern Italy) was carried out. The entire provincial road network extends for about 1,320 km through a territory, of which represents the main connection infrastructure among thirty-one municipalities due to the lack of an efficient integrated transportation system through the whole regional territory. For this reason, the strategic importance of these roads consists in their uniqueness in connecting every urban center with the socio-economic surrounding context. These roads and their vehicular traffic are continuously exposed to instability processes (about the 40% of the total length is disrupted by landslides), characterized both by high intensity and low frequency and by low intensity and high frequency. This last typology, consisting in small shallow landslides, is particularly hazardous for the roads since it is widespread along the road network, its occurrence is connected to rainfalls and determines high vulnerability conditions for the road in terms of interruption of vehicular traffic. A GIS-based heuristic-bivariate statistical predictive model was performed to assess and map the landslide susceptibility in the study area, by using a polynomial function of eight predisposing factors, weighted according to their influence on the landslide phenomena, recognized and collected in an inventory. Susceptibility associated to small shallow phenomena was assessed by using a polynomial function of specific factors, such as slope angle and aspect, lithological outcrops, rainfalls, etc. In absence of detailed input data, the spatial distribution of landslide risk along the road corridors was assessed and mapped using a qualitative hazard-consequence matrix approach, by which risk is obtained by combining hazard categories with consequence classes pairwise in a two-dimensional table or matrix. Landslide hazard, which is a function of the return time, due to the lack of temporal data, was evaluated as a function of the landslide intensity (velocity and areal extent) and susceptibility. The direct consequences of instability on the roads were defined by combining exposure and vulnerability in a matrix. Exposure was evaluated in terms of amount of traffic, which was calculated along each road stretch, connecting two or more urban areas, as a function of the average of population of each centers. Vulnerability, which expresses the degree of damage, was assessed in function of the presence of criticalities along roads, which were ranked according to the severity of damages and type of performed reparation works. The consequences, combined with the hazard levels, allowed to assess the landslide risk, classified in low, medium and high levels. The risk map highlighted that about the 30% (392 km) of the examined road corridors is affected by high risk levels. The comparison between the risk map and the landslide inventory recognized along roads has also revealed that the 49.5% of landslides affects sections where the risk was evaluated high. The obtained risk classification of the roads represents a support for decision making and allows to identify the priorities for designing appropriate landslide mitigation plans.

SENTRE and TREND attenuator field installations

DOT National Transportation Integrated Search

1990-02-01

Arizona's canal network is extensive and necessitates the existence of many short bridges on the highway network. The necessity for maintaining access to adjacent canal roads dictates that any barrier installation intended to shield errant vehicles f...

New Abstraction Networks and a New Visualization Tool in Support of Auditing the SNOMED CT Content

PubMed Central

Geller, James; Ochs, Christopher; Perl, Yehoshua; Xu, Junchuan

2012-01-01

Medical terminologies are large and complex. Frequently, errors are hidden in this complexity. Our objective is to find such errors, which can be aided by deriving abstraction networks from a large terminology. Abstraction networks preserve important features but eliminate many minor details, which are often not useful for identifying errors. Providing visualizations for such abstraction networks aids auditors by allowing them to quickly focus on elements of interest within a terminology. Previously we introduced area taxonomies and partial area taxonomies for SNOMED CT. In this paper, two advanced, novel kinds of abstraction networks, the relationship-constrained partial area subtaxonomy and the root-constrained partial area subtaxonomy are defined and their benefits are demonstrated. We also describe BLUSNO, an innovative software tool for quickly generating and visualizing these SNOMED CT abstraction networks. BLUSNO is a dynamic, interactive system that provides quick access to well organized information about SNOMED CT. PMID:23304293

New abstraction networks and a new visualization tool in support of auditing the SNOMED CT content.

PubMed

Geller, James; Ochs, Christopher; Perl, Yehoshua; Xu, Junchuan

2012-01-01

Medical terminologies are large and complex. Frequently, errors are hidden in this complexity. Our objective is to find such errors, which can be aided by deriving abstraction networks from a large terminology. Abstraction networks preserve important features but eliminate many minor details, which are often not useful for identifying errors. Providing visualizations for such abstraction networks aids auditors by allowing them to quickly focus on elements of interest within a terminology. Previously we introduced area taxonomies and partial area taxonomies for SNOMED CT. In this paper, two advanced, novel kinds of abstraction networks, the relationship-constrained partial area subtaxonomy and the root-constrained partial area subtaxonomy are defined and their benefits are demonstrated. We also describe BLUSNO, an innovative software tool for quickly generating and visualizing these SNOMED CT abstraction networks. BLUSNO is a dynamic, interactive system that provides quick access to well organized information about SNOMED CT.

Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Networks

PubMed Central

Lam, William H. K.; Li, Qingquan

2017-01-01

Travel times in congested urban road networks are highly stochastic. Provision of travel time distribution information, including both mean and variance, can be very useful for travelers to make reliable path choice decisions to ensure higher probability of on-time arrival. To this end, a heterogeneous data fusion method is proposed to estimate travel time distributions by fusing heterogeneous data from point and interval detectors. In the proposed method, link travel time distributions are first estimated from point detector observations. The travel time distributions of links without point detectors are imputed based on their spatial correlations with links that have point detectors. The estimated link travel time distributions are then fused with path travel time distributions obtained from the interval detectors using Dempster-Shafer evidence theory. Based on fused path travel time distribution, an optimization technique is further introduced to update link travel time distributions and their spatial correlations. A case study was performed using real-world data from Hong Kong and showed that the proposed method obtained accurate and robust estimations of link and path travel time distributions in congested road networks. PMID:29210978

Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Networks.

PubMed

Shi, Chaoyang; Chen, Bi Yu; Lam, William H K; Li, Qingquan

2017-12-06

Travel times in congested urban road networks are highly stochastic. Provision of travel time distribution information, including both mean and variance, can be very useful for travelers to make reliable path choice decisions to ensure higher probability of on-time arrival. To this end, a heterogeneous data fusion method is proposed to estimate travel time distributions by fusing heterogeneous data from point and interval detectors. In the proposed method, link travel time distributions are first estimated from point detector observations. The travel time distributions of links without point detectors are imputed based on their spatial correlations with links that have point detectors. The estimated link travel time distributions are then fused with path travel time distributions obtained from the interval detectors using Dempster-Shafer evidence theory. Based on fused path travel time distribution, an optimization technique is further introduced to update link travel time distributions and their spatial correlations. A case study was performed using real-world data from Hong Kong and showed that the proposed method obtained accurate and robust estimations of link and path travel time distributions in congested road networks.

Population Accessibility to Radiotherapy Services in New South Wales Region of Australia: a methodological contribution

NASA Astrophysics Data System (ADS)

Shukla, Nagesh; Wickramasuriya, Rohan; Miller, Andrew; Perez, Pascal

2015-05-01

This paper proposes an integrated modelling process to assess the population accessibility to radiotherapy treatment services in future based on future cancer incidence and road network-based accessibility. Previous research efforts assessed travel distance/time barriers affecting access to cancer treatment services, as well as epidemiological studies that showed that cancer incidence rates vary with population demography. It is established that travel distances to treatment centres and demographic profiles of the accessible regions greatly influence the demand for cancer radiotherapy (RT) services. However, an integrated service planning approach that combines spatially-explicit cancer incidence projections, and the RT services accessibility based on patient road network have never been attempted. This research work presents this novel methodology for the accessibility assessment of RT services and demonstrates its viability by modelling New South Wales (NSW) cancer incidence rates for different age-sex groups based on observed cancer incidence trends; estimating the road network-based access to current NSW treatment centres; and, projecting the demand for RT services in New South Wales, Australia from year 2011 to 2026.

Developing a 3D Road Cadastral System: Comparing Legal Requirements and User Needs

NASA Astrophysics Data System (ADS)

Gristina, S.; Ellul, C.; Scianna, A.

2016-10-01

Road transport has always played an important role in a country's growth and, in order to manage road networks and ensure a high standard of road performance (e.g. durability, efficiency and safety), both public and private road inventories have been implemented using databases and Geographical Information Systems. They enable registering and managing significant amounts of different road information, but to date do not focus on 3D road information, data integration and interoperability. In an increasingly complex 3D urban environment, and in the age of smart cities, however, applications including intelligent transport systems, mobility and traffic management, road maintenance and safety require digital data infrastructures to manage road data: thus new inventories based on integrated 3D road models (queryable, updateable and shareable on line) are required. This paper outlines the first step towards the implementation of 3D GIS-based road inventories. Focusing on the case study of the "Road Cadastre" (the Italian road inventory as established by law), it investigates current limitations and required improvements, and also compares the required data structure imposed by cadastral legislation with real road users' needs. The study aims to: a) determine whether 3D GIS would improve road cadastre (for better management of data through the complete life-cycle infrastructure projects); b) define a conceptual model for a 3D road cadastre for Italy (whose general principles may be extended also to other countries).

A participatory sensing approach to characterize ride quality

NASA Astrophysics Data System (ADS)

Bridgelall, Raj

2014-03-01

Rough roads increase vehicle operation and road maintenance costs. Consequently, transportation agencies spend a significant portion of their budgets on ride-quality characterization to forecast maintenance needs. The ubiquity of smartphones and social media, and the emergence of a connected vehicle environment present lucrative opportunities for cost-reduction and continuous, network-wide, ride-quality characterization. However, there is a lack of models to transform inertial and position information from voluminous data flows into indices that transportation agencies currently use. This work expands on theories of the Road Impact Factor introduced in previous research. The index characterizes road roughness by aggregating connected vehicle data and reporting roughness in direct proportion to the International Roughness Index. Their theoretical relationships are developed, and a case study is presented to compare the relative data quality from an inertial profiler and a regular passenger vehicle. Results demonstrate that the approach is a viable alternative to existing models that require substantially more resources and provide less network coverage. One significant benefit of the participatory sensing approach is that transportation agencies can monitor all network facilities continuously to locate distress symptoms, such as frost heaves, that appear and disappear between ride assessment cycles. Another benefit of the approach is continuous monitoring of all high-risk intersections such as rail grade crossings to better understand the relationship between ride-quality and traffic safety.

Prioritizing Road Treatments using the Geomorphic Roads Analysis and Inventory Package (GRAIP) to Improve Watershed Conditions in the Wall Creek Watershed, Oregon

NASA Astrophysics Data System (ADS)

Day, K. T.; Black, T.; Clifton, C.; Luce, C.; McCune, S.; Nelson, N.

2010-12-01

Wall Creek, tributary to the North Fork John Day River in eastern Oregon, was identified as a priority watershed by the Umatilla National Forest for restoration in 2002. Most streams in this 518 km2 multi-ownership watershed are designated critical habitat for threatened steelhead. Eight streams are listed on the Oregon 303(d) list for elevated temperatures and excess sedimentation. Over 1000 km of public and private roads in the watershed present a major source of potential water quality and habitat impairment. We conducted a watershed-wide inventory of roads using the Geomorphic Roads Analysis and Inventory Package (GRAIP) in 2009 to quantify sediment contributions from roads to streams. GRAIP is a field and GIS-based model developed by the Forest Service Rocky Mountain Research Station and Utah State University that georeferences and quantifies road hydrologic connectivity, sediment production and delivery, mass wasting, and risk of diversion and plugging at stream crossings. Field survey and modeling produced data for 6,473 drainage locations on 726 km of road (most of the publically owned roads) quantifying the location and mass of sediment produced and delivered to streams. Findings indicate a relatively small subset of roads deliver the majority of road-produced fine sediment; 12 percent of the road length delivers 90 percent of the total fine sediment to streams. Overall fine sediment production in the watershed is relatively low (with an estimated background erosion rate of 518,000 kg/yr for the watershed) and sediment produced and delivered from the road system appears to be a modest addition. Road surfaces produce approximately 81,455 kg of fine sediment per year, with 20,976 kg/year delivered to the stream network. Fifty-nine gullies were observed, 41 of which received road runoff. Sixteen road-related landslides were also observed. The excavated volume of these features totals 3,922,000 kg which is equivalent to 175 years of fine sediment delivery at the current rate. These data are being used by the Umatilla National Forest to prioritize road rehabilitation activities including storm risk reduction and road decommissioning, and to move toward an ecologically and economically sustainable road system. The highest sediment-delivering road segments were evaluated in 2010 to prioritize stabilization and storm damage risk reduction projects. Approximately 30 km of hydrologically connected road segments will be proposed for treatments including closure, decommissioning, and stabilization activities. Once complete, these improvements would result in the reduction of about 7,000 kg/year of fine sediment delivered to the fluvial system from the road network, or a third of the total road contribution to stream sedimentation. Methods and results presented are part of federal land management agency involvement in Total Maximum Daily Load development in the John Day Basin. The project is a collaborative effort with funding and support from the Environmental Protection Agency, Bureau of Land Management, and Oregon Department of Environmental Quality.

The Pomona-Rincon Road and Its Place in the Regional Transportation Network

DTIC Science & Technology

1989-10-19

on American soil by diverting north of Pilot Knob (near Yuma in Imperial County) to Indian Wells, near Indio. This proved impossible, due to desert...Overland Mail, and then the Fort Yuma to Los Angeles Road. Portions of this route are still extant in the Prado Basin south of Euclid Avenue. The Serrano...Emigrant Trail. It became the route of the Butterfield Overland Mail, and then the Fort Yuma to Los Angeles Road. Portions of this route are still extant in

Research of cost aspects of cement pavements construction

NASA Astrophysics Data System (ADS)

Bezuglyi, Artem; Illiash, Sergii; Tymoshchuk, Oleksandr

2017-09-01

The tendency to increasing traffic volume on public roads and to increased axle loads of vehicles makes the road scientists to develop scientifically justified methods for preserving the existing and developing the new transport network of Ukraine. One of the options for solving such issues is the construction of roads with rigid (cement concrete) pavement. However, any solution must be justified considering technical and economic components. This paper presents the results of the research of cost aspects of cement pavements construction.

Motion planning for autonomous vehicle based on radial basis function neural network in unstructured environment.

PubMed

Chen, Jiajia; Zhao, Pan; Liang, Huawei; Mei, Tao

2014-09-18

The autonomous vehicle is an automated system equipped with features like environment perception, decision-making, motion planning, and control and execution technology. Navigating in an unstructured and complex environment is a huge challenge for autonomous vehicles, due to the irregular shape of road, the requirement of real-time planning, and the nonholonomic constraints of vehicle. This paper presents a motion planning method, based on the Radial Basis Function (RBF) neural network, to guide the autonomous vehicle in unstructured environments. The proposed algorithm extracts the drivable region from the perception grid map based on the global path, which is available in the road network. The sample points are randomly selected in the drivable region, and a gradient descent method is used to train the RBF network. The parameters of the motion-planning algorithm are verified through the simulation and experiment. It is observed that the proposed approach produces a flexible, smooth, and safe path that can fit any road shape. The method is implemented on autonomous vehicle and verified against many outdoor scenes; furthermore, a comparison of proposed method with the existing well-known Rapidly-exploring Random Tree (RRT) method is presented. The experimental results show that the proposed method is highly effective in planning the vehicle path and offers better motion quality.

Motion Planning for Autonomous Vehicle Based on Radial Basis Function Neural Network in Unstructured Environment

PubMed Central

Chen, Jiajia; Zhao, Pan; Liang, Huawei; Mei, Tao

2014-01-01

The autonomous vehicle is an automated system equipped with features like environment perception, decision-making, motion planning, and control and execution technology. Navigating in an unstructured and complex environment is a huge challenge for autonomous vehicles, due to the irregular shape of road, the requirement of real-time planning, and the nonholonomic constraints of vehicle. This paper presents a motion planning method, based on the Radial Basis Function (RBF) neural network, to guide the autonomous vehicle in unstructured environments. The proposed algorithm extracts the drivable region from the perception grid map based on the global path, which is available in the road network. The sample points are randomly selected in the drivable region, and a gradient descent method is used to train the RBF network. The parameters of the motion-planning algorithm are verified through the simulation and experiment. It is observed that the proposed approach produces a flexible, smooth, and safe path that can fit any road shape. The method is implemented on autonomous vehicle and verified against many outdoor scenes; furthermore, a comparison of proposed method with the existing well-known Rapidly-exploring Random Tree (RRT) method is presented. The experimental results show that the proposed method is highly effective in planning the vehicle path and offers better motion quality. PMID:25237902

[Application of simulated annealing method and neural network on optimizing soil sampling schemes based on road distribution].

PubMed

Han, Zong-wei; Huang, Wei; Luo, Yun; Zhang, Chun-di; Qi, Da-cheng

2015-03-01

Taking the soil organic matter in eastern Zhongxiang County, Hubei Province, as a research object, thirteen sample sets from different regions were arranged surrounding the road network, the spatial configuration of which was optimized by the simulated annealing approach. The topographic factors of these thirteen sample sets, including slope, plane curvature, profile curvature, topographic wetness index, stream power index and sediment transport index, were extracted by the terrain analysis. Based on the results of optimization, a multiple linear regression model with topographic factors as independent variables was built. At the same time, a multilayer perception model on the basis of neural network approach was implemented. The comparison between these two models was carried out then. The results revealed that the proposed approach was practicable in optimizing soil sampling scheme. The optimal configuration was capable of gaining soil-landscape knowledge exactly, and the accuracy of optimal configuration was better than that of original samples. This study designed a sampling configuration to study the soil attribute distribution by referring to the spatial layout of road network, historical samples, and digital elevation data, which provided an effective means as well as a theoretical basis for determining the sampling configuration and displaying spatial distribution of soil organic matter with low cost and high efficiency.

Deep Constrained Siamese Hash Coding Network and Load-Balanced Locality-Sensitive Hashing for Near Duplicate Image Detection.

PubMed

Hu, Weiming; Fan, Yabo; Xing, Junliang; Sun, Liang; Cai, Zhaoquan; Maybank, Stephen

2018-09-01

We construct a new efficient near duplicate image detection method using a hierarchical hash code learning neural network and load-balanced locality-sensitive hashing (LSH) indexing. We propose a deep constrained siamese hash coding neural network combined with deep feature learning. Our neural network is able to extract effective features for near duplicate image detection. The extracted features are used to construct a LSH-based index. We propose a load-balanced LSH method to produce load-balanced buckets in the hashing process. The load-balanced LSH significantly reduces the query time. Based on the proposed load-balanced LSH, we design an effective and feasible algorithm for near duplicate image detection. Extensive experiments on three benchmark data sets demonstrate the effectiveness of our deep siamese hash encoding network and load-balanced LSH.

Privacy-Preserving Security for Vehicular Communications

ERIC Educational Resources Information Center

Weerasinghe, Hesiri Dhammika

2011-01-01

Because of the large number of deaths, severe injuries and huge financial loss due to auto accidents and poor traffic management, road safety and traffic management have become very important areas of interest among research community. As a result, Vehicular Ad-hoc Network (VANET) becomes a promising technology to improve road safety and quality…

Assessment of commuters' daily exposure to flash flooding over the roads of the Gard region, France

NASA Astrophysics Data System (ADS)

Debionne, Samuel; Ruin, Isabelle; Shabou, Saif; Lutoff, Céline; Creutin, Jean-Dominique

2016-10-01

Flash floods are responsible for a majority of natural disaster fatalities in the USA and Europe and most of them are vehicle-related. If human exposure to flood is generally assessed through the number of inhabitants per buildings located in flood prone zone, it is clear that this number varies dramatically throughout the day as people move from place to place to follow their daily program of activities. Knowing the number of motorists exposed on flood prone road sections or the factors determining their exposure would allow providing a more realistic evaluation of the degree of exposure. In order to bridge this gap and provide emergency managers with methods to assess the risk level for motorists, this paper describes two methods, a simple rough-and-ready estimate and a traffic attribution method, and applies both of them on datasets of the Gard département, an administrative region of Southern France with about 700 000 inhabitants over 5875 km2. The first method to obtain an overall estimation of motorists flood exposure is to combine (i) the regional density of roads and rivers to derive a count of potential road cuts and (ii) the average daily kilometers driven by commuters of the study area to derive the number of people passing these potential cuts. If useful as a first approximation, this method fails to capture the spatial heterogeneities introduced by the geometry of river and road networks and the distribution of commuters' itineraries. To address this point, this paper (i) uses a pre-established detailed identification of road cuts (Naulin et al., 2013) and (ii) applies a well-known traffic attribution method to existing and freely available census datasets. Both methods indicate that commuters' exposure is much larger than the number of commuters itself, illustrating the risk amplification effect of mobility. Comparing the results from both methods shows that (i) the road network geometry plays a significant role in reducing the risk of river-road dangerous intersections and (ii) not all commuters are equally exposed. Evidently commuters who have longer routes are more exposed, but residents of rural municipalities as well as professionals with highly qualified jobs are also more exposed. Finally, these exposure assessment methods applied to the Gard area allows locating road sections where commuters' exposure to flood is high. It also sets the first step toward the implementation of a modeling platform able to combine the estimation of daily travel patterns exposure and behavioral response of motorists to road flooding, a critical input for emergency services and services in charge of the management of road networks in flash flood prone areas.

Restoration of services in disrupted infrastructure systems: A network science approach.

PubMed

Ulusan, Aybike; Ergun, Ozlem

2018-01-01

Due to the ubiquitous nature of disruptive extreme events, functionality of the critical infrastructure systems (CIS) is constantly at risk. In case of a disruption, in order to minimize the negative impact to the society, service networks operating on the CIS should be restored as quickly as possible. In this paper, we introduce a novel network science inspired measure to quantify the criticality of components within a disrupted service network and develop a restoration heuristic (Cent-Restore) that prioritizes restoration efforts based on this measure. As an illustrative case study, we consider a road network blocked by debris in the aftermath of a natural disaster. The debris obstructs the flow of relief aid and search-and-rescue teams between critical facilities and disaster sites, debilitating the emergency service network. In this context, the problem is defined as finding a schedule to clear the roads with the limited resources. First, we develop a mixed-integer programming model for the problem. Then we validate the efficiency and accuracy of the Cent-Restore heuristic on randomly generated instances by comparing it to the model. Furthermore, we use Cent-Restore to recommend real-time restoration plans for disrupted road networks of Boston and Manhattan and analyze the performance of the plans over time through resilience curves. We compare Cent-Restore to the current restoration guidelines proposed by FEMA and other strategies that prioritize the restoration efforts based on different measures. As a result we confirm the importance of including specific post-disruption attributes of the networks to create effective restoration strategies. Moreover, we explore the relationship between a service network's resilience and its topological and operational characteristics under different disruption scenarios. The methods and insights provided in this work can be extended to other disrupted large-scale critical infrastructure systems in which the ultimate goal is to enable the functions of the overlaying service networks.

Connectivity: Performance Portable Algorithms for graph connectivity v. 0.1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Slota, George; Rajamanickam, Sivasankaran; Madduri, Kamesh

Graphs occur in several places in real world from road networks, social networks and scientific simulations. Connectivity is a graph analysis software to graph connectivity in modern architectures like multicore CPUs, Xeon Phi and GPUs.

STUDY ON SUPPORTING FOR DRAWING UP THE BCP FOR URBAN EXPRESSWAY NETWORK USING BY TRAFFIC SIMULATION SYSTEM

NASA Astrophysics Data System (ADS)

Yamawaki, Masashi; Shiraki, Wataru; Inomo, Hitoshi; Yasuda, Keiichi

The urban expressway network is an important infrastructure to execute a disaster restoration. Therefore, it is necessary to draw up the BCP (Business Continuity Plan) to enable securing of road user's safety and restoration of facilities, etc. It is important that each urban expressway manager execute decision and improvement of effective BCP countermeasures when disaster occurs by assuming various disaster situations. Then, in this study, we develop the traffic simulation system that can reproduce various disaster situations and traffic actions, and examine some methods supporting for drawing up the BCP for an urban expressway network. For disaster outside assumption such as tsunami generated by a huge earthquake, we examine some approaches securing safety of users and cars on the Hanshin Expressway Network as well as on general roads. And, we aim to propose a tsunami countermeasure not considered in the current urban expressway BCP.

Updating road databases from shape-files using aerial images

NASA Astrophysics Data System (ADS)

Häufel, Gisela; Bulatov, Dimitri; Pohl, Melanie

2015-10-01

Road databases are an important part of geo data infrastructure. The knowledge about their characteristics and course is essential for urban planning, navigation or evacuation tasks. Starting from OpenStreetMap (OSM) shape-file data for street networks, we introduce an algorithm to enrich these available road maps by new maps which are based on other airborne sensor technology. In our case, these are results of our context-based urban terrain reconstruction process. We wish to enhance the use of road databases by computing additional junctions, narrow passages and other items which may emerge due to changes in the terrain. This is relevant for various military and civil applications.

Differential patterns, trends and hotspots of road traffic injuries on different road networks in Vellore district, southern India.

PubMed

Mohan, Venkata Raghava; Sarkar, Rajiv; Abraham, Vinod Joseph; Balraj, Vinohar; Naumova, Elena N

2015-03-01

To describe spatial and temporal profiles of Road Traffic Injuries (RTIs) on different road networks in Vellore district of southern India. Using the information in the police maintained First Information Reports (FIRs), daily time series of RTI counts were created and temporal characteristics were analysed with respect to the vehicle, road types and time of the day for the period January 2005 to May 2007. Daily incidence and trend of RTIs were estimated using a Poisson regression analysis. Of the reported 3262 RTIs, 52% had occurred on the National Highway (NH). The overall RTI rate on the NH was 8.8/100 000 vehicles per day with significantly higher pedestrian involvement. The mean numbers of RTIs were significantly higher on weekends. Thirteen percentage of all RTIs were associated with fatalities. Hotspots are major town junctions, and RTI rates differ over different stretches of the NH. In India, FIRs form a valuable source of RTI information. Information on different vehicle profile, RTI patterns, and their spatial and temporal trends can be used by administrators to devise effective strategies for RTI prevention by concentrating on the high-risk areas, thereby optimising the use of available personnel and resources. © 2014 John Wiley & Sons Ltd.

Effects of iterative learning based signal control strategies on macroscopic fundamental diagrams of urban road networks

NASA Astrophysics Data System (ADS)

Yan, Fei; Tian, Fuli; Shi, Zhongke

2016-10-01

Urban traffic flows are inherently repeated on a daily or weekly basis. This repeatability can help improve the traffic conditions if it is used properly by the control system. In this paper, we propose a novel iterative learning control (ILC) strategy for traffic signals of urban road networks using the repeatability feature of traffic flow. To improve the control robustness, the ILC strategy is further integrated with an error feedback control law in a complementary manner. Theoretical analysis indicates that the ILC-based traffic signal control methods can guarantee the asymptotic learning convergence, despite the presence of modeling uncertainties and exogenous disturbances. Finally, the impacts of the ILC-based signal control strategies on the network macroscopic fundamental diagram (MFD) are examined. The results show that the proposed ILC-based control strategies can homogenously distribute the network accumulation by controlling the vehicle numbers in each link to the desired levels under different traffic demands, which can result in the network with high capacity and mobility.

Evolving phenotypic networks in silico.

PubMed

François, Paul

2014-11-01

Evolved gene networks are constrained by natural selection. Their structures and functions are consequently far from being random, as exemplified by the multiple instances of parallel/convergent evolution. One can thus ask if features of actual gene networks can be recovered from evolutionary first principles. I review a method for in silico evolution of small models of gene networks aiming at performing predefined biological functions. I summarize the current implementation of the algorithm, insisting on the construction of a proper "fitness" function. I illustrate the approach on three examples: biochemical adaptation, ligand discrimination and vertebrate segmentation (somitogenesis). While the structure of the evolved networks is variable, dynamics of our evolved networks are usually constrained and present many similar features to actual gene networks, including properties that were not explicitly selected for. In silico evolution can thus be used to predict biological behaviours without a detailed knowledge of the mapping between genotype and phenotype. Copyright © 2014 The Author. Published by Elsevier Ltd.. All rights reserved.

Indirect diagnosis of pavement structural damages using surface GPR reflection techniques

NASA Astrophysics Data System (ADS)

Benedetto, A.; Pensa, S.

2007-06-01

The safety and operability of road networks is, in part, dependent on the quality of the pavement. It is known that pavements suffer from many different structural problems which can lead to damage to the pavement surface. To minimize the effect of these problems programmed policies for pavement management are required. Additionally a given local anomaly on the road surface can affect the safety of the road to various degrees according to the category of the road, so it is possible to set up different programmes of repair according to the different standards of road. Programmed policies for pavement management are required because of the wide structural damage which occurs to pavements during their normal operating life. This has consequences for the safety and operability of road networks. During the last decade, road networks suffered from great structural damage. The damage occurs for different reasons, such as the increasing traffic or the lack of means for routine maintenance. Many forms of damage, originating in the bottom layers are invisible until the pavement cracks. They depend on the infiltration of water and the presence of cohesive soil greatly reduces the bearing capacity of the sub-asphalt layers and underlying soils. On the basis of an in-depth literature review, an experimental survey with Ground Penetrating Radar (GPR) was carried out to calibrate the geophysical parameters and to validate the reliability of an indirect diagnostic method of pavement damage. The experiments were set on a pavement under which water was injected over a period of several hours. GPR travel time data were used to estimate the dielectric constant and the water content in the unbound aggregate layer, the variations in water content with time and particular areas where rate of infiltration decreases. A new methodology has been proposed to extract the hydraulic permittivity fields in sub-asphalt structural layers and soils from the moisture maps observed with GPR. It is effective at diagnosing the presence of clay or cohesive soil that compromises the bearing capacity of sub-base and induces damage.

Methods to improve traffic flow and noise exposure estimation on minor roads.

PubMed

Morley, David W; Gulliver, John

2016-09-01

Address-level estimates of exposure to road traffic noise for epidemiological studies are dependent on obtaining data on annual average daily traffic (AADT) flows that is both accurate and with good geographical coverage. National agencies often have reliable traffic count data for major roads, but for residential areas served by minor roads, especially at national scale, such information is often not available or incomplete. Here we present a method to predict AADT at the national scale for minor roads, using a routing algorithm within a geographical information system (GIS) to rank roads by importance based on simulated journeys through the road network. From a training set of known minor road AADT, routing importance is used to predict AADT on all UK minor roads in a regression model along with the road class, urban or rural location and AADT on the nearest major road. Validation with both independent traffic counts and noise measurements show that this method gives a considerable improvement in noise prediction capability when compared to models that do not give adequate consideration to minor road variability (Spearman's rho. increases from 0.46 to 0.72). This has significance for epidemiological cohort studies attempting to link noise exposure to adverse health outcomes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Drivers' social-work relationships as antecedents of unsafe driving: A social network perspective.

PubMed

Arizon Peretz, Renana; Luria, Gil

2017-09-01

In order to reduce road accidents rates, studies around the globe have attempted to shed light on the antecedents for unsafe road behaviors. The aim of the current research is to contribute to this literature by offering a new organizational antecedent of driver's unsafe behavior: The driver's relationships with his or her peers, as reflected in three types of social networks: negative relationships network, friendship networks and advice networks (safety consulting). We hypothesized that a driver's position in negative relationship networks, friendship networks, and advice networks will predict unsafe driving. Additionally, we hypothesized the existence of mutual influences among the driver's positions in these various networks, and suggested that the driver's positions interact to predict unsafe driving behaviors. The research included 83 professional drivers from four different organizations. Driving behavior data were gathered via the IVDR (In-Vehicle Data Recorder) system, installed in every truck to measure and record the driver's behavior. The findings indicated that the drivers' position in the team networks predicts safe driving behavior: Centrality in negative relationship networks is positively related to unsafe driving, and centrality in friendship networks is negatively related to unsafe driving, while centrality in advice networks is not related to unsafe driving. Furthermore, we found an interaction effect between negative network centrality and centrality in friendship networks. The relation between negative networks and unsafe behavior is weaker when high levels of friendship network centrality exist. The implications will be presented in the Discussion section. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fiber optic sensor for monitoring a density of road traffic

NASA Astrophysics Data System (ADS)

Nedoma, Jan; Fajkus, Marcel; Martinek, Radek; Mec, Pavel; Novak, Martin; Jargus, Jan; Vasinek, Vladimir

2017-10-01

Authors of this article have focused on the use of fiber-optic technology in the car traffic. The article describes the use of fiber-optic interferometer for the purpose of the dynamic calculation of traffic density and inclusion the vehicle into the traffic lane. The objective is to increase safety and traffic flow. Presented solution is characterized by the non-destructive character to the road - sensor no need built into the roadway. The sensor works with standard telecommunications fibers of the G.652 standard. Other hallmarks are immunity to electromagnetic interference (EMI) and passivity of concerning the power supply. The massive expansion of optical cables within telecommunication needs along roads offers the possibility of connecting to the existing telecommunications fiber-optic network without a converter. Information can be transmitted at distances of several km up to tens km by this fiber-optic network. Set of experimental measurements in real traffic flow verified the functionality of presented solution.

The impact of self-driving cars on existing transportation networks

NASA Astrophysics Data System (ADS)

Ji, Xiang

2018-04-01

In this paper, considering the usage of self-driving, I research the congestion problems of traffic networks from both macro and micro levels. Firstly, the macroscopic mathematical model is established using the Greenshields function, analytic hierarchy process and Monte Carlo simulation, where the congestion level is divided into five levels according to the average vehicle speed. The roads with an obvious congestion situation is investigated mainly and the traffic flow and topology of the roads are analyzed firstly. By processing the data, I propose a traffic congestion model. In the model, I assume that half of the non-self-driving cars only take the shortest route and the other half can choose the path randomly. While self-driving cars can obtain vehicle density data of each road and choose the path more reasonable. When the path traffic density exceeds specific value, it cannot be selected. To overcome the dimensional differences of data, I rate the paths by BORDA sorting. The Monte Carlo simulation of Cellular Automaton is used to obtain the negative feedback information of the density of the traffic network, where the vehicles are added into the road network one by one. I then analyze the influence of negative feedback information on path selection of intelligent cars. The conclusion is that the increase of the proportion of intelligent vehicles will make the road load more balanced, and the self-driving cars can avoid the peak and reduce the degree of road congestion. Combined with other models, the optimal self-driving ratio is about sixty-two percent. From the microscopic aspect, by using the single-lane traffic NS rule, another model is established to analyze the road Partition scheme. The self-driving traffic is more intelligent, and their cooperation can reduce the random deceleration probability. By the model, I get the different self-driving ratio of space-time distribution. I also simulate the case of making a lane separately for self-driving, compared to the former model. It is concluded that a single lane is more efficient in a certain interval. However, it is not recommended to offer a lane separately. However, the self-driving also faces the problem of hacker attacks and greater damage after fault. So, when self-driving ratio is higher than a certain value, the increase of traffic flow rate is small. In this article, that value is discussed, and the optimal proportion is determined. Finally, I give a nontechnical explanation of the problem.

Incidents Prediction in Road Junctions Using Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Hajji, Tarik; Alami Hassani, Aicha; Ouazzani Jamil, Mohammed

2018-05-01

The implementation of an incident detection system (IDS) is an indispensable operation in the analysis of the road traffics. However the IDS may, in no case, represent an alternative to the classical monitoring system controlled by the human eye. The aim of this work is to increase detection and prediction probability of incidents in camera-monitored areas. Knowing that, these areas are monitored by multiple cameras and few supervisors. Our solution is to use Artificial Neural Networks (ANN) to analyze moving objects trajectories on captured images. We first propose a modelling of the trajectories and their characteristics, after we develop a learning database for valid and invalid trajectories, and then we carry out a comparative study to find the artificial neural network architecture that maximizes the rate of valid and invalid trajectories recognition.

Ribbon networks for modeling navigable paths of autonomous agents in virtual environments.

PubMed

Willemsen, Peter; Kearney, Joseph K; Wang, Hongling

2006-01-01

This paper presents the Environment Description Framework (EDF) for modeling complex networks of intersecting roads and pathways in virtual environments. EDF represents information about the layout of streets and sidewalks, the rules that govern behavior on roads and walkways, and the locations of agents with respect to navigable structures. The framework serves as the substrate on which behavior programs for autonomous vehicles and pedestrians are built. Pathways are modeled as ribbons in space. The ribbon structure provides a natural coordinate frame for defining the local geometry of navigable surfaces. EDF includes a powerful runtime interface supported by robust and efficient code for locating objects on the ribbon network, for mapping between Cartesian and ribbon coordinates, and for determining behavioral constraints imposed by the environment.

The Traffic Adaptive Data Dissemination (TrAD) Protocol for both Urban and Highway Scenarios.

PubMed

Tian, Bin; Hou, Kun Mean; Zhou, Haiying

2016-06-21

The worldwide economic cost of road crashes and injuries is estimated to be US$518 billion per year and the annual congestion cost in France is estimated to be €5.9 billion. Vehicular Ad hoc Networks (VANETs) are one solution to improve transport features such as traffic safety, traffic jam and infotainment on wheels, where a great number of event-driven messages need to be disseminated in a timely way in a region of interest. In comparison with traditional wireless networks, VANETs have to consider the highly dynamic network topology and lossy links due to node mobility. Inter-Vehicle Communication (IVC) protocols are the keystone of VANETs. According to our survey, most of the proposed IVC protocols focus on either highway or urban scenarios, but not on both. Furthermore, too few protocols, considering both scenarios, can achieve high performance. In this paper, an infrastructure-less Traffic Adaptive data Dissemination (TrAD) protocol which takes into account road traffic and network traffic status for both highway and urban scenarios will be presented. TrAD has double broadcast suppression techniques and is designed to adapt efficiently to the irregular road topology. The performance of the TrAD protocol was evaluated quantitatively by means of realistic simulations taking into account different real road maps, traffic routes and vehicular densities. The obtained simulation results show that TrAD is more efficient in terms of packet delivery ratio, number of transmissions and delay in comparison with the performance of three well-known reference protocols. Moreover, TrAD can also tolerate a reasonable degree of GPS drift and still achieve efficient data dissemination.

The Traffic Adaptive Data Dissemination (TrAD) Protocol for both Urban and Highway Scenarios

PubMed Central

Tian, Bin; Hou, Kun Mean; Zhou, Haiying

2016-01-01

The worldwide economic cost of road crashes and injuries is estimated to be US$518 billion per year and the annual congestion cost in France is estimated to be €5.9 billion. Vehicular Ad hoc Networks (VANETs) are one solution to improve transport features such as traffic safety, traffic jam and infotainment on wheels, where a great number of event-driven messages need to be disseminated in a timely way in a region of interest. In comparison with traditional wireless networks, VANETs have to consider the highly dynamic network topology and lossy links due to node mobility. Inter-Vehicle Communication (IVC) protocols are the keystone of VANETs. According to our survey, most of the proposed IVC protocols focus on either highway or urban scenarios, but not on both. Furthermore, too few protocols, considering both scenarios, can achieve high performance. In this paper, an infrastructure-less Traffic Adaptive data Dissemination (TrAD) protocol which takes into account road traffic and network traffic status for both highway and urban scenarios will be presented. TrAD has double broadcast suppression techniques and is designed to adapt efficiently to the irregular road topology. The performance of the TrAD protocol was evaluated quantitatively by means of realistic simulations taking into account different real road maps, traffic routes and vehicular densities. The obtained simulation results show that TrAD is more efficient in terms of packet delivery ratio, number of transmissions and delay in comparison with the performance of three well-known reference protocols. Moreover, TrAD can also tolerate a reasonable degree of GPS drift and still achieve efficient data dissemination. PMID:27338393

Restoration of services in disrupted infrastructure systems: A network science approach

PubMed Central

Ergun, Ozlem

2018-01-01

Due to the ubiquitous nature of disruptive extreme events, functionality of the critical infrastructure systems (CIS) is constantly at risk. In case of a disruption, in order to minimize the negative impact to the society, service networks operating on the CIS should be restored as quickly as possible. In this paper, we introduce a novel network science inspired measure to quantify the criticality of components within a disrupted service network and develop a restoration heuristic (Cent-Restore) that prioritizes restoration efforts based on this measure. As an illustrative case study, we consider a road network blocked by debris in the aftermath of a natural disaster. The debris obstructs the flow of relief aid and search-and-rescue teams between critical facilities and disaster sites, debilitating the emergency service network. In this context, the problem is defined as finding a schedule to clear the roads with the limited resources. First, we develop a mixed-integer programming model for the problem. Then we validate the efficiency and accuracy of the Cent-Restore heuristic on randomly generated instances by comparing it to the model. Furthermore, we use Cent-Restore to recommend real-time restoration plans for disrupted road networks of Boston and Manhattan and analyze the performance of the plans over time through resilience curves. We compare Cent-Restore to the current restoration guidelines proposed by FEMA and other strategies that prioritize the restoration efforts based on different measures. As a result we confirm the importance of including specific post-disruption attributes of the networks to create effective restoration strategies. Moreover, we explore the relationship between a service network’s resilience and its topological and operational characteristics under different disruption scenarios. The methods and insights provided in this work can be extended to other disrupted large-scale critical infrastructure systems in which the ultimate goal is to enable the functions of the overlaying service networks. PMID:29444191

School Library Media Specialists and the Internet: Road Kill or Road Warriors?

ERIC Educational Resources Information Center

Barron, Daniel D.

1994-01-01

Discusses use of the Internet by school library media specialists and its importance in the development of the library profession. Highlights include how to access the Internet and resources about the Internet, including information about networks as well as three sources that provide introductions to the general concepts of the Internet. (LRW)

Power and Energy: Geopolitical Aspects of the Transnational Natural Gas Pipelines from the Caspian Sea Basin to Europe

DTIC Science & Technology

2010-06-01

corridor as the “Silk Road.”25 On this trade-road network, merchants, missionaries , and conquistadors carried silk, gems, pottery, tea, paper, medicines...2010). Atwell, Kyle. “Yanukovich: Ukraine will be a ridge between East and West” Atlantic Review, Feb 19, 2010, http://atlanticreview.org/archives

Effects of road infrastructure and traffic complexity in speed adaptation behaviour of distracted drivers.

PubMed

Oviedo-Trespalacios, Oscar; Haque, Md Mazharul; King, Mark; Washington, Simon

2017-04-01

The use of mobile phones while driving remains a major human factors issue in the transport system. A significant safety concern is that driving while distracted by a mobile phone potentially modifies the driving speed leading to conflicts with other road users and consequently increases crash risk. However, the lack of systematic knowledge of the mechanisms involved in speed adaptation of distracted drivers constrains the explanation and modelling of the extent of this phenomenon. The objective of this study was to investigate speed adaptation of distracted drivers under varying road infrastructure and traffic complexity conditions. The CARRS-Q Advanced Driving Simulator was used to test participants on a simulated road with different traffic conditions, such as free flow traffic along straight roads, driving in urbanized areas, and driving in heavy traffic along suburban roads. Thirty-two licensed young drivers drove the simulator under three phone conditions: baseline (no phone conversation), hands-free and handheld phone conversations. To understand the relationships between distraction, road infrastructure and traffic complexity, speed adaptation calculated as the deviation of driving speed from the posted speed limit was modelled using a decision tree. The identified groups of road infrastructure and traffic characteristics from the decision tree were then modelled with a Generalized Linear Mixed Model (GLMM) with repeated measures to develop inferences about speed adaptation behaviour of distracted drivers. The GLMM also included driver characteristics and secondary task demands as predictors of speed adaptation. Results indicated that complex road environments like urbanization, car-following situations along suburban roads, and curved road alignment significantly influenced speed adaptation behaviour. Distracted drivers selected a lower speed while driving along a curved road or during car-following situations, but speed adaptation was negligible in the presence of high visual cutter, indicating the prioritization of the driving task over the secondary task. Additionally, drivers who scored high on self-reported safe attitudes towards mobile phone usage, and who reported prior involvement in a road traffic crash, selected a lower driving speed in the distracted condition than in the baseline. The results aid in understanding how driving task demands influence speed adaptation of distracted drivers under various road infrastructure and traffic complexity conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Non-Intrusive Gaze Tracking Using Artificial Neural Networks

DTIC Science & Technology

1994-01-05

We have developed an artificial neural network based gaze tracking, system which can be customized to individual users. A three layer feed forward...empirical analysis of the performance of a large number of artificial neural network architectures for this task. Suggestions for further explorations...for neurally based gaze trackers are presented, and are related to other similar artificial neural network applications such as autonomous road following.

Boundary conditions estimation on a road network using compressed sensing.

DOT National Transportation Integrated Search

2016-02-01

This report presents a new boundary condition estimation framework for transportation networks in which : the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a : Hamilton-Jacobi equation, we pose th...

Impact of constrained rewiring on network structure and node dynamics

NASA Astrophysics Data System (ADS)

Rattana, P.; Berthouze, L.; Kiss, I. Z.

2014-11-01

In this paper, we study an adaptive spatial network. We consider a susceptible-infected-susceptible (SIS) epidemic on the network, with a link or contact rewiring process constrained by spatial proximity. In particular, we assume that susceptible nodes break links with infected nodes independently of distance and reconnect at random to susceptible nodes available within a given radius. By systematically manipulating this radius we investigate the impact of rewiring on the structure of the network and characteristics of the epidemic. We adopt a step-by-step approach whereby we first study the impact of rewiring on the network structure in the absence of an epidemic, then with nodes assigned a disease status but without disease dynamics, and finally running network and epidemic dynamics simultaneously. In the case of no labeling and no epidemic dynamics, we provide both analytic and semianalytic formulas for the value of clustering achieved in the network. Our results also show that the rewiring radius and the network's initial structure have a pronounced effect on the endemic equilibrium, with increasingly large rewiring radiuses yielding smaller disease prevalence.

Constrained Surface-Level Gateway Placement for Underwater Acoustic Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Li, Deying; Li, Zheng; Ma, Wenkai; Chen, Hong

One approach to guarantee the performance of underwater acoustic sensor networks is to deploy multiple Surface-level Gateways (SGs) at the surface. This paper addresses the connected (or survivable) Constrained Surface-level Gateway Placement (C-SGP) problem for 3-D underwater acoustic sensor networks. Given a set of candidate locations where SGs can be placed, our objective is to place minimum number of SGs at a subset of candidate locations such that it is connected (or 2-connected) from any USN to the base station. We propose a polynomial time approximation algorithm for the connected C-SGP problem and survivable C-SGP problem, respectively. Simulations are conducted to verify our algorithms' efficiency.

Bearing Capacity Assessment on low Volume Roads

NASA Astrophysics Data System (ADS)

Zariņš, A.

2015-11-01

A large part of Latvian road network consists of low traffic volume roads and in particular of roads without hard pavement. Unbounded pavements shows serious problems in the form of rutting and other deformations, which finally lead to weak serviceability and damage of the road structure after intensive exploitation periods. Traditionally, these problems have been associated with heavy goods transport, overloaded vehicles and their impact. To find the specific damaging factors causing road pavement deformations and evaluate their prevention possibilities, and establish conditions that will allow doing it, the study was carried out. The tire pressure has been set as the main factor of load. Two different tire pressures have been used in tests and their impacts were compared. The comparison was done using deflection measurements with LWD together with dielectric constant measurements in a road structure using percometer. Measurements were taken in the upper pavement structure layers at different depths during full-scale loading and in different moisture/temperature conditions. Advisable load intensity and load factors for heavy traffic according to road conditions were set based on the study results.

Supplement Analysis for the Watershed Management Program EIS (DOE/EIS-0265/SA-155) - Blind Slough Restoration Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wittpenn, Nancy A.

2004-07-09

This project proposes to restore tidal connection between the Columbia River Estuary and Blind Slough through the replacement and/or installation of culverts, installation of water control devices, breaching of dikes, and channel enhancement. These enhancements would restore connectivity to approximately ten (10) miles of slough channels previously isolated from tidal influence due to dikes, road crossings, and constrained culverts.

The Use of Simulators in Rules of the Road Training

DTIC Science & Technology

2013-12-01

ships and total losses (collision, contact, fire/explosion, foundering, wrecked /stranded, hull/machinery, missing and other) (from Sampson et al...number of ships and total losses (collision, contact, fire/explosion, foundering, wrecked /stranded, hull/machinery, missing and other) (from Sampson...another vessel at night, it would be a vessel ___ _ o (a) aground (b) constrained by her draft o (c) dredging o (d) moored over a wreck Post

Joint Resource Optimization for Cognitive Sensor Networks with SWIPT-Enabled Relay.

PubMed

Lu, Weidang; Lin, Yuanrong; Peng, Hong; Nan, Tian; Liu, Xin

2017-09-13

Energy-constrained wireless networks, such as wireless sensor networks (WSNs), are usually powered by fixed energy supplies (e.g., batteries), which limits the operation time of networks. Simultaneous wireless information and power transfer (SWIPT) is a promising technique to prolong the lifetime of energy-constrained wireless networks. This paper investigates the performance of an underlay cognitive sensor network (CSN) with SWIPT-enabled relay node. In the CSN, the amplify-and-forward (AF) relay sensor node harvests energy from the ambient radio-frequency (RF) signals using power splitting-based relaying (PSR) protocol. Then, it helps forward the signal of source sensor node (SSN) to the destination sensor node (DSN) by using the harvested energy. We study the joint resource optimization including the transmit power and power splitting ratio to maximize CSN's achievable rate with the constraint that the interference caused by the CSN to the primary users (PUs) is within the permissible threshold. Simulation results show that the performance of our proposed joint resource optimization can be significantly improved.

Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks

NASA Technical Reports Server (NTRS)

Cheung, Kar-Ming; Lee, Charles H.

2012-01-01

We developed framework and the mathematical formulation for optimizing communication network using mixed integer programming. The design yields a system that is much smaller, in search space size, when compared to the earlier approach. Our constrained network optimization takes into account the dynamics of link performance within the network along with mission and operation requirements. A unique penalty function is introduced to transform the mixed integer programming into the more manageable problem of searching in a continuous space. The constrained optimization problem was proposed to solve in two stages: first using the heuristic Particle Swarming Optimization algorithm to get a good initial starting point, and then feeding the result into the Sequential Quadratic Programming algorithm to achieve the final optimal schedule. We demonstrate the above planning and scheduling methodology with a scenario of 20 spacecraft and 3 ground stations of a Deep Space Network site. Our approach and framework have been simple and flexible so that problems with larger number of constraints and network can be easily adapted and solved.

The number and type of food retailers surrounding schools and their association with lunchtime eating behaviours in students.

PubMed

Seliske, Laura; Pickett, William; Rosu, Andrei; Janssen, Ian

2013-02-07

The primary study objective was to examine whether the presence of food retailers surrounding schools was associated with students' lunchtime eating behaviours. The secondary objective was to determine whether measures of the food retail environment around schools captured using road network or circular buffers were more strongly related to eating behaviours while at school. Grade 9 and 10 students (N=6,971) who participated in the 2009/10 Canadian Health Behaviour in School Aged Children Survey were included in this study. The outcome was determined by students' self-reports of where they typically ate their lunch during school days. Circular and road network-based buffers were created for a 1 km distance surrounding 158 schools participating in the HBSC. The addresses of fast food restaurants, convenience stores and coffee/donut shops were mapped within the buffers. Multilevel logistic regression was used to determine whether there was a relationship between the presence of food retailers near schools and students regularly eating their lunch at a fast food restaurant, snack-bar or café. The Akaike Information Criteria (AIC) value, a measure of goodness-of-fit, was used to determine the optimal buffer type. For the 1 km circular buffers, students with 1-2 (OR= 1.10, 95% CI: 0.57-2.11), 3-4 (OR=1.45, 95% CI: 0.75-2.82) and ≥5 nearby food retailers (OR=2.94, 95% CI: 1.71-5.09) were more likely to eat lunch at a food retailer compared to students with no nearby food retailers. The relationships were slightly stronger when assessed via 1 km road network buffers, with a greater likelihood of eating at a food retailer for 1-2 (OR=1.20, 95% CI:0.74-1.95), 3-4 (OR=3.19, 95% CI: 1.66-6.13) and ≥5 nearby food retailers (OR=3.54, 95% CI: 2.08-6.02). Road network buffers appeared to provide a better measure of the food retail environment, as indicated by a lower AIC value (3332 vs. 3346). There was a strong relationship between the presence of food retailers near schools and students' lunchtime eating behaviours. Results from the goodness of fit analysis suggests that road network buffers provide a more optimal measure of school neighbourhood food environments relative to circular buffers.

Damage Assessment for Disaster Relief Efforts in Urban Areas Using Optical Imagery and LiDAR Data

NASA Astrophysics Data System (ADS)

Bahr, Thomas

2014-05-01

Imagery combined with LiDAR data and LiDAR-derived products provides a significant source of geospatial data which is of use in disaster mitigation planning. Feature rich building inventories can be constructed from tools with 3D rooftop extraction capabilities, and two dimensional outputs such as DSMs and DTMs can be used to generate layers to support routing efforts in Spatial Analyst and Network Analyst workflows. This allows us to leverage imagery and LiDAR tools for disaster mitigation or other scenarios. Software such as ENVI, ENVI LiDAR, and ArcGIS® Spatial and Network Analyst can therefore be used in conjunction to help emergency responders route ground teams in support of disaster relief efforts. This is exemplified by a case study against the background of the magnitude 7.0 earthquake that struck Haiti's capital city of Port-au-Prince on January 12, 2010. Soon after, both LiDAR data and an 8-band WorldView-2 scene were collected to map the disaster zone. The WorldView-2 scene was orthorectified and atmospherically corrected in ENVI prior to use. ENVI LiDAR was used to extract the DSM, DTM, buildings, and debris from the LiDAR data point cloud. These datasets provide a foundation for the 2D portion of the analysis. As the data was acquired over an area of dense urbanization, the majority of ground surfaces are roads, and standing buildings and debris are actually largely separable on the basis of elevation classes. To extract the road network of Port-au-Prince, the LiDAR-based feature height information was fused with the WorldView-2 scene, using ENVI's object-based feature extraction approach. This road network was converted to a network dataset for further analysis by the ArcGIS Network Analyst. For the specific case of Haiti, the distribution of blue tarps, used as accommodations for refugees, provided a spectrally distinct target. Pure blue tarp pixel spectra were selected from the WorldView-2 scene and input as a reference into ENVI's Spectral Angle Mapper (SAM) classification routine, together with a water-shadow mask to prevent false positives. The resulting blue tarp shape file was input into the ArcGIS Point Density tool, a feature of the Spatial Analyst toolbox. The final distribution map shows the density of blue tarps in Port-au-Prince and can be used to roughly delineate camps of refugees. Analogous, a debris density map was generated after separating the debris elevation class. The combination of this debris density map with the road network allowed to construct an intact road network of Port-au-Prince within the ArcGIS Network Analyst. Moderate density debris was used as a cost-increase barrier feature of the network dataset, and high density debris was used as a total obstruction barrier feature. Based on this information, two hypothetical routing scenarios were analyzed. One involved routing a ground team between two different refugee concentration zones. For the other, potential helicopter landing zones were computed from the LiDAR-derived products and added as facility features to the Network Analyst. Routes from the helicopter landing zones to refugee concentration access points were solved using closest facility logic, again making use of the obstructed network.

Low-stress bicycling and network connectivity : [research brief].

DOT National Transportation Integrated Search

2012-05-01

In one sense, a citys or regions bicycling network includes all of its roads and paths on which bicycling is permitted. However, some streets provide such a poor level of safety and comfort for bicycling that the majority of the population cons...

An integrated pavement data management and feedback system (PAMS) : final report.

DOT National Transportation Integrated Search

1987-04-01

This report discusses the implementation of a pavement condition rating (PCR) procedure to sample sections of the road network system. The resources needed are identified for such implementation. The uses of PCR data at the network and project level ...

Linkages between unpaved forest roads and streambed sediment: why context matters in directing road restoration

USGS Publications Warehouse

Al-Chokhachy, Robert K.; Black, Tom A.; Thomas, Cameron; Luce, Charlie H.; Rieman, Bruce; Cissel, Richard; Carlson, Anne; Hendrickson, Shane; Archer, Eric K.; Kershner, Jeffrey L.

2016-01-01

Unpaved forest roads remain a pervasive disturbance on public lands and mitigating sediment from road networks remains a priority for management agencies. Restoring roaded landscapes is becoming increasingly important for many native coldwater fishes that disproportionately rely on public lands for persistence. However, effectively targeting restoration opportunities requires a comprehensive understanding of the effects of roads across different ecosystems. Here, we combine a review and a field study to evaluate the status of knowledge supporting the conceptual framework linking unpaved forest roads with streambed sediment. Through our review, we specifically focused on those studies linking measures of the density of forest roads or sediment delivery with empirical streambed sediment measures. Our field study provides an example of a targeted effort of linking spatially explicit estimates of sediment production with measures of streambed sediment. Surprisingly, our review uncovered few studies (n = 8) that empirically tested the conceptual framework linking unpaved forest roads and streambed sediment, and the results varied considerably. Field results generally supported the conceptual model that unpaved forest roads can control streambed sediment quality, but demonstrated high-spatial variability in the effects of forest roads on streambed sediment and the need to address hotspots of sediment sources. The importance of context in the effects of forest roads is apparent in both our review and field data, suggesting the need for in situ studies to avoid misdirected restoration actions.

Productivity and cost estimators for conventional ground-based skidding on steep terrain using preplanned skid roads

Treesearch

Michael D. Erickson; Curt C. Hassler; Chris B. LeDoux

1991-01-01

Continuous time and motion study techniques were used to develop productivity and cost estimators for the skidding component of ground-based logging systems, operating on steep terrain using preplanned skid roads. Comparisons of productivity and costs were analyzed for an overland random access skidding method, verses a skidding method utilizing a network of preplanned...

Optimizing biomass feedstock logistics for forest residue processing and transportation on a tree-shaped road network

Treesearch

Hee Han; Woodam Chung; Lucas Wells; Nathaniel Anderson

2018-01-01

An important task in forest residue recovery operations is to select the most cost-efficient feedstock logistics system for a given distribution of residue piles, road access, and available machinery. Notable considerations include inaccessibility of treatment units to large chip vans and frequent, long-distance mobilization of forestry equipment required to process...

An outer approximation method for the road network design problem

PubMed Central

2018-01-01

Best investment in the road infrastructure or the network design is perceived as a fundamental and benchmark problem in transportation. Given a set of candidate road projects with associated costs, finding the best subset with respect to a limited budget is known as a bilevel Discrete Network Design Problem (DNDP) of NP-hard computationally complexity. We engage with the complexity with a hybrid exact-heuristic methodology based on a two-stage relaxation as follows: (i) the bilevel feature is relaxed to a single-level problem by taking the network performance function of the upper level into the user equilibrium traffic assignment problem (UE-TAP) in the lower level as a constraint. It results in a mixed-integer nonlinear programming (MINLP) problem which is then solved using the Outer Approximation (OA) algorithm (ii) we further relax the multi-commodity UE-TAP to a single-commodity MILP problem, that is, the multiple OD pairs are aggregated to a single OD pair. This methodology has two main advantages: (i) the method is proven to be highly efficient to solve the DNDP for a large-sized network of Winnipeg, Canada. The results suggest that within a limited number of iterations (as termination criterion), global optimum solutions are quickly reached in most of the cases; otherwise, good solutions (close to global optimum solutions) are found in early iterations. Comparative analysis of the networks of Gao and Sioux-Falls shows that for such a non-exact method the global optimum solutions are found in fewer iterations than those found in some analytically exact algorithms in the literature. (ii) Integration of the objective function among the constraints provides a commensurate capability to tackle the multi-objective (or multi-criteria) DNDP as well. PMID:29590111

An outer approximation method for the road network design problem.

PubMed

Asadi Bagloee, Saeed; Sarvi, Majid

2018-01-01

Best investment in the road infrastructure or the network design is perceived as a fundamental and benchmark problem in transportation. Given a set of candidate road projects with associated costs, finding the best subset with respect to a limited budget is known as a bilevel Discrete Network Design Problem (DNDP) of NP-hard computationally complexity. We engage with the complexity with a hybrid exact-heuristic methodology based on a two-stage relaxation as follows: (i) the bilevel feature is relaxed to a single-level problem by taking the network performance function of the upper level into the user equilibrium traffic assignment problem (UE-TAP) in the lower level as a constraint. It results in a mixed-integer nonlinear programming (MINLP) problem which is then solved using the Outer Approximation (OA) algorithm (ii) we further relax the multi-commodity UE-TAP to a single-commodity MILP problem, that is, the multiple OD pairs are aggregated to a single OD pair. This methodology has two main advantages: (i) the method is proven to be highly efficient to solve the DNDP for a large-sized network of Winnipeg, Canada. The results suggest that within a limited number of iterations (as termination criterion), global optimum solutions are quickly reached in most of the cases; otherwise, good solutions (close to global optimum solutions) are found in early iterations. Comparative analysis of the networks of Gao and Sioux-Falls shows that for such a non-exact method the global optimum solutions are found in fewer iterations than those found in some analytically exact algorithms in the literature. (ii) Integration of the objective function among the constraints provides a commensurate capability to tackle the multi-objective (or multi-criteria) DNDP as well.

A distance constrained synaptic plasticity model of C. elegans neuronal network

NASA Astrophysics Data System (ADS)

Badhwar, Rahul; Bagler, Ganesh

2017-03-01

Brain research has been driven by enquiry for principles of brain structure organization and its control mechanisms. The neuronal wiring map of C. elegans, the only complete connectome available till date, presents an incredible opportunity to learn basic governing principles that drive structure and function of its neuronal architecture. Despite its apparently simple nervous system, C. elegans is known to possess complex functions. The nervous system forms an important underlying framework which specifies phenotypic features associated to sensation, movement, conditioning and memory. In this study, with the help of graph theoretical models, we investigated the C. elegans neuronal network to identify network features that are critical for its control. The 'driver neurons' are associated with important biological functions such as reproduction, signalling processes and anatomical structural development. We created 1D and 2D network models of C. elegans neuronal system to probe the role of features that confer controllability and small world nature. The simple 1D ring model is critically poised for the number of feed forward motifs, neuronal clustering and characteristic path-length in response to synaptic rewiring, indicating optimal rewiring. Using empirically observed distance constraint in the neuronal network as a guiding principle, we created a distance constrained synaptic plasticity model that simultaneously explains small world nature, saturation of feed forward motifs as well as observed number of driver neurons. The distance constrained model suggests optimum long distance synaptic connections as a key feature specifying control of the network.

The effects of road building on arbuscular mycorrhizal fungal diversity in Huangshan Scenic Area.

PubMed

Yang, Anna; Tang, Dongmei; Jin, Xiulong; Lu, Lin; Li, Xiaohong; Liu, Kun

2018-01-22

Arbuscular mycorrhizal (AM) fungi are vital soil microbes that connect many individual plants into a large functional organism via a vast mycelial network under the ground. In this study, the changes of soil AM fungal community in response to road-building disturbance caused by tourism development in Huangshan (Yellow Mountain) Scenic Area are assessed. Road building have brought negative effects on AM fungal community, inducing lower diversity parameters, including species number, spore density and diversity indices. However, the dominant genus and species of AM fungi which play key roles in the AM fungal community composition are quite similar before and after road building. Moreover, there are no significant differences in species richness of AM fungi associated with plants, suggesting the tolerance of AM fungal community to the disturbance of road building.

Cart'Eaux: an automatic mapping procedure for wastewater networks using machine learning and data mining

NASA Astrophysics Data System (ADS)

Bailly, J. S.; Delenne, C.; Chahinian, N.; Bringay, S.; Commandré, B.; Chaumont, M.; Derras, M.; Deruelle, L.; Roche, M.; Rodriguez, F.; Subsol, G.; Teisseire, M.

2017-12-01

In France, local government institutions must establish a detailed description of wastewater networks. The information should be available, but it remains fragmented (different formats held by different stakeholders) and incomplete. In the "Cart'Eaux" project, a multidisciplinary team, including an industrial partner, develops a global methodology using Machine Learning and Data Mining approaches applied to various types of large data to recover information in the aim of mapping urban sewage systems for hydraulic modelling. Deep-learning is first applied using a Convolution Neural Network to localize manhole covers on 5 cm resolution aerial RGB images. The detected manhole covers are then automatically connected using a tree-shaped graph constrained by industry rules. Based on a Delaunay triangulation, connections are chosen to minimize a cost function depending on pipe length, slope and possible intersection with roads or buildings. A stochastic version of this algorithm is currently being developed to account for positional uncertainty and detection errors, and generate sets of probable networks. As more information is required for hydraulic modeling (slopes, diameters, materials, etc.), text data mining is used to extract network characteristics from data posted on the Web or available through governmental or specific databases. Using an appropriate list of keywords, the web is scoured for documents which are saved in text format. The thematic entities are identified and linked to the surrounding spatial and temporal entities. The methodology is developed and tested on two towns in southern France. The primary results are encouraging: 54% of manhole covers are detected with few false detections, enabling the reconstruction of probable networks. The data mining results are still being investigated. It is clear at this stage that getting numerical values on specific pipes will be challenging. Thus, when no information is found, decision rules will be used to assign admissible numerical values to enable the final hydraulic modelling. Consequently, sensitivity analysis of the hydraulic model will be performed to take into account the uncertainty associated with each piece of information. Project funded by the European Regional Development Fund and the Occitanie Region.

libRoadRunner: a high performance SBML simulation and analysis library

PubMed Central

Somogyi, Endre T.; Bouteiller, Jean-Marie; Glazier, James A.; König, Matthias; Medley, J. Kyle; Swat, Maciej H.; Sauro, Herbert M.

2015-01-01

Motivation: This article presents libRoadRunner, an extensible, high-performance, cross-platform, open-source software library for the simulation and analysis of models expressed using Systems Biology Markup Language (SBML). SBML is the most widely used standard for representing dynamic networks, especially biochemical networks. libRoadRunner is fast enough to support large-scale problems such as tissue models, studies that require large numbers of repeated runs and interactive simulations. Results: libRoadRunner is a self-contained library, able to run both as a component inside other tools via its C++ and C bindings, and interactively through its Python interface. Its Python Application Programming Interface (API) is similar to the APIs of MATLAB (www.mathworks.com) and SciPy (http://www.scipy.org/), making it fast and easy to learn. libRoadRunner uses a custom Just-In-Time (JIT) compiler built on the widely used LLVM JIT compiler framework. It compiles SBML-specified models directly into native machine code for a variety of processors, making it appropriate for solving extremely large models or repeated runs. libRoadRunner is flexible, supporting the bulk of the SBML specification (except for delay and non-linear algebraic equations) including several SBML extensions (composition and distributions). It offers multiple deterministic and stochastic integrators, as well as tools for steady-state analysis, stability analysis and structural analysis of the stoichiometric matrix. Availability and implementation: libRoadRunner binary distributions are available for Mac OS X, Linux and Windows. The library is licensed under Apache License Version 2.0. libRoadRunner is also available for ARM-based computers such as the Raspberry Pi. http://www.libroadrunner.org provides online documentation, full build instructions, binaries and a git source repository. Contacts: hsauro@u.washington.edu or somogyie@indiana.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26085503

libRoadRunner: a high performance SBML simulation and analysis library.

PubMed

Somogyi, Endre T; Bouteiller, Jean-Marie; Glazier, James A; König, Matthias; Medley, J Kyle; Swat, Maciej H; Sauro, Herbert M

2015-10-15

This article presents libRoadRunner, an extensible, high-performance, cross-platform, open-source software library for the simulation and analysis of models expressed using Systems Biology Markup Language (SBML). SBML is the most widely used standard for representing dynamic networks, especially biochemical networks. libRoadRunner is fast enough to support large-scale problems such as tissue models, studies that require large numbers of repeated runs and interactive simulations. libRoadRunner is a self-contained library, able to run both as a component inside other tools via its C++ and C bindings, and interactively through its Python interface. Its Python Application Programming Interface (API) is similar to the APIs of MATLAB ( WWWMATHWORKSCOM: ) and SciPy ( HTTP//WWWSCIPYORG/: ), making it fast and easy to learn. libRoadRunner uses a custom Just-In-Time (JIT) compiler built on the widely used LLVM JIT compiler framework. It compiles SBML-specified models directly into native machine code for a variety of processors, making it appropriate for solving extremely large models or repeated runs. libRoadRunner is flexible, supporting the bulk of the SBML specification (except for delay and non-linear algebraic equations) including several SBML extensions (composition and distributions). It offers multiple deterministic and stochastic integrators, as well as tools for steady-state analysis, stability analysis and structural analysis of the stoichiometric matrix. libRoadRunner binary distributions are available for Mac OS X, Linux and Windows. The library is licensed under Apache License Version 2.0. libRoadRunner is also available for ARM-based computers such as the Raspberry Pi. http://www.libroadrunner.org provides online documentation, full build instructions, binaries and a git source repository. hsauro@u.washington.edu or somogyie@indiana.edu Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2015. This work is written by US Government employees and is in the public domain in the US.

A high temporal-spatial vehicle emission inventory based on detailed hourly traffic data in a medium-sized city of China.

PubMed

Liu, Yong-Hong; Ma, Jin-Ling; Li, Li; Lin, Xiao-Fang; Xu, Wei-Jia; Ding, Hui

2018-05-01

To improve the accuracy and temporal-spatial resolution for a vehicle emission inventory in a medium-sized city with a strip road network, this study was conducted based on detailed hourly traffic-flow data for each day of 2014, and covered all road types and regions in the city of Foshan. Detailed hourly emission characteristics and sources in five regions were analysed. The results showed that the total vehicle emissions of CO, NO X , VOCs, and PM 2.5 were 13.10 × 10 4 , 0.23 × 10 4 , 4.46 × 10 4 , and 0.18 × 10 4 tons, respectively. Motorcycles (MCs) and light passenger cars (LPCs) were the dominant contributors of CO emissions, while buses and heavy passenger cars (HPCs) were the dominant contributors for NO X . As a whole, the daytime contributions to total emissions were close to 80%, and emissions during the peak periods accounted for almost 40%. Specifically, the hourly emissions of each pollutant on workdays were higher than on non-workdays (maximum up to 64.2%), and for some roads the early peak periods changed significantly from workdays to non-workdays. At expressways, artery roads, and local roads, the daily emission intensities of CO, NOx, and PM 2.5 in Foshan were close to or even higher than that of Beijing. On a regional scale, the temporal variation of vehicle emissions on workdays at artery roads of different regions were similar. In addition, the higher emission intensities of CO and VOCs were identified in DaLiang-RongGui (DLRG) and that of NO X and PM 2.5 were in Central Region (CR). These results are meaningful for decision-makers to help provide more detailed vehicle pollution control measures in Foshan with a strip road network and only one ring road. Copyright © 2018 Elsevier Ltd. All rights reserved.

Elevation data fitting and precision analysis of Google Earth in road survey

NASA Astrophysics Data System (ADS)

Wei, Haibin; Luan, Xiaohan; Li, Hanchao; Jia, Jiangkun; Chen, Zhao; Han, Leilei

2018-05-01

Objective: In order to improve efficiency of road survey and save manpower and material resources, this paper intends to apply Google Earth to the feasibility study stage of road survey and design. Limited by the problem that Google Earth elevation data lacks precision, this paper is focused on finding several different fitting or difference methods to improve the data precision, in order to make every effort to meet the accuracy requirements of road survey and design specifications. Method: On the basis of elevation difference of limited public points, any elevation difference of the other points can be fitted or interpolated. Thus, the precise elevation can be obtained by subtracting elevation difference from the Google Earth data. Quadratic polynomial surface fitting method, cubic polynomial surface fitting method, V4 interpolation method in MATLAB and neural network method are used in this paper to process elevation data of Google Earth. And internal conformity, external conformity and cross correlation coefficient are used as evaluation indexes to evaluate the data processing effect. Results: There is no fitting difference at the fitting point while using V4 interpolation method. Its external conformity is the largest and the effect of accuracy improvement is the worst, so V4 interpolation method is ruled out. The internal and external conformity of the cubic polynomial surface fitting method both are better than those of the quadratic polynomial surface fitting method. The neural network method has a similar fitting effect with the cubic polynomial surface fitting method, but its fitting effect is better in the case of a higher elevation difference. Because the neural network method is an unmanageable fitting model, the cubic polynomial surface fitting method should be mainly used and the neural network method can be used as the auxiliary method in the case of higher elevation difference. Conclusions: Cubic polynomial surface fitting method can obviously improve data precision of Google Earth. The error of data in hilly terrain areas meets the requirement of specifications after precision improvement and it can be used in feasibility study stage of road survey and design.

Vehicle NOx emission plume isotopic signatures: Spatial variability across the eastern United States

NASA Astrophysics Data System (ADS)

Miller, David J.; Wojtal, Paul K.; Clark, Sydney C.; Hastings, Meredith G.

2017-04-01

On-road vehicle nitrogen oxide (NOx) sources currently dominate the U.S. anthropogenic emission budgets, yet vehicle NOx emissions have uncertain contributions to oxidized nitrogen (N) deposition patterns. Isotopic signatures serve as a potentially valuable observational tool to trace source contributions to NOx chemistry and N deposition, yet in situ emission signatures are underconstrained. We characterize the spatiotemporal variability of vehicle NOx emission isotopic signatures (δ15N-NOx) representative of U.S. vehicle fleet-integrated emission plumes. A novel combination of on-road mobile and stationary urban measurements is performed using a field and laboratory-verified technique for actively capturing NOx in solution to quantify δ15N-NOx at hourly resolution. On-road δ15N-NOx upwind of Providence, RI, ranged from -7 to -3‰. Simultaneous urban background δ15N-NOx observations showed comparable range and variations with on-road measurements, suggesting that vehicles dominate NOx emissions in the Providence area. On-road spatial δ15N-NOx variations of -9 to -2‰ were observed under various driving conditions in six urban metropolitan areas and rural interstate highways during summer and autumn in the U.S. Northeast and Midwest. Although isotopic signatures were insensitive to on-road driving mode variations, statistically significant correlations were found between δ15N-NOx and NOx emission factor extremes associated with heavy diesel emitter contributions. Overall, these results constrain an isotopic signature of fleet-integrated roadway NOx emission plumes, which have important implications for distinguishing vehicle NOx from other sources and tracking emission contributions to NOx chemistry and N deposition.

An Efficient Method for Automatic Road Extraction Based on Multiple Features from LiDAR Data

NASA Astrophysics Data System (ADS)

Li, Y.; Hu, X.; Guan, H.; Liu, P.

2016-06-01

The road extraction in urban areas is difficult task due to the complicated patterns and many contextual objects. LiDAR data directly provides three dimensional (3D) points with less occlusions and smaller shadows. The elevation information and surface roughness are distinguishing features to separate roads. However, LiDAR data has some disadvantages are not beneficial to object extraction, such as the irregular distribution of point clouds and lack of clear edges of roads. For these problems, this paper proposes an automatic road centerlines extraction method which has three major steps: (1) road center point detection based on multiple feature spatial clustering for separating road points from ground points, (2) local principal component analysis with least squares fitting for extracting the primitives of road centerlines, and (3) hierarchical grouping for connecting primitives into complete roads network. Compared with MTH (consist of Mean shift algorithm, Tensor voting, and Hough transform) proposed in our previous article, this method greatly reduced the computational cost. To evaluate the proposed method, the Vaihingen data set, a benchmark testing data provided by ISPRS for "Urban Classification and 3D Building Reconstruction" project, was selected. The experimental results show that our method achieve the same performance by less time in road extraction using LiDAR data.

Road traffic injuries in Colombia.

PubMed

Rodríguez, Deysi Yasmin; Fernández, Francisco José; Acero Velásquez, Hugo

2003-01-01

Road traffic injuries are a leading public health problem in Colombia. Pedestrians are the most vulnerable road users, especially in the main urban centers of Bogotá, Medellin and Cali. Data analyzed in this report include official statistics from the National Police and the National Institute of Legal Medicine and Forensic Sciences for 1996-2000, and results of a study conducted at the National University of Colombia in 2000. Methods from the Highway Capacity Manual were used for determining physical and technical variables, and a Geographical Information System tool was used for the location and spatial analysis of the road traffic crashes. Pedestrians accounted for close to 32% of injuries and 40% of the deaths from road traffic crashes. The problem of road traffic crashes existed predominately in urban areas. In the main urban centers, pedestrians constituted nearly 68% of road traffic crash victims. The high level of risky road use behaviors demonstrated by pedestrians and drivers, and inadequate infrastructure for safe mobility of pedestrians in some sections of the road network were the main contributing factors. Major improvements were achieved in Bogotá following enhancements to the municipal transport system and other policies introduced since 1995. In conclusion, policies and programs for improving road safety, in particular pedestrian safety, and strengthening urban planning are top priority.

Topographic and road control of mega-gullies in Kinshasa (DR Congo)

NASA Astrophysics Data System (ADS)

Makanzu Imwangana, Fils; Dewitte, Olivier; Ntombi, Médard; Moeyersons, Jan

2014-07-01

Diachronic mapping (1957, 1967, 2007 and 2010) shows an exponentially growing mega-gully network since roads were constructed through in the forests and plantations which occupied the sandy soils of the high town of Kinshasa. We found that the spatial occurrence of the mega-gullies (width ≥ 5 m) in this newly urbanized environment is controlled by two factors. First, there is a topographic control, given by the relation S = 0.00008A- 1.459, with S being the slope gradient (m m- 1) of the soil surface at the gully head and A the drainage area (ha) above the head. There is also a ‘road’ control, expressed by S = 22.991Lc- 1.999, with Lc being the cumulated length of roads in the basin above the gully head. The co-existence of both controls reflects the fact that the local sands are highly permeable and hence roads are more important generators of continuous runoff. The S-A relation noted above should not be applied outside the town where the road network is less dense. In contrast, the S-Lc relation may be used in both the town and rural areas underlain by porous soils where roads are the only generators of continuous runoff. We further conclude that the high town of Kinshasa is one of the most vulnerable places for gullying, and gullying can potentially transform the town into a badland. ‘Artisanal’ gully treatment is more successful than generally believed and the S-Lc relation can be a tool for mega-gully prevention.

Towards spatially distributed flood forecasts in flash flood prone areas: application to the supervision of a road network in the South of France

NASA Astrophysics Data System (ADS)

Naulin, Jean-Philippe; Payrastre, Olivier; Gaume, Eric; Delrieu, Guy

2013-04-01

Accurate flood forecasts are crucial for an efficient flood event management. Until now, hydro-meteorological forecasts have been mainly used for early-warnings in France (Meteorological and flood vigilance maps) or over the world (Flash-flood guidances). These forecasts are generally limited to the main streams covered by the flood forecasting services or to specific watersheds with particular assets like check dams which are in most cases well gauged river sections, leaving aside large parts of the territory. A distributed hydro-meteorological forecasting approach will be presented, able to take advantage of the high spatial and temporal resolution rainfall estimates that are now available to provide information at ungauged sites. The proposed system aiming at detecting road inundation risks had been initially developed and tested in areas of limited size. Its extension to a whole region (the Gard region in the South of France) will be presented, including over 2000 crossing points between rivers and roads and its validation against a large data set of actually reported road inundations observed during recent flash-flood events. These first validation results appear promising. Such a tool would provide the necessary information for flood event management services to identify the areas at risk and to take the appropriate safety and rescue measures: pre-positioning of rescue means, stopping of the traffic on exposed roads, determination of safe accesses or evacuation routes. Moreover, beyond the specific application to the supervision of a road network, this work provides also results concerning the performances of hydro-meteorological forecasts for ungauged headwaters.

Finite plateau in spectral gap of polychromatic constrained random networks

NASA Astrophysics Data System (ADS)

Avetisov, V.; Gorsky, A.; Nechaev, S.; Valba, O.

2017-12-01

We consider critical behavior in the ensemble of polychromatic Erdős-Rényi networks and regular random graphs, where network vertices are painted in different colors. The links can be randomly removed and added to the network subject to the condition of the vertex degree conservation. In these constrained graphs we run the Metropolis procedure, which favors the connected unicolor triads of nodes. Changing the chemical potential, μ , of such triads, for some wide region of μ , we find the formation of a finite plateau in the number of intercolor links, which exactly matches the finite plateau in the network algebraic connectivity (the value of the first nonvanishing eigenvalue of the Laplacian matrix, λ2). We claim that at the plateau the spontaneously broken Z2 symmetry is restored by the mechanism of modes collectivization in clusters of different colors. The phenomena of a finite plateau formation holds also for polychromatic networks with M ≥2 colors. The behavior of polychromatic networks is analyzed via the spectral properties of their adjacency and Laplacian matrices.

Value of ITS information for congestion avoidance in inter-modal transportation systems : phase II.

DOT National Transportation Integrated Search

2010-03-01

Our project has four major mile-stones for the second year: : Mile-stone #1: Develop Dynamic Inter-modal Transportation Optimization Models: For : mostly air-road network and inter-modal networks significant to OHIO : MICHIGAN regions and our col...

Point-Cloud Compression for Vehicle-Based Mobile Mapping Systems Using Portable Network Graphics

NASA Astrophysics Data System (ADS)

Kohira, K.; Masuda, H.

2017-09-01

A mobile mapping system is effective for capturing dense point-clouds of roads and roadside objects Point-clouds of urban areas, residential areas, and arterial roads are useful for maintenance of infrastructure, map creation, and automatic driving. However, the data size of point-clouds measured in large areas is enormously large. A large storage capacity is required to store such point-clouds, and heavy loads will be taken on network if point-clouds are transferred through the network. Therefore, it is desirable to reduce data sizes of point-clouds without deterioration of quality. In this research, we propose a novel point-cloud compression method for vehicle-based mobile mapping systems. In our compression method, point-clouds are mapped onto 2D pixels using GPS time and the parameters of the laser scanner. Then, the images are encoded in the Portable Networking Graphics (PNG) format and compressed using the PNG algorithm. In our experiments, our method could efficiently compress point-clouds without deteriorating the quality.

Interactive, graphical processing unitbased evaluation of evacuation scenarios at the state scale

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perumalla, Kalyan S; Aaby, Brandon G; Yoginath, Srikanth B

2011-01-01

In large-scale scenarios, transportation modeling and simulation is severely constrained by simulation time. For example, few real- time simulators scale to evacuation traffic scenarios at the level of an entire state, such as Louisiana (approximately 1 million links) or Florida (2.5 million links). New simulation approaches are needed to overcome severe computational demands of conventional (microscopic or mesoscopic) modeling techniques. Here, a new modeling and execution methodology is explored that holds the potential to provide a tradeoff among the level of behavioral detail, the scale of transportation network, and real-time execution capabilities. A novel, field-based modeling technique and its implementationmore » on graphical processing units are presented. Although additional research with input from domain experts is needed for refining and validating the models, the techniques reported here afford interactive experience at very large scales of multi-million road segments. Illustrative experiments on a few state-scale net- works are described based on an implementation of this approach in a software system called GARFIELD. Current modeling cap- abilities and implementation limitations are described, along with possible use cases and future research.« less

Motion planning with complete knowledge using a colored SOM.

PubMed

Vleugels, J; Kok, J N; Overmars, M

1997-01-01

The motion planning problem requires that a collision-free path be determined for a robot moving amidst a fixed set of obstacles. Most neural network approaches to this problem are for the situation in which only local knowledge about the configuration space is available. The main goal of the paper is to show that neural networks are also suitable tools in situations with complete knowledge of the configuration space. In this paper we present an approach that combines a neural network and deterministic techniques. We define a colored version of Kohonen's self-organizing map that consists of two different classes of nodes. The network is presented with random configurations of the robot and, from this information, it constructs a road map of possible motions in the work space. The map is a growing network, and different nodes are used to approximate boundaries of obstacles and the Voronoi diagram of the obstacles, respectively. In a second phase, the positions of the two kinds of nodes are combined to obtain the road map. In this way a number of typical problems with small obstacles and passages are avoided, and the required number of nodes for a given accuracy is within reasonable limits. This road map is searched to find a motion connecting the given source and goal configurations of the robot. The algorithm is simple and general; the only specific computation that is required is a check for intersection of two polygons. We implemented the algorithm for planar robots allowing both translation and rotation and experiments show that compared to conventional techniques it performs well, even for difficult motion planning scenes.

An experimental study of the Online Information Paradox: Does en-route information improve road network performance?

PubMed

Wijayaratna, Kasun P; Dixit, Vinayak V; Denant-Boemont, Laurent; Waller, S Travis

2017-01-01

This study investigates the empirical presence of a theoretical transportation paradox, defined as the "Online Information Paradox" (OIP). The paradox suggests that, for certain road networks, the provision of online information deteriorate travel conditions for all users of that network relative to the situation where no online information is provided to users. The analytical presence of the paradox was derived for a specific network structure by using two equilibrium models, the first being the Expected User Equilibrium (EUE) solution (no information scenario) and the other being the User Equilibrium with Recourse (UER) solution (with information scenario). An incentivised computerised route choice game was designed using the concepts of experimental economics and administered in a controlled laboratory environment to investigate the physical presence of the paradox. Aggregate statistics of path flows and Total System Travel Costs (TSTC) were used to compare the experimental results with the theoretical findings. A total of 12 groups of 12 participants completed the experiment and the OIP and the occurrence of the OIP being significant was observed in 11 of the 12 cases. Though information increased travel costs for users on average, it reduced the volatility of travel costs experienced in the no information scenario indicating that information can achieve a more reliable system. Further replications of similar experiments and more importantly field based identification of the phenomena will force transport professionals to be aware of the emergence of the paradox. In addition, studies such as this emphasise the need for the adoption of adaptive traffic assignment techniques to appropriately model the acquisition of information on a road network.

Supporting and Constraining Factors in the Development of University Teaching Experienced by Teachers

ERIC Educational Resources Information Center

Jääskelä, Päivikki; Häkkinen, Päivi; Rasku-Puttonen, Helena

2017-01-01

Higher education calls for reform, but deeper knowledge about the prerequisites for teaching development and pedagogical change is missing. In this study, 51 university teachers' experiences of supportive or constraining factors in teaching development were investigated in the context of Finland's multidisciplinary network. The findings reveal…

A Near-Optimal Distributed QoS Constrained Routing Algorithm for Multichannel Wireless Sensor Networks

PubMed Central

Lin, Frank Yeong-Sung; Hsiao, Chiu-Han; Yen, Hong-Hsu; Hsieh, Yu-Jen

2013-01-01

One of the important applications in Wireless Sensor Networks (WSNs) is video surveillance that includes the tasks of video data processing and transmission. Processing and transmission of image and video data in WSNs has attracted a lot of attention in recent years. This is known as Wireless Visual Sensor Networks (WVSNs). WVSNs are distributed intelligent systems for collecting image or video data with unique performance, complexity, and quality of service challenges. WVSNs consist of a large number of battery-powered and resource constrained camera nodes. End-to-end delay is a very important Quality of Service (QoS) metric for video surveillance application in WVSNs. How to meet the stringent delay QoS in resource constrained WVSNs is a challenging issue that requires novel distributed and collaborative routing strategies. This paper proposes a Near-Optimal Distributed QoS Constrained (NODQC) routing algorithm to achieve an end-to-end route with lower delay and higher throughput. A Lagrangian Relaxation (LR)-based routing metric that considers the “system perspective” and “user perspective” is proposed to determine the near-optimal routing paths that satisfy end-to-end delay constraints with high system throughput. The empirical results show that the NODQC routing algorithm outperforms others in terms of higher system throughput with lower average end-to-end delay and delay jitter. In this paper, for the first time, the algorithm shows how to meet the delay QoS and at the same time how to achieve higher system throughput in stringently resource constrained WVSNs.

The road maintenance funding models in Indonesia use earmarked tax

NASA Astrophysics Data System (ADS)

Gultom, Tiopan Henry M.; Tamin, Ofyar Z.; Sjafruddin, Ade; Pradono

2017-11-01

One of the solutions to get a sustainable road maintenance fund is to separate road sector revenue from other accounts, afterward, form a specific account for road maintenance. In 2001, Antameng and the Ministry of Public Works proposed a road fund model in Indonesia. Sources of the road funds proposal was a tariff formed on the nominal total tax. The policy of road funds was proposed to finance the road network maintenance of districts and provincials. This research aims to create a policy model of road maintenance funds in Indonesia using an earmarked tax mechanism. The research method is qualitative research, with data collection techniques are triangulation. Interview methods conducted were semi-structured. Strength, Weakness, Opportunities, and Threat from every part of the models were showen on the survey format. Respondents were representative of executives who involved directly against the financing of road maintenance. Validation model conducted by a discussion panel, it was called the Focus Group Discussion (FGD). The FGD involved all selected respondents. Road maintenance financing model that most appropriately applied in Indonesia was a model of revenue source use an earmarked PBBKB, PKB and PPnBM. Revenue collection mechanism was added tariff of registered vehicle tax (PKB), Vehicle Fuel Tax (PBBKB) and the luxury vehicle sales tax (PPnBM). The funds are managed at the provincial level by a public service agency.

Road Extraction from AVIRIS Using Spectral Mixture and Q-Tree Filter Techniques

NASA Technical Reports Server (NTRS)

Gardner, Margaret E.; Roberts, Dar A.; Funk, Chris; Noronha, Val

2001-01-01

Accurate road location and condition information are of primary importance in road infrastructure management. Additionally, spatially accurate and up-to-date road networks are essential in ambulance and rescue dispatch in emergency situations. However, accurate road infrastructure databases do not exist for vast areas, particularly in areas with rapid expansion. Currently, the US Department of Transportation (USDOT) extends great effort in field Global Positioning System (GPS) mapping and condition assessment to meet these informational needs. This methodology, though effective, is both time-consuming and costly, because every road within a DOT's jurisdiction must be field-visited to obtain accurate information. Therefore, the USDOT is interested in identifying new technologies that could help meet road infrastructure informational needs more effectively. Remote sensing provides one means by which large areas may be mapped with a high standard of accuracy and is a technology with great potential in infrastructure mapping. The goal of our research is to develop accurate road extraction techniques using high spatial resolution, fine spectral resolution imagery. Additionally, our research will explore the use of hyperspectral data in assessing road quality. Finally, this research aims to define the spatial and spectral requirements for remote sensing data to be used successfully for road feature extraction and road quality mapping. Our findings will facilitate the USDOT in assessing remote sensing as a new resource in infrastructure studies.

An experimental evaluation of potential scavenger effects on snake road mortality detections

USGS Publications Warehouse

Hubbard, Kaylan A.; Chalfoun, Anna D.

2012-01-01

As road networks expand and collisions between vehicles and wildlife become more common, accurately quantifying mortality rates for the taxa that are most impacted will be critical. Snakes are especially vulnerable to collisions with vehicles because of their physiology and behavior. Reptile road mortality is typically quantified using driving or walking surveys; however, scavengers can rapidly remove carcasses from the road and cause underestimation of mortality. Our objective was to determine the effect that scavengers might have had on our ability to accurately detect reptile road mortality during over 150 h and 4,000 km of driving surveys through arid shrublands in southwest Wyoming, which resulted in only two observations of mortality. We developed unique simulated snake carcasses out of Burbot (Lota lota), a locally invasive fish species, and examined removal rates across three different road types at three study sites. Carcass size was not a significant predictor of time of removal, and carcass removal was comparable during the daytime and nighttime hours. However, removal of simulated carcasses was higher on paved roads than unpaved or two-track roads at all study sites, with an average of 75% of the carcasses missing within 60 h compared to 34% and 31%, respectively. Scavengers may therefore negatively impact the ability of researchers to accurately detect herpetofaunal road mortality, especially for paved roads where road mortality is likely the most prevalent.

Forage Harvest and Transport Costs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Butler, J.; Downing, M.; Turhollow, A.

An engineering-economic approach is used to calculate harvest, in-field transport, and over-the-road transport costs for hay as bales and modules, silage, and crop residues as bales and modules. Costs included are equipment depreciation interest; fuel, lube, and oil; repairs; insurance, housing, and taxes; and labor. Field preparation, pest control, fertilizer, land, and overhead are excluded from the costs calculated Equipment is constrained by power available, throughput or carrying capacity, and field speed.

Intelligent Transport Systems in the Management of Road Transportation

NASA Astrophysics Data System (ADS)

Kalupová, Blanka; Hlavoň, Ivan

2016-11-01

Extension of European Union causes increase of free transfer of people and goods. At the same time they raised the problems associated with the transport, e.g. congestion and related accidents on roads, air traffic delays and more. To increase the efficiency and safety of transport, the European Commission supports the introduction of intelligent transport systems and services in all transport sectors. Implementation of intelligent transport systems and services in the road transport reduces accident frequency, increases the capacity of existing infrastructure and reduces congestions. Use of toll systems provides resources needed for the construction and operation of a new road network, improves public transport, cycling transport and walking transport, and also their multimodal integration with individual car transport.

Retrieval Algorithms for Road Surface Modelling Using Laser-Based Mobile Mapping.

PubMed

Jaakkola, Anttoni; Hyyppä, Juha; Hyyppä, Hannu; Kukko, Antero

2008-09-01

Automated processing of the data provided by a laser-based mobile mapping system will be a necessity due to the huge amount of data produced. In the future, vehiclebased laser scanning, here called mobile mapping, should see considerable use for road environment modelling. Since the geometry of the scanning and point density is different from airborne laser scanning, new algorithms are needed for information extraction. In this paper, we propose automatic methods for classifying the road marking and kerbstone points and modelling the road surface as a triangulated irregular network. On the basis of experimental tests, the mean classification accuracies obtained using automatic method for lines, zebra crossings and kerbstones were 80.6%, 92.3% and 79.7%, respectively.

Automatic extraction of road features in urban environments using dense ALS data

NASA Astrophysics Data System (ADS)

Soilán, Mario; Truong-Hong, Linh; Riveiro, Belén; Laefer, Debra

2018-02-01

This paper describes a methodology that automatically extracts semantic information from urban ALS data for urban parameterization and road network definition. First, building façades are segmented from the ground surface by combining knowledge-based information with both voxel and raster data. Next, heuristic rules and unsupervised learning are applied to the ground surface data to distinguish sidewalk and pavement points as a means for curb detection. Then radiometric information was employed for road marking extraction. Using high-density ALS data from Dublin, Ireland, this fully automatic workflow was able to generate a F-score close to 95% for pavement and sidewalk identification with a resolution of 20 cm and better than 80% for road marking detection.

A Vulnerability Index and Analysis for the Road Network of Rural Chile

NASA Astrophysics Data System (ADS)

Braun, Andreas; Stötzer, Johanna; Kubisch, Susanne; Dittrich, Andre; Keller, Sina

2017-04-01

Natural hazards impose considerable threats to the physical and socio-economic wellbeing of people, a fact, which is well understood and investigated for many regions. However, not only people are vulnerable. During the last decades, a considerable amount of literature has focussed the particular vulnerability of the critical infrastructure: for example road networks. Considering critical infrastructure, far less reliable information exists for many regions worldwide - particularly, regions outside of the so called developed world. Critical infrastructure is destroyed in many disasters, causing cascade and follow up effects, for instance, impediments during evacuation, rescue and during the resilience phase. These circumstances, which are general enough to be applied to most regions, aggravate in regions characterized by high disparities between the urban and the rural sphere. Peripheral rural areas are especially prone to get isolated due to defects of the few roads which connect them to larger urban centres (where, frequently, disaster and emergency actors are situated). The rural area of Central Chile is a appropriate example for these circumstances. It is prone to destruction by several geo-hazards and furthermore, characterized by the aforementioned disparities. Past disasters, e.g. the 1991 Cerro Hudson eruption and the 2010 Maule earthquake have led to follow up effects (e.g. farmers, being unable to evacuate their animals due to road failures in the first case, and difficultires to evacuate people from places such as Caleta Tumbes or Dichato, which are connected by just a single road only in the second). The contribution develops a methodology to investigate into the critical infrastructure of such places. It develops a remoteness index for Chile, which identifies remote, peripheral rural areas, prone to get isolated due to road network failures during disasters. The approach is graph based. It offers particular advantages for regions like rural Chile since 1. it does not require traffic flow data which do not exist, 2. identifies peripheral areas particularly well, 3. identifies both nodes (places) prone to isolation and edges (roads) critical for the connectivity of rural areas, 4. based on a mathematical structure, it implies several possible planning solutions to reduce vulnerability of the critical infrastructure and people dependent on it. The methodology is presented and elaborated theoretically. Afterwards, it is demonstrated on an actual dataset from central Chile. It is demonstrated, how the methodology can be applied to derive planning solutions for peripheral rural areas.

Assessment of on-road transportation demand and CO2 emissions for determination of air quality impacts from the Megacity of São Paulo

NASA Astrophysics Data System (ADS)

Perez-Martinez, P. J.; Miranda, R. M.; Andrade, M. D. F.

2017-12-01

In this manuscript we assess the capability of using mobility surveys and a high-scale assignment and emission model to study climate change and air quality impacts related to on-road transportation in the Megacity of São Paulo (MSP). Initially, we estimate CO2 emissions of light and heavy vehicles (LVs and HVs) at a spatial scale of 500m and temporal scale of an hour, using transport demand modeling. The estimates are based on origin and destination trip pairs and the height of the planetary boundary layer (PBL). These estimates, performed for the years 2007 and 2012, depend also on intermediate variables as dilution rates (D) and surface particulate-matter concentrations (PM). Secondly, we assess the changes in CO2 vehicle emissions from the MRSP over the period 2007-2012 (4% year-1). Consequently, CO2 emission inventories merge trip-based surveys, traffic assignments and road network database with air pollution monitoring data. Despite the difference of the methodologies, we use a road link bottom up vehicle activity based approach, the assessed emissions agree with the State's Emission Inventory. This paper shows that the CO2 emissions from LDVs and HDVs in the MSP in 2007 and 2012 were 8,477 and 10,075 tCeq day-1 (58% LVs and 42% HVs), respectively. CO2 emissions from vehicles show spatial patterns consistent with passenger and freight transport trips and road network assignments. Temporal profiles (diurnal, weekly and monthly) were estimated using traffic counts and congestion surrogates. The profiles were compared with average road-site (Western of MSP) and background (Jaraguá Peak) CO2 measurements available for 2014. On-road measurements showed one peak associated to the morning peak hour of vehicles (437±45 ppm) and another night peak (435±49 ppm) related to the low PBL (313 m) and D (329 m2 h-1). From on-road measurements, background values (414±2 ppm) were subtracted to estimate excess CO2 (12±8 ppm) directly attributed to vehicles. The inventory reflects the relationships between traffic patterns and emissions, and the developed methodology could be used to evaluate the impacts of forthcoming urban transport and emission control policies. In the future, our estimates will be verified with ground measurements of CO2 concentrations over a bigger monitoring network in the MSP.

Social Network Mapping: A New Tool For The Leadership Toolbox

DTIC Science & Technology

2002-04-01

SOCIAL NETWORK MAPPING: A NEW TOOL FOR THE LEADERSHIP TOOLBOX By Elisabeth J. Strines, Colonel, USAF 8037 Washington Road Alexandria...valid OMB control number. 1. REPORT DATE 00 APR 2002 2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE Social Network Mapping: A...describes the concept of social network mapping and demonstrates how it can be used by squadron commanders and leaders at all levels to provide subtle

Network Science Center Research Team’s Visit to Kampala, Uganda

DTIC Science & Technology

2013-04-15

Leader • Someone in Social Network • Commercial Bank • White Collar Professional • Military Leader 16 | P a g e Network Science Center, West Point www.netscience.usma.edu 845.938.0804 ...regions, where the Lord’s Resistance Army 2 | P a g e Network Science Center, West Point www.netscience.usma.edu 845.938.0804 (LRA), a militant...Non-Governmental Organizations. Teddy Ruge Kanjokya Road in Kamwokya 3 | P a g e Network Science Center, West Point

Nomadic ecology shaped the highland geography of Asia’s Silk Roads

NASA Astrophysics Data System (ADS)

Frachetti, Michael D.; Smith, C. Evan; Traub, Cynthia M.; Williams, Tim

2017-03-01

There are many unanswered questions about the evolution of the ancient ‘Silk Roads’ across Asia. This is especially the case in their mountainous stretches, where harsh terrain is seen as an impediment to travel. Considering the ecology and mobility of inner Asian mountain pastoralists, we use ‘flow accumulation’ modelling to calculate the annual routes of nomadic societies (from 750 m to 4,000 m elevation). Aggregating 500 iterations of the model reveals a high-resolution flow network that simulates how centuries of seasonal nomadic herding could shape discrete routes of connectivity across the mountains of Asia. We then compare the locations of known high-elevation Silk Road sites with the geography of these optimized herding flows, and find a significant correspondence in mountainous regions. Thus, we argue that highland Silk Road networks (from 750 m to 4,000 m) emerged slowly in relation to long-established mobility patterns of nomadic herders in the mountains of inner Asia.

Ontology-Based Architecture for Intelligent Transportation Systems Using a Traffic Sensor Network.

PubMed

Fernandez, Susel; Hadfi, Rafik; Ito, Takayuki; Marsa-Maestre, Ivan; Velasco, Juan R

2016-08-15

Intelligent transportation systems are a set of technological solutions used to improve the performance and safety of road transportation. A crucial element for the success of these systems is the exchange of information, not only between vehicles, but also among other components in the road infrastructure through different applications. One of the most important information sources in this kind of systems is sensors. Sensors can be within vehicles or as part of the infrastructure, such as bridges, roads or traffic signs. Sensors can provide information related to weather conditions and traffic situation, which is useful to improve the driving process. To facilitate the exchange of information between the different applications that use sensor data, a common framework of knowledge is needed to allow interoperability. In this paper an ontology-driven architecture to improve the driving environment through a traffic sensor network is proposed. The system performs different tasks automatically to increase driver safety and comfort using the information provided by the sensors.

Ontology-Based Architecture for Intelligent Transportation Systems Using a Traffic Sensor Network

PubMed Central

Fernandez, Susel; Hadfi, Rafik; Ito, Takayuki; Marsa-Maestre, Ivan; Velasco, Juan R.

2016-01-01

Intelligent transportation systems are a set of technological solutions used to improve the performance and safety of road transportation. A crucial element for the success of these systems is the exchange of information, not only between vehicles, but also among other components in the road infrastructure through different applications. One of the most important information sources in this kind of systems is sensors. Sensors can be within vehicles or as part of the infrastructure, such as bridges, roads or traffic signs. Sensors can provide information related to weather conditions and traffic situation, which is useful to improve the driving process. To facilitate the exchange of information between the different applications that use sensor data, a common framework of knowledge is needed to allow interoperability. In this paper an ontology-driven architecture to improve the driving environment through a traffic sensor network is proposed. The system performs different tasks automatically to increase driver safety and comfort using the information provided by the sensors. PMID:27537878

Use of certain alternative fuels in road transport in Poland

NASA Astrophysics Data System (ADS)

Gis, W.; Pielecha, J.; Waśkiewicz, J.; Gis, M.; Menes, M.

2016-09-01

The development of biomethane and hydrogen technology in the road transport in the EU countries is recommended, among the others, in the Directive of the European Parliament and of the Council 2014/94/EU of 22 October 2014. Under the provisions of the said Directive, it is recommended to EU countries to use biomethane and progressively ensure accessibility to hydrogen cars on their territories, and above all to ensure the possibility of driving hydrogen vehicles between the member States. The territorial accessibility for biomethane vehicles is determined by the availability of biomethane refuelling infrastructure in the first place in cities and then on the road network distances recommended in this directive. The territorial accessibility for hydrogen vehicles is determined by the availability of hydrogen refuelling infrastructure, in the first place along the TEN-T network. The article presents the possibilities of using these alternative fuels in Poland, presenting some of the results of research and analysis in this area.

Influence of forest roads standards and networks on water yield as predicted by the distributed hydrology-soil-vegetation model

Treesearch

Salli F. Dymond; W. Michael Aust; Steven P. Prisley; Mark H. Eisenbies; James M. Vose

2013-01-01

Throughout the country, foresters are continually looking at the effects of logging and forest roads on stream discharge and overall stream health. In the Pacific Northwest, a distributed hydrology-soil-vegetation model (DHSVM) has been used to predict the effects of logging on peak discharge in mountainous regions. DHSVM uses elevation, meteorological, vegetation, and...

Spread of invasive plants from roads to river systems in Alaska: a network model

Treesearch

Tricia L. Wurtz; Matt J. Spellman Macander

2010-01-01

Alaska has relatively few invasive plants, and most of them are found only along the state’s limited road system. One of the most widely distributed invasives in the state, Melilotus alba Medik., or sweetclover, has been sown both as a forage crop and as a roadside stabilization species. Melilotus has recently been found to...

Optimization design of urban expressway ramp control

NASA Astrophysics Data System (ADS)

Xu, Hongke; Li, Peiqi; Zheng, Jinnan; Sun, Xiuzhen; Lin, Shan

2017-05-01

In this paper, various types of expressway systems are analyzed, and a variety of signal combinations are proposed to mitigate traffic congestion. And various signal combinations are used to verify the effectiveness of the multi-signal combinatorial control strategy. The simulation software VISSIM was used to simulate the system. Based on the network model of 25 kinds of road length combinations and the simulation results, an optimization scheme suitable for the practical road model is summarized. The simulation results show that the controller can reduce the travel time by 25% under the large traffic flow and improve the road capacity by about 20%.

Interpreting stream sediment fingerprints against primary and secondary source signatures in agricultural catchments

NASA Astrophysics Data System (ADS)

Blake, Will H.; Haley, Steve; Smith, Hugh G.; Taylor, Alex; Goddard, Rupert; Lewin, Sean; Fraser, David

2013-04-01

Many sediment fingerprinting studies adopt a black box approach to source apportionment whereby the properties of downstream sediment are compared quantitatively to the geochemical fingerprints of potential catchment sources without consideration of potential signature development or modification during transit. Working within a source-pathway-receptor framework, this study aimed to undertake sediment source apportionment within 6 subcatchments of an agricultural river basin with specific attention to the potential role of contaminants (vehicle emissions and mine waste) in development of stream sediment signatures. Fallout radionuclide (FRN) and geochemical fingerprinting methods were adopted independently to establish source signatures for primary sediment sources of surface and subsurface soil materials under various land uses plus reworked mine and 'secondary' soil material deposited, in transit, along road networks. FRN data demonstrated expected variability between surface soil (137Cs = 14 ± 3 Bq kg-1; 210Pbxs = 40 ± 7 Bq kg-1) and channel bank materials (137Cs = 3 ± 1 Bq kg-1; 210Pbxs = 24 ± 5 Bq kg-1) but road transported soil material was considerably elevated in 210Pbxs (up to 673 ± 51 Bq kg-1) due to sediment interaction with pluvial surface water within the road network. Geochemical discrimination between surface and subsurface soil materials was dominated by alkaline earth and alkali metals e.g. Ba, Rb, Ca, K, Mg which are sensitive to weathering processes in soil. Magnetic susceptibility and heavy metals were important discriminators of road transported material which demonstrated transformation of the signatures of material transported via the road network. Numerical unmixing of stream sediment indicated that alongside channel bank erosion, road transported material was an important component in some systems in accord with FRN evidence. While mining spoil also ranked as a significant source in an affected catchment, perhaps related to legacy sediment, the potential role of dissolved metal leaching and subsequent sediment-water interaction within the channel on signature modification remained unclear. Consideration of sediment signature modification en route from primary source to stream elucidated important information regarding sediment transfer pathways and dynamics relevant to sediment management decisions. Further work on sediment-water interactions and potential for signature transformation in the channel environment is required.

Neuroticism and conscientiousness respectively constrain and facilitate short-term plasticity within the working memory neural network.

PubMed

Dima, Danai; Friston, Karl J; Stephan, Klaas E; Frangou, Sophia

2015-10-01

Individual differences in cognitive efficiency, particularly in relation to working memory (WM), have been associated both with personality dimensions that reflect enduring regularities in brain configuration, and with short-term neural plasticity, that reflects task-related changes in brain connectivity. To elucidate the relationship of these two divergent mechanisms, we tested the hypothesis that personality dimensions, which reflect enduring aspects of brain configuration, inform about the neurobiological framework within which short-term, task-related plasticity, as measured by effective connectivity, can be facilitated or constrained. As WM consistently engages the dorsolateral prefrontal (DLPFC), parietal (PAR), and anterior cingulate cortex (ACC), we specified a WM network model with bidirectional, ipsilateral, and contralateral connections between these regions from a functional magnetic resonance imaging dataset obtained from 40 healthy adults while performing the 3-back WM task. Task-related effective connectivity changes within this network were estimated using Dynamic Causal Modelling. Personality was evaluated along the major dimensions of Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness. Only two dimensions were relevant to task-dependent effective connectivity. Neuroticism and Conscientiousness respectively constrained and facilitated neuroplastic responses within the WM network. These results suggest individual differences in cognitive efficiency arise from the interplay between enduring and short-term plasticity in brain configuration. © 2015 Wiley Periodicals, Inc.

SAE for the prediction of road traffic status from taxicab operating data and bus smart card data

NASA Astrophysics Data System (ADS)

Zhengfeng, Huang; Pengjun, Zheng; Wenjun, Xu; Gang, Ren

Road traffic status is significant for trip decision and traffic management, and thus should be predicted accurately. A contribution is that we consider multi-modal data for traffic status prediction than only using single source data. With the substantial data from Ningbo Passenger Transport Management Sector (NPTMS), we wished to determine whether it was possible to develop Stacked Autoencoders (SAEs) for accurately predicting road traffic status from taxicab operating data and bus smart card data. We show that SAE performed better than linear regression model and Back Propagation (BP) neural network for determining the relationship between road traffic status and those factors. In a 26-month data experiment using SAE, we show that it is possible to develop highly accurate predictions (91% test accuracy) of road traffic status from daily taxicab operating data and bus smart card data.

Strategies for prevention of road traffic injuries (RTIs) in Pakistan: situational analysis.

PubMed

Khan, Adeel Ahmed; Fatmi, Zafar

2014-05-01

Road traffic injuries (RTIs) are one of the leading causes of death among productive age group. Using systems approach framework (SAF), current preventive strategies for RTI control were reviewed in Pakistan. A review of the literature was done using four international search engines. Only ten studies on preventive strategies for RTI stemming from Pakistan were found. The first Road Traffic Injuries Research Network (RTIRN) surveillance system for road traffic injuries was established in urban city (Karachi) in Pakistan has shown promise for injury control and should be scaled up to other cities. Enforcement of traffic laws on seat-belt and helmet wearing is poor. National Highway and Motorway Police Ordinance (2000) was one of the few legislative measure so far taken in Pakistan. Using SAF, efforts are required to implement interventions targeting human, vehicle design and also making environment safer for road users.

Automatic Centerline Extraction of Coverd Roads by Surrounding Objects from High Resolution Satellite Images

NASA Astrophysics Data System (ADS)

Kamangir, H.; Momeni, M.; Satari, M.

2017-09-01

This paper presents an automatic method to extract road centerline networks from high and very high resolution satellite images. The present paper addresses the automated extraction roads covered with multiple natural and artificial objects such as trees, vehicles and either shadows of buildings or trees. In order to have a precise road extraction, this method implements three stages including: classification of images based on maximum likelihood algorithm to categorize images into interested classes, modification process on classified images by connected component and morphological operators to extract pixels of desired objects by removing undesirable pixels of each class, and finally line extraction based on RANSAC algorithm. In order to evaluate performance of the proposed method, the generated results are compared with ground truth road map as a reference. The evaluation performance of the proposed method using representative test images show completeness values ranging between 77% and 93%.

CSR: Constrained Selfish Routing in Ad-Hoc Networks

NASA Astrophysics Data System (ADS)

Bassem, Christine; Bestavros, Azer

Routing protocols for ad-hoc networks assume that the nodes forming the network are either under a single authority, or else that they would be altruistically forwarding data for other nodes with no expectation of a return. These assumptions are unrealistic since in ad-hoc networks, nodes are likely to be autonomous and rational (selfish), and thus unwilling to help unless they have an incentive to do so. Providing such incentives is an important aspect that should be considered when designing ad-hoc routing protocols. In this paper, we propose a dynamic, decentralized routing protocol for ad-hoc networks that provides incentives in the form of payments to intermediate nodes used to forward data for others. In our Constrained Selfish Routing (CSR) protocol, game-theoretic approaches are used to calculate payments (incentives) that ensure both the truthfulness of participating nodes and the fairness of the CSR protocol. We show through simulations that CSR is an energy efficient protocol and that it provides lower communication overhead in the best and average cases compared to existing approaches.

A new transport phenomenon in nanostructures: a mesoscopic analog of the Braess paradox encountered in road networks

PubMed Central

2012-01-01

The Braess paradox, known for traffic and other classical networks, lies in the fact that adding a new route to a congested network in an attempt to relieve congestion can degrade counterintuitively the overall network performance. Recently, we have extended the concept of the Braess paradox to semiconductor mesoscopic networks, whose transport properties are governed by quantum physics. In this paper, we demonstrate theoretically that, alike in classical systems, congestion plays a key role in the occurrence of a Braess paradox in mesoscopic networks. PMID:22913510

Explorations Around "Graceful Failure" in Transportation Infrastructure: Lessons Learned By the Infrastructure and Climate Network (ICNet)

NASA Astrophysics Data System (ADS)

Jacobs, J. M.; Thomas, N.; Mo, W.; Kirshen, P. H.; Douglas, E. M.; Daniel, J.; Bell, E.; Friess, L.; Mallick, R.; Kartez, J.; Hayhoe, K.; Croope, S.

2014-12-01

Recent events have demonstrated that the United States' transportation infrastructure is highly vulnerable to extreme weather events which will likely increase in the future. In light of the 60% shortfall of the $900 billion investment needed over the next five years to maintain this aging infrastructure, hardening of all infrastructures is unlikely. Alternative strategies are needed to ensure that critical aspects of the transportation network are maintained during climate extremes. Preliminary concepts around multi-tier service expectations of bridges and roads with reference to network capacity will be presented. Drawing from recent flooding events across the U.S., specific examples for roads/pavement will be used to illustrate impacts, disruptions, and trade-offs between performance during events and subsequent damage. This talk will also address policy and cultural norms within the civil engineering practice that will likely challenge the application of graceful failure pathways during extreme events.

Regional transportation network blocked by snowdrifts: assessment of risk reduction strategies by the example of the wind event of February 2015 in the Canton of Vaud, Switzerland

NASA Astrophysics Data System (ADS)

Voumard, Jérémie; Jaboyedoff, Michel; Derron, Marc-Henri

2016-04-01

The 5-8th February, a meteorological situation characterized by a strong wind coming from the North generated many snowdrifts on roads and railways in the Canton of Vaud, Switzerland. The affected region, about 900 km2, is located on the Swiss Plateau. More than thirty roads and few railways were blocked during the event. On some areas, too many roads and railways tracks were closed to assure the school transports making obligatory the total closure of seven schools and the partial closure of three schools affecting 8'000 students, which is almost 10% of students of the Canton of Vaud. Over hundred vehicles blocked in the snowdrifts had to be unobstructed. Over 150 snowplows drivers were requisitioned but the wind with gusts of over 80 km/h was too strong to release the roads from the snow accumulation. The boat transport on the Lake Geneva was interrupted during three days because of the danger generated by the strong wind during the berths. This interruption generated up to 100 km deviation for commuting traffic. The county police recommended to the population to limit their travels on the road. The last roads closures due to snowdrifts in the Canton of Vaud occurred ten years ago, in 2005. This particular event that affected considerably the accessibility of a large area of the Canton of Vaud is interesting because results of a "simple" meteorological situation that strongly reduced the accessibility during four days of an area with a population of about 340'000. It raises several questions as for examples: how the emergency services accessibility is assured; what are the tools that can reduce the roads closures; what is the best road management to follow during such an event (which roads must be priority cleaned, which roads can be left covered by snow); how to prevent such an event, are snow fences enough to avoid snowdrifts or is there another way to limit their creation? To try obtaining answers to those questions, we assess the most critical infrastructures where an accessibility is crucial to be maintained. We analyze then the road network to highlight the roads vulnerability from snowdrifts with topographic and meteorological indicators. We also assess the ratio cost/benefit of different measures limiting snowdrifts. We finally discuss strategies to reduce the risk of this winter meteorological event.

Effects of roads and well pads on erosion in the Largo Canyon watershed, New Mexico, 2001-02

USGS Publications Warehouse

Matherne, Anne Marie

2006-01-01

Largo Canyon, located in the San Juan Basin of northwestern New Mexico, is one of the longest dry washes in the world. Oil and gas production in the San Juan Basin, which began in the 1940's, required the development of an extensive network of dirt roads to service the oil and gas wells in the Navajo Reservoir area. Presently, there are about eight wells per square mile, and the density of oil and gas wells is expected to increase. Potential environmental effects on landscape stability that may result from the additional roads and well pads have not been documented. In 2001, the U.S. Geological Survey began a study in cooperation with the Bureau of Land Management to evaluate the effects of roads and well pads associated with oil and gas operations on the erosion potential of Bureau of Land Management lands in the Largo Canyon watershed. The effects of roads and well pads on erosion were quantified by installing sediment dams (dams) and by surveying transects across roads and well pads. Data from 26 dams were used in the analysis. Dams were installed at 43 sites: 21 on hillsides upslope from roads or pads to measure erosion from hillslopes, 11 at the downslope edges of roads to measure erosion from roads, and 11 at the downslope edges of well pads to measure erosion from well pads. Pairs of survey transects were established at nine well pads and two road locations. Sediment-accumulation data for 26 dams, recorded at 17 measurement intervals, indicate that average erosion rates at the dams significantly correlate to size of the contributing area. The average erosion rate normalized by drainage area was 0.001 foot per year below roads, 0.003 foot per year on hillslopes, and 0.011 foot per year below well pads. Results of a two-sample t-test indicate that there was no significant difference in average erosion rates for dams located on hillslopes and below roads, whereas average erosion rates were significantly greater for dams below well pads than for dams on hillslopes and dams below roads. The average erosion rates estimated from the data collected during this study most likely represent minimum erosion rates. Sediment-accumulation data for measurement intervals and for dams that were breached during 2002, resulting from the large volume of runoff generated by high-intensity storms, were not used to compute erosion rates. For this reason, the higher range of erosion rates is underrepresented and the results of this study are biased toward the lower end of the range of erosion rates. Measurements along road transects generally indicate that sediment is eroded from the top of road berms and redeposited at the base of the berms and may be transported downslope along the road. Measurements along well-pad transects generally indicate that sediment eroded from hillslopes is transported over the surface of the well pad and down the well-pad edges. Based on field observations, roads aligned parallel to topographic contours facilitate erosional processes in two ways: (1) roads cut across and collect runoff from previously established drainages and (2) roads, where they are cut into hillsides or into the land surface, provide focal points for the initiation of erosion. Roads aligned across topographic contours can serve as conduits to channel runoff but do not constitute a large percentage of the road network.

76 FR 59482 - Petition for Waivers of Compliance

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-26

... States. It operates the largest rail network in Canada and the only transcontinental network in North... capability and limitations as provided to Norfolk Southern Railway to operate RoadRailer equipment by FRA in... (or signing the document, if submitted on behalf of an association, business, labor union, etc.). You...

Value of its information for congestion avoidance in inter-modal transportation systems : phase II, final report, March 2010.

DOT National Transportation Integrated Search

2010-03-01

Our project has four major mile-stones for the second year: : Mile-stone #1: Develop Dynamic Inter-modal Transportation Optimization Models: For : mostly air-road network and inter-modal networks significant to OHIO : MICHIGAN regions and our collabo...

From County Roads to Superhighway: Keeping Pace with the New Business and Legal Turns on the Information Superhighway.

ERIC Educational Resources Information Center

Gordon, Mark L.; McKenzie, Diana J. P.

1994-01-01

Discusses the development of a national information superhighway. Highlights include the National Information Infrastructure; NREN (National Research and Education Network); private networks, including Prodigy; repositioning in the telecommunications industry, including telephone, cable, and entertainment companies; government regulations;…

West Virginia forest industry transportation network analysis using GIS

Treesearch

Steven E. Harouff; Shawn T. Grushecky; Ben D. Spong

2008-01-01

To better understand and increase efficiency in delivery of harvested roundwood on West Virginia' roadways, a detailed network analysis using Geographic Information Systems (GIS) was conducted. Typical proximity-based analysis, which looks at straightline distances (buffers) around given features regardless of terrain and road characteristics, provides limited...

Dynamics of wood in stream networks of the western Cascades Range, Oregon

Treesearch

Nicole M. Czarnomski; David M. Dreher; Kai U. Snyder; Julia A. Jones; Frederick J. Swanson

2008-01-01

We develop and test a conceptual model of wood dynamics in stream networks that considers legacies of forest management practices, floods, and debris flows. We combine an observational study of wood in 25 km of 2nd- through 5th-order streams in a steep, forested watershed of the western Cascade Range of Oregon with whole-network studies of forest cutting, roads, and...

Constrained synaptic connectivity in functional mammalian neuronal networks grown on patterned surfaces.

PubMed

Wyart, Claire; Ybert, Christophe; Bourdieu, Laurent; Herr, Catherine; Prinz, Christelle; Chatenay, Didier

2002-06-30

The use of ordered neuronal networks in vitro is a promising approach to study the development and the activity of small neuronal assemblies. However, in previous attempts, sufficient growth control and physiological maturation of neurons could not be achieved. Here we describe an original protocol in which polylysine patterns confine the adhesion of cellular bodies to prescribed spots and the neuritic growth to thin lines. Hippocampal neurons in these networks are maintained healthy in serum free medium up to 5 weeks in vitro. Electrophysiology and immunochemistry show that neurons exhibit mature excitatory and inhibitory synapses and calcium imaging reveals spontaneous activity of neurons in isolated networks. We demonstrate that neurons in these geometrical networks form functional synapses preferentially to their first neighbors. We have, therefore, established a simple and robust protocol to constrain both the location of neuronal cell bodies and their pattern of connectivity. Moreover, the long term maintenance of the geometry and the physiology of the networks raises the possibility of new applications for systematic screening of pharmacological agents and for electronic to neuron devices.

Effect of resource constraints on intersimilar coupled networks.

PubMed

Shai, S; Dobson, S

2012-12-01

Most real-world networks do not live in isolation but are often coupled together within a larger system. Recent studies have shown that intersimilarity between coupled networks increases the connectivity of the overall system. However, unlike connected nodes in a single network, coupled nodes often share resources, like time, energy, and memory, which can impede flow processes through contention when intersimilarly coupled. We study a model of a constrained susceptible-infected-recovered (SIR) process on a system consisting of two random networks sharing the same set of nodes, where nodes are limited to interact with (and therefore infect) a maximum number of neighbors at each epidemic time step. We obtain that, in agreement with previous studies, when no limit exists (regular SIR model), positively correlated (intersimilar) coupling results in a lower epidemic threshold than negatively correlated (interdissimilar) coupling. However, in the case of the constrained SIR model, the obtained epidemic threshold is lower with negatively correlated coupling. The latter finding differentiates our work from previous studies and provides another step towards revealing the qualitative differences between single and coupled networks.

Effect of resource constraints on intersimilar coupled networks

NASA Astrophysics Data System (ADS)

Shai, S.; Dobson, S.

2012-12-01

Most real-world networks do not live in isolation but are often coupled together within a larger system. Recent studies have shown that intersimilarity between coupled networks increases the connectivity of the overall system. However, unlike connected nodes in a single network, coupled nodes often share resources, like time, energy, and memory, which can impede flow processes through contention when intersimilarly coupled. We study a model of a constrained susceptible-infected-recovered (SIR) process on a system consisting of two random networks sharing the same set of nodes, where nodes are limited to interact with (and therefore infect) a maximum number of neighbors at each epidemic time step. We obtain that, in agreement with previous studies, when no limit exists (regular SIR model), positively correlated (intersimilar) coupling results in a lower epidemic threshold than negatively correlated (interdissimilar) coupling. However, in the case of the constrained SIR model, the obtained epidemic threshold is lower with negatively correlated coupling. The latter finding differentiates our work from previous studies and provides another step towards revealing the qualitative differences between single and coupled networks.

Evaluating horizontal positional accuracy of low-cost UAV orthomosaics over forest terrain using ground control points extracted from different sources

NASA Astrophysics Data System (ADS)

Patias, Petros; Giagkas, Fotis; Georgiadis, Charalampos; Mallinis, Giorgos; Kaimaris, Dimitris; Tsioukas, Vassileios

2017-09-01

Within the field of forestry, forest road mapping and inventory plays an important role in management activities related to wood harvesting industry, sentiment and water run-off modelling, biodiversity distribution and ecological connectivity, recreation activities, future planning of forest road networks and wildfire protection and fire-fighting. Especially in countries of the Mediterranean Rim, knowledge at regional and national scales regarding the distribution and the characteristics of rural and forest road network is essential in order to ensure an effective emergency management and rapid response of the fire-fighting mechanism. Yet, the absence of accurate and updated geodatabases and the drawbacks related to the use of traditional cartographic methods arising from the forest environment settings, and the cost and efforts needed, as thousands of meters need to be surveyed per site, trigger the need for new data sources and innovative mapping approaches. Monitoring the condition of unpaved forest roads with unmanned aerial vehicle technology is an attractive option for substituting objective, laboursome surveys. Although photogrammetric processing of UAV imagery can achieve accuracy of 1-2 centimeters and dense point clouds, the process is commonly based on the establishment of control points. In the case of forest road networks, which are linear features, there is a need for a great number of control points. Our aim is to evaluate low-cost UAV orthoimages generated over forest areas with GCP's captured from existing national scale aerial orthoimagery, satellite imagery available through a web mapping service (WMS), field surveys using Mobile Mapping System and GNSS receiver. We also explored the direct georeferencing potential through the GNSS onboard the low cost UAV. The results suggest that the GNSS approach proved to most accurate, while the positional accuracy derived using the WMS and the aerial orthoimagery datasets deemed satisfactory for the specific task at hand. The direct georeferencing procedure seems to be insufficient unless an onboard GNSS with improved specifications or Real-Time Kinematic (RTK) capabilities is used.

An approach to plan and evaluate the location of radiotherapy services and its application in the New South Wales, Australia.

PubMed

Shukla, Nagesh; Wickramasuriya, Rohan; Miller, Andrew; Perez, Pascal

2015-11-01

This paper proposes an integrated modelling approach for location planning of radiotherapy treatment services based on cancer incidence and road network-based accessibility. Previous research efforts have established travel distance/time barriers as a key factor affecting access to cancer treatment services, as well as epidemiological studies have shown that cancer incidence rates vary with population demography. Our study is built on the evidence that the travel distances to treatment centres and demographic profiles of the accessible regions greatly influence the uptake of cancer radiotherapy (RT) services. An integrated service planning approach that combines spatially-explicit cancer incidence projections, and the placement of new RT services based on road network based accessibility measures have never been attempted. This research presents a novel approach for the location planning of RT services, and demonstrates its viability by modelling cancer incidence rates for different age-sex groups in New South Wales, Australia based on observed cancer incidence trends; and estimations of the road network-based access to current NSW treatment centres. Using three indices (General Efficiency, Service Availability and Equity), we show how the best location for a new RT centre may be chosen when there are multiple competing locations. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

UFCN: a fully convolutional neural network for road extraction in RGB imagery acquired by remote sensing from an unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Kestur, Ramesh; Farooq, Shariq; Abdal, Rameen; Mehraj, Emad; Narasipura, Omkar; Mudigere, Meenavathi

2018-01-01

Road extraction in imagery acquired by low altitude remote sensing (LARS) carried out using an unmanned aerial vehicle (UAV) is presented. LARS is carried out using a fixed wing UAV with a high spatial resolution vision spectrum (RGB) camera as the payload. Deep learning techniques, particularly fully convolutional network (FCN), are adopted to extract roads by dense semantic segmentation. The proposed model, UFCN (U-shaped FCN) is an FCN architecture, which is comprised of a stack of convolutions followed by corresponding stack of mirrored deconvolutions with the usage of skip connections in between for preserving the local information. The limited dataset (76 images and their ground truths) is subjected to real-time data augmentation during training phase to increase the size effectively. Classification performance is evaluated using precision, recall, accuracy, F1 score, and brier score parameters. The performance is compared with support vector machine (SVM) classifier, a one-dimensional convolutional neural network (1D-CNN) model, and a standard two-dimensional CNN (2D-CNN). The UFCN model outperforms the SVM, 1D-CNN, and 2D-CNN models across all the performance parameters. Further, the prediction time of the proposed UFCN model is comparable with SVM, 1D-CNN, and 2D-CNN models.

Remote sensing-based detection and quantification of roadway debris following natural disasters

NASA Astrophysics Data System (ADS)

Axel, Colin; van Aardt, Jan A. N.; Aros-Vera, Felipe; Holguín-Veras, José

2016-05-01

Rapid knowledge of road network conditions is vital to formulate an efficient emergency response plan following any major disaster. Fallen buildings, immobile vehicles, and other forms of debris often render roads impassable to responders. The status of roadways is generally determined through time and resource heavy methods, such as field surveys and manual interpretation of remotely sensed imagery. Airborne lidar systems provide an alternative, cost-effective option for performing network assessments. The 3D data can be collected quickly over a wide area and provide valuable insight about the geometry and structure of the scene. This paper presents a method for automatically detecting and characterizing debris in roadways using airborne lidar data. Points falling within the road extent are extracted from the point cloud and clustered into individual objects using region growing. Objects are classified as debris or non-debris using surface properties and contextual cues. Debris piles are reconstructed as surfaces using alpha shapes, from which an estimate of debris volume can be computed. Results using real lidar data collected after a natural disaster are presented. Initial results indicate that accurate debris maps can be automatically generated using the proposed method. These debris maps would be an invaluable asset to disaster management and emergency response teams attempting to reach survivors despite a crippled transportation network.

McMAC: Towards a MAC Protocol with Multi-Constrained QoS Provisioning for Diverse Traffic in Wireless Body Area Networks

PubMed Central

Monowar, Muhammad Mostafa; Hassan, Mohammad Mehedi; Bajaber, Fuad; Al-Hussein, Musaed; Alamri, Atif

2012-01-01

The emergence of heterogeneous applications with diverse requirements for resource-constrained Wireless Body Area Networks (WBANs) poses significant challenges for provisioning Quality of Service (QoS) with multi-constraints (delay and reliability) while preserving energy efficiency. To address such challenges, this paper proposes McMAC, a MAC protocol with multi-constrained QoS provisioning for diverse traffic classes in WBANs. McMAC classifies traffic based on their multi-constrained QoS demands and introduces a novel superframe structure based on the “transmit-whenever-appropriate” principle, which allows diverse periods for diverse traffic classes according to their respective QoS requirements. Furthermore, a novel emergency packet handling mechanism is proposed to ensure packet delivery with the least possible delay and the highest reliability. McMAC is also modeled analytically, and extensive simulations were performed to evaluate its performance. The results reveal that McMAC achieves the desired delay and reliability guarantee according to the requirements of a particular traffic class while achieving energy efficiency. PMID:23202224

Path Network Recovery Using Remote Sensing Data and Geospatial-Temporal Semantic Graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

William C. McLendon III; Brost, Randy C.

Remote sensing systems produce large volumes of high-resolution images that are difficult to search. The GeoGraphy (pronounced Geo-Graph-y) framework [2, 20] encodes remote sensing imagery into a geospatial-temporal semantic graph representation to enable high level semantic searches to be performed. Typically scene objects such as buildings and trees tend to be shaped like blocks with few holes, but other shapes generated from path networks tend to have a large number of holes and can span a large geographic region due to their connectedness. For example, we have a dataset covering the city of Philadelphia in which there is a singlemore » road network node spanning a 6 mile x 8 mile region. Even a simple question such as "find two houses near the same street" might give unexpected results. More generally, nodes arising from networks of paths (roads, sidewalks, trails, etc.) require additional processing to make them useful for searches in GeoGraphy. We have assigned the term Path Network Recovery to this process. Path Network Recovery is a three-step process involving (1) partitioning the network node into segments, (2) repairing broken path segments interrupted by occlusions or sensor noise, and (3) adding path-aware search semantics into GeoQuestions. This report covers the path network recovery process, how it is used, and some example use cases of the current capabilities.« less

Spatially distributed flood forecasting in flash flood prone areas: Application to road network supervision in Southern France

NASA Astrophysics Data System (ADS)

Naulin, J.-P.; Payrastre, O.; Gaume, E.

2013-04-01

SummaryAccurate flood forecasts are critical to an efficient flood event management strategy. Until now, hydro-meteorological forecasts have mainly been used to establish early-warnings in France (meteorological and flood vigilance maps) or over the world (flash-flood guidances). These forecasts are typically limited either to the main streams covered by the flood forecasting services or to watersheds with specific assets like check dams, which in most cases are well gauged river sections, thus leaving aside large parts of the territory. This paper presents a distributed hydro-meteorological forecasting approach, which makes use of the high spatial and temporal resolution rainfall estimates that are now available, to provide information at ungauged sites. The proposed system intended to detect road inundation risks had initially been developed and tested in areas of limited size. This paper presents the extension of such a system to an entire region (i.e. the Gard region in Southern France), including over 2000 crossing points between rivers and roads and its validation with respect to a large data set of actual reported road inundations observed during recent flash flood events. These initial validation results appear to be most promising. The eventual proposed tool would provide the necessary information for flood event management services to identify the areas at risk and adopt appropriate safety and rescue measures: i.e. pre-positioning of rescue equipment, interruption of the traffic on the exposed roads and determination of safe access or evacuation routes. Moreover, beyond the specific application to the supervision of a road network, the research undertaken herein also provides results for the performance of hydro-meteorological forecasts on ungauged headwaters.

Application of WebGIS for traffic risk assessment

NASA Astrophysics Data System (ADS)

Voumard, Jérémie; Aye, Zar Chi; Derron, Marc-Henri; Jaboyedoff, Michel

2015-04-01

Roads and railways are threatened throughout the year by several natural hazards around the world, leading to the closing of transportation corridors, loss of access, deviation travels and potentially infrastructures damages and loss of human lives and also financial, social and economic consequences. Protection measures used to reduce the exposure to natural hazards are usually expensive and cannot be deployed on an entire transportation network. It is thus necessary to choose priority areas where protection measures need to be built. The aim of this study is to propose a friendly tool to evaluate and to understand issues and consequences of section closing and affected parts of a transportation network at small region scale. The proposed tool, currently in its design and building phase, will provide ways to simulate different closure scenarios and to analyze their consequences on transportation network; like deviating traffic on others roads and railways sections, additional time and distance travel or accessibility for emergency services like police, firefighters and ambulances. The tool is based on OpenGeo architecture, which is composed of open-source components. It integrates PostGIS for database, GeoServer and GeoWebCache for application servers and finally GeoExt and OpenLayers for user interface. Users will be able to attribute quantitative (like roads and railway type and closure consequences) and qualitative (like section unavailability duration, season, etc.) data to the different roads and railways sections based on their user rights. They will also be able to evaluate different track closures consequences in terms of different scenarios. Once finalized, the goal of this project including natural hazards, traffic and geomatic thematic is to propose a decision support tool for public authorities firstly and for specialists secondly so that they can evaluate easily and accurately as much as possible to highlight the weakpoints of the transportation network in the case track closures due to natural hazards.

Urban flood mitigation planning for Guwahati: A case of Bharalu basin.

PubMed

Sarmah, Tanaya; Das, Sutapa

2018-01-15

Guwahati, the capital city of Assam and the gateway to the seven north-eastern Indian states, is located in the Brahmaputra valley-one of the most flood prone regions of the world. The city receives an average annual rainfall of 1688 mm and is highly vulnerable towards frequent urban floods because of uncontrolled dumping of solid waste and siltation have choked the natural water channels. This coupled with the absence of an integrated drainage network and rapid urbanisation causes floods in many parts of the city, after a quick downpour. Bharalu river is the main natural water channel of the city and Bharalu basin is the most vulnerable one. The present paper is an attempt to plan for urban flood mitigation, by designing an integrated drainage network for the Bharalu basin which includes the low-lying urbanized areas bordered by the Guwahati-Shillong Road, the Radha Gobindo Baruah Road and the Rajgarh Road. Data regarding land use, flood level, rainfall, urban pattern and vulnerability towards urban flood were collected from available literature, field survey to find highest water level for 11.4 km road stretch, expert opinion survey from 18 experts and feedback from 77 community elders who have been residing in the city since the 1980s. The Bharalu basin is divided into seven drainage blocks and storm run-off has been calculated based on the inputs. Seven different trapezoidal drainage sections were designed to form an integrated drainage network which is 'self-healing' to a certain extent. This can serve as a template for the other catchment basins and to design a drainage network for the entire Guwahati city, thereby reducing urban flood hazard to a significant extent. The study illustrates the necessity of an urban flood mitigation planning approach in sub-Himalayan urban settlements such as Guwahati. Copyright © 2017 Elsevier Ltd. All rights reserved.

Network models provide insights into how oriens–lacunosum-moleculare and bistratified cell interactions influence the power of local hippocampal CA1 theta oscillations

PubMed Central

Ferguson, Katie A.; Huh, Carey Y. L.; Amilhon, Bénédicte; Manseau, Frédéric; Williams, Sylvain; Skinner, Frances K.

2015-01-01

Hippocampal theta is a 4–12 Hz rhythm associated with episodic memory, and although it has been studied extensively, the cellular mechanisms underlying its generation are unclear. The complex interactions between different interneuron types, such as those between oriens–lacunosum-moleculare (OLM) interneurons and bistratified cells (BiCs), make their contribution to network rhythms difficult to determine experimentally. We created network models that are tied to experimental work at both cellular and network levels to explore how these interneuron interactions affect the power of local oscillations. Our cellular models were constrained with properties from patch clamp recordings in the CA1 region of an intact hippocampus preparation in vitro. Our network models are composed of three different types of interneurons: parvalbumin-positive (PV+) basket and axo-axonic cells (BC/AACs), PV+ BiCs, and somatostatin-positive OLM cells. Also included is a spatially extended pyramidal cell model to allow for a simplified local field potential representation, as well as experimentally-constrained, theta frequency synaptic inputs to the interneurons. The network size, connectivity, and synaptic properties were constrained with experimental data. To determine how the interactions between OLM cells and BiCs could affect local theta power, we explored how the number of OLM-BiC connections and connection strength affected local theta power. We found that our models operate in regimes that could be distinguished by whether OLM cells minimally or strongly affected the power of network theta oscillations due to balances that, respectively, allow compensatory effects or not. Inactivation of OLM cells could result in no change or even an increase in theta power. We predict that the dis-inhibitory effect of OLM cells to BiCs to pyramidal cell interactions plays a critical role in the resulting power of network theta oscillations. Overall, our network models reveal a dynamic interplay between different classes of interneurons in influencing local theta power. PMID:26300744

A spatial DB model to simulate the road network efficiency in hydrogeological emergency

DOE Office of Scientific and Technical Information (OSTI.GOV)

Michele, Mangiameli, E-mail: michele.mangiameli@dica.unict.it; Giuseppe, Mussumeci

We deal with the theme of the simulation of risk analysis using a technological approach based on the integration of exclusively free and open source tools: PostgreSQL as Database Management System (DBMS) and Quantum GIS-GRASS as Geographic Information System (GIS) platform. The case study is represented by a seismic land in Sicily characterized by steep slopes and frequent instability phenomena. This area includes a city of about 30.000 inhabitants (Enna) that lies on the top of a mountain at about 990 m a.s.l.. The access to the city is assured by few and very winding roads that are also highly vulnerablemore » to seismic and hydrogeological hazards. When exceptional rainfall events occur, the loss of efficiency of these roads should compromise timeliness and effectiveness of rescue operations. The data of the sample area have been structured into the adopted DBMS, and the connection to the GIS functionalities allows simulating the exceptional events. We analyzed the hazard, vulnerability and exposure related to these events and calculated the final risk defining three classes for each scenario: low (L), medium (M) and high (H). This study can be a valuable tool to prioritize risk levels and set priorities for intervention to the main road networks.« less

Achieving Passive Localization with Traffic Light Schedules in Urban Road Sensor Networks

PubMed Central

Niu, Qiang; Yang, Xu; Gao, Shouwan; Chen, Pengpeng; Chan, Shibing

2016-01-01

Localization is crucial for the monitoring applications of cities, such as road monitoring, environment surveillance, vehicle tracking, etc. In urban road sensor networks, sensors are often sparely deployed due to the hardware cost. Under this sparse deployment, sensors cannot communicate with each other via ranging hardware or one-hop connectivity, rendering the existing localization solutions ineffective. To address this issue, this paper proposes a novel Traffic Lights Schedule-based localization algorithm (TLS), which is built on the fact that vehicles move through the intersection with a known traffic light schedule. We can first obtain the law by binary vehicle detection time stamps and describe the law as a matrix, called a detection matrix. At the same time, we can also use the known traffic light information to construct the matrices, which can be formed as a collection called a known matrix collection. The detection matrix is then matched in the known matrix collection for identifying where sensors are located on urban roads. We evaluate our algorithm by extensive simulation. The results show that the localization accuracy of intersection sensors can reach more than 90%. In addition, we compare it with a state-of-the-art algorithm and prove that it has a wider operational region. PMID:27735871

A spatial DB model to simulate the road network efficiency in hydrogeological emergency

NASA Astrophysics Data System (ADS)

Michele, Mangiameli; Giuseppe, Mussumeci

2015-12-01

We deal with the theme of the simulation of risk analysis using a technological approach based on the integration of exclusively free and open source tools: PostgreSQL as Database Management System (DBMS) and Quantum GIS-GRASS as Geographic Information System (GIS) platform. The case study is represented by a seismic land in Sicily characterized by steep slopes and frequent instability phenomena. This area includes a city of about 30.000 inhabitants (Enna) that lies on the top of a mountain at about 990 m a.s.l.. The access to the city is assured by few and very winding roads that are also highly vulnerable to seismic and hydrogeological hazards. When exceptional rainfall events occur, the loss of efficiency of these roads should compromise timeliness and effectiveness of rescue operations. The data of the sample area have been structured into the adopted DBMS, and the connection to the GIS functionalities allows simulating the exceptional events. We analyzed the hazard, vulnerability and exposure related to these events and calculated the final risk defining three classes for each scenario: low (L), medium (M) and high (H). This study can be a valuable tool to prioritize risk levels and set priorities for intervention to the main road networks..

Implementation Of Secure 6LoWPAN Communications For Tactical Wireless Sensor Networks

DTIC Science & Technology

2016-09-01

wireless sensor networks (WSN) consist of power -constrained devices spread throughout a region-of-interest to provide data extraction in real time...1  A.  LOW POWER WIRELESS SENSOR NETWORKS ............................1  B.  INTRODUCTION TO...communication protocol for low power wireless personal area networks Since the IEEE 802.15.4 standard only defines the first two layers of the Open

Co-location and Self-Similar Topologies of Urban Infrastructure Networks

NASA Astrophysics Data System (ADS)

Klinkhamer, Christopher; Zhan, Xianyuan; Ukkusuri, Satish; Elisabeth, Krueger; Paik, Kyungrock; Rao, Suresh

2016-04-01

The co-location of urban infrastructure is too obvious to be easily ignored. For reasons of practicality, reliability, and eminent domain, the spatial locations of many urban infrastructure networks, including drainage, sanitary sewers, and road networks, are well correlated. However, important questions dealing with correlations in the network topologies of differing infrastructure types remain unanswered. Here, we have extracted randomly distributed, nested subnets from the urban drainage, sanitary sewer, and road networks in two distinctly different cities: Amman, Jordan; and Indianapolis, USA. Network analyses were performed for each randomly chosen subnet (location and size), using a dual-mapping approach (Hierarchical Intersection Continuity Negotiation). Topological metrics for each infrastructure type were calculated and compared for all subnets in a given city. Despite large differences in the climate, governance, and populace of the two cities, and functional properties of the different infrastructure types, these infrastructure networks are shown to be highly spatially homogenous. Furthermore, strong correlations are found between topological metrics of differing types of surface and subsurface infrastructure networks. Also, the network topologies of each infrastructure type for both cities are shown to exhibit self-similar characteristics (i.e., power law node-degree distributions, [p(k) = ak-γ]. These findings can be used to assist city planners and engineers either expanding or retrofitting existing infrastructure, or in the case of developing countries, building new cities from the ground up. In addition, the self-similar nature of these infrastructure networks holds significant implications for the vulnerability of these critical infrastructure networks to external hazards and ways in which network resilience can be improved.

Visibility from roads predict the distribution of invasive fishes in agricultural ponds.

PubMed

Kizuka, Toshikazu; Akasaka, Munemitsu; Kadoya, Taku; Takamura, Noriko

2014-01-01

Propagule pressure and habitat characteristics are important factors used to predict the distribution of invasive alien species. For species exhibiting strong propagule pressure because of human-mediated introduction of species, indicators of introduction potential must represent the behavioral characteristics of humans. This study examined 64 agricultural ponds to assess the visibility of ponds from surrounding roads and its value as a surrogate of propagule pressure to explain the presence and absence of two invasive fish species. A three-dimensional viewshed analysis using a geographic information system quantified the visual exposure of respective ponds to humans. Binary classification trees were developed as a function of their visibility from roads, as well as five environmental factors: river density, connectivity with upstream dam reservoirs, pond area, chlorophyll a concentration, and pond drainage. Traditional indicators of human-mediated introduction (road density and proportion of urban land-use area) were alternatively included for comparison instead of visual exposure. The presence of Bluegill (Lepomis macrochirus) was predicted by the ponds' higher visibility from roads and pond connection with upstream dam reservoirs. Results suggest that fish stocking into ponds and their dispersal from upstream sources facilitated species establishment. Largemouth bass (Micropterus salmoides) distribution was constrained by chlorophyll a concentration, suggesting their lower adaptability to various environments than that of Bluegill. Based on misclassifications from classification trees for Bluegill, pond visual exposure to roads showed greater predictive capability than traditional indicators of human-mediated introduction. Pond visibility is an effective predictor of invasive species distribution. Its wider use might improve management and mitigate further invasion. The visual exposure of recipient ecosystems to humans is important for many invasive species that spread with frequent instances of human-mediated introduction.

The number and type of food retailers surrounding schools and their association with lunchtime eating behaviours in students

PubMed Central

2013-01-01

Background The primary study objective was to examine whether the presence of food retailers surrounding schools was associated with students’ lunchtime eating behaviours. The secondary objective was to determine whether measures of the food retail environment around schools captured using road network or circular buffers were more strongly related to eating behaviours while at school. Methods Grade 9 and 10 students (N=6,971) who participated in the 2009/10 Canadian Health Behaviour in School Aged Children Survey were included in this study. The outcome was determined by students’ self-reports of where they typically ate their lunch during school days. Circular and road network-based buffers were created for a 1 km distance surrounding 158 schools participating in the HBSC. The addresses of fast food restaurants, convenience stores and coffee/donut shops were mapped within the buffers. Multilevel logistic regression was used to determine whether there was a relationship between the presence of food retailers near schools and students regularly eating their lunch at a fast food restaurant, snack-bar or café. The Akaike Information Criteria (AIC) value, a measure of goodness-of-fit, was used to determine the optimal buffer type. Results For the 1 km circular buffers, students with 1–2 (OR= 1.10, 95% CI: 0.57-2.11), 3–4 (OR=1.45, 95% CI: 0.75-2.82) and ≥5 nearby food retailers (OR=2.94, 95% CI: 1.71-5.09) were more likely to eat lunch at a food retailer compared to students with no nearby food retailers. The relationships were slightly stronger when assessed via 1 km road network buffers, with a greater likelihood of eating at a food retailer for 1–2 (OR=1.20, 95% CI:0.74-1.95), 3–4 (OR=3.19, 95% CI: 1.66-6.13) and ≥5 nearby food retailers (OR=3.54, 95% CI: 2.08-6.02). Road network buffers appeared to provide a better measure of the food retail environment, as indicated by a lower AIC value (3332 vs. 3346). Conclusions There was a strong relationship between the presence of food retailers near schools and students’ lunchtime eating behaviours. Results from the goodness of fit analysis suggests that road network buffers provide a more optimal measure of school neighbourhood food environments relative to circular buffers. PMID:23391296

Bobcats ( Lynx rufus) as a Model Organism to Investigate the Effects of Roads on Wide-Ranging Carnivores

NASA Astrophysics Data System (ADS)

Litvaitis, John A.; Reed, Gregory C.; Carroll, Rory P.; Litvaitis, Marian K.; Tash, Jeffrey; Mahard, Tyler; Broman, Derek J. A.; Callahan, Catherine; Ellingwood, Mark

2015-06-01

We are using bobcats ( Lynx rufus) as a model organism to examine how roads affect the abundance, distribution, and genetic structure of a wide-ranging carnivore. First, we compared the distribution of bobcat-vehicle collisions to road density and then estimated collision probabilities for specific landscapes using a moving window with road-specific traffic volume. Next, we obtained incidental observations of bobcats from the public, camera-trap detections, and locations of bobcats equipped with GPS collars to examine habitat selection. These data were used to generate a cost-surface map to investigate potential barrier effects of roads. Finally, we have begun an examination of genetic structure of bobcat populations in relation to major road networks. Distribution of vehicle-killed bobcats was correlated with road density, especially state and interstate highways. Collision models suggested that some regions may function as demographic sinks. Simulated movements in the context of the cost-surface map indicated that some major roads may be barriers. These patterns were supported by the genetic structure of bobcats. The sharpest divisions among genetically distinct demes occurred along natural barriers (mountains and large lakes) and in road-dense regions. In conclusion, our study has demonstrated the utility of using bobcats as a model organism to understand the variety of threats that roads pose to a wide-ranging species. Bobcats may also be useful as one of a group of focal species while developing approaches to maintain existing connectivity or mitigate the negative effects of roads.

Bobcats (Lynx rufus) as a Model Organism to Investigate the Effects of Roads on Wide-Ranging Carnivores.

PubMed

Litvaitis, John A; Reed, Gregory C; Carroll, Rory P; Litvaitis, Marian K; Tash, Jeffrey; Mahard, Tyler; Broman, Derek J A; Callahan, Catherine; Ellingwood, Mark

2015-06-01

We are using bobcats (Lynx rufus) as a model organism to examine how roads affect the abundance, distribution, and genetic structure of a wide-ranging carnivore. First, we compared the distribution of bobcat-vehicle collisions to road density and then estimated collision probabilities for specific landscapes using a moving window with road-specific traffic volume. Next, we obtained incidental observations of bobcats from the public, camera-trap detections, and locations of bobcats equipped with GPS collars to examine habitat selection. These data were used to generate a cost-surface map to investigate potential barrier effects of roads. Finally, we have begun an examination of genetic structure of bobcat populations in relation to major road networks. Distribution of vehicle-killed bobcats was correlated with road density, especially state and interstate highways. Collision models suggested that some regions may function as demographic sinks. Simulated movements in the context of the cost-surface map indicated that some major roads may be barriers. These patterns were supported by the genetic structure of bobcats. The sharpest divisions among genetically distinct demes occurred along natural barriers (mountains and large lakes) and in road-dense regions. In conclusion, our study has demonstrated the utility of using bobcats as a model organism to understand the variety of threats that roads pose to a wide-ranging species. Bobcats may also be useful as one of a group of focal species while developing approaches to maintain existing connectivity or mitigate the negative effects of roads.

An experimental study of the Online Information Paradox: Does en-route information improve road network performance?

PubMed Central

2017-01-01

This study investigates the empirical presence of a theoretical transportation paradox, defined as the “Online Information Paradox” (OIP). The paradox suggests that, for certain road networks, the provision of online information deteriorate travel conditions for all users of that network relative to the situation where no online information is provided to users. The analytical presence of the paradox was derived for a specific network structure by using two equilibrium models, the first being the Expected User Equilibrium (EUE) solution (no information scenario) and the other being the User Equilibrium with Recourse (UER) solution (with information scenario). An incentivised computerised route choice game was designed using the concepts of experimental economics and administered in a controlled laboratory environment to investigate the physical presence of the paradox. Aggregate statistics of path flows and Total System Travel Costs (TSTC) were used to compare the experimental results with the theoretical findings. A total of 12 groups of 12 participants completed the experiment and the OIP and the occurrence of the OIP being significant was observed in 11 of the 12 cases. Though information increased travel costs for users on average, it reduced the volatility of travel costs experienced in the no information scenario indicating that information can achieve a more reliable system. Further replications of similar experiments and more importantly field based identification of the phenomena will force transport professionals to be aware of the emergence of the paradox. In addition, studies such as this emphasise the need for the adoption of adaptive traffic assignment techniques to appropriately model the acquisition of information on a road network. PMID:28902854

Network-constrained group lasso for high-dimensional multinomial classification with application to cancer subtype prediction.

PubMed

Tian, Xinyu; Wang, Xuefeng; Chen, Jun

2014-01-01

Classic multinomial logit model, commonly used in multiclass regression problem, is restricted to few predictors and does not take into account the relationship among variables. It has limited use for genomic data, where the number of genomic features far exceeds the sample size. Genomic features such as gene expressions are usually related by an underlying biological network. Efficient use of the network information is important to improve classification performance as well as the biological interpretability. We proposed a multinomial logit model that is capable of addressing both the high dimensionality of predictors and the underlying network information. Group lasso was used to induce model sparsity, and a network-constraint was imposed to induce the smoothness of the coefficients with respect to the underlying network structure. To deal with the non-smoothness of the objective function in optimization, we developed a proximal gradient algorithm for efficient computation. The proposed model was compared to models with no prior structure information in both simulations and a problem of cancer subtype prediction with real TCGA (the cancer genome atlas) gene expression data. The network-constrained mode outperformed the traditional ones in both cases.

Urban street structure and traffic safety.

PubMed

Mohan, Dinesh; Bangdiwala, Shrikant I; Villaveces, Andres

2017-09-01

This paper reports the influence of road type and junction density on road traffic fatality rates in U.S. cities. The Fatality Analysis Reporting System (FARS) files were used to obtain fatality rates for all cities for the years 2005-2010. A stratified random sample of 16 U.S. cities was taken, and cities with high and low road traffic fatality rates were compared on their road layout details (TIGER maps were used). Statistical analysis was done to determine the effect of junction density and road type on road traffic fatality rates. The analysis of road network and road traffic crash fatality rates in these randomly selected U.S. cities shows that, (a) higher number of junctions per road length was significantly associated with a lower motor- vehicle crash and pedestrian mortality rates, and, (b) increased number of kilometers of roads of any kind was associated with higher fatality rates, but an additional kilometer of main arterial road was associated with a significantly higher increase in total fatalities. When compared to non-arterial roads, the higher the ratio of highways and main arterial roads, there was an association with higher fatality rates. These results have important implications for road safety professionals. They suggest that once the road and street structure is put in place, that will influence whether a city has low or high traffic fatality rates. A city with higher proportion of wider roads and large city blocks will tend to have higher traffic fatality rates, and therefore in turn require much more efforts in police enforcement and other road safety measures. Urban planners need to know that smaller block size with relatively less wide roads will result in lower traffic fatality rates and this needs to be incorporated at the planning stage. Copyright © 2017 National Safety Council and Elsevier Ltd. All rights reserved.

Natural history matters: how biological constraints shape diversified interactions in pollination networks.

PubMed

Jordano, Pedro

2016-11-01

Species-specific traits constrain the ways organisms interact in nature. Some pairwise interactions among coexisting species simply do not occur; they are impossible to observe despite the fact that partners coexist in the same place. The author discusses these 'forbidden links' of species interaction networks. Photo: a sphingid moth, Manduca sexta visiting a flower of Tocoyena formosa (Rubiaceae) in the Brazilian Cerrado; tongue and corolla tube lengths approximately 100 mm. Courtesy of Felipe Amorim. Sazatornil, F.D., Moré, M., Benitez-Vieyra, S., Cocucci, A.A., Kitching, I.J., Schlumpberger, B.O., Oliveira, P.E., Sazima, M. & Amorim, F.W. (2016) Beyond neutral and forbidden links: morphological matches and the assembly of mutualistic hawkmoth-plant networks. Journal of Animal Ecology, 85, 1586-1594. Species-specific traits and life-history characteristics constrain the ways organisms interact in nature. For example, gape-limited predators are constrained in the sizes of prey they can handle and efficiently consume. When we consider the ubiquity of such constrains, it is evident how hard it can be to be a generalist partner in ecological interactions: a free-living animal or plant cannot simply interact with every available partner it encounters. Some pairwise interactions among coexisting species simply do not occur; they are impossible to observe despite the fact that partners coexist in the same place. Sazatornil et al. () explore the nature of such constraints in the mutualisms among hawkmoths and the plants they pollinate. In this iconic interaction, used by Darwin and Wallace to vividly illustrate the power of natural selection in shaping evolutionary change, both pollinators and plants are sharply constrained in their interaction modes and outcomes. © 2016 The Author. Journal of Animal Ecology © 2016 British Ecological Society.

Systematic Development of Intelligent Systems for Public Road Transport.

PubMed

García, Carmelo R; Quesada-Arencibia, Alexis; Cristóbal, Teresa; Padrón, Gabino; Alayón, Francisco

2016-07-16

This paper presents an architecture model for the development of intelligent systems for public passenger transport by road. The main objective of our proposal is to provide a framework for the systematic development and deployment of telematics systems to improve various aspects of this type of transport, such as efficiency, accessibility and safety. The architecture model presented herein is based on international standards on intelligent transport system architectures, ubiquitous computing and service-oriented architecture for distributed systems. To illustrate the utility of the model, we also present a use case of a monitoring system for stops on a public passenger road transport network.

Systematic Development of Intelligent Systems for Public Road Transport

PubMed Central

García, Carmelo R.; Quesada-Arencibia, Alexis; Cristóbal, Teresa; Padrón, Gabino; Alayón, Francisco

2016-01-01

This paper presents an architecture model for the development of intelligent systems for public passenger transport by road. The main objective of our proposal is to provide a framework for the systematic development and deployment of telematics systems to improve various aspects of this type of transport, such as efficiency, accessibility and safety. The architecture model presented herein is based on international standards on intelligent transport system architectures, ubiquitous computing and service-oriented architecture for distributed systems. To illustrate the utility of the model, we also present a use case of a monitoring system for stops on a public passenger road transport network. PMID:27438836

Scale-dependent genetic structure of the Idaho giant salamander (Dicamptodon aterrimus) in stream networks

Treesearch

Lindy B. Mullen; H. Arthur Woods; Michael K. Schwartz; Adam J. Sepulveda; Winsor H. Lowe

2010-01-01

The network architecture of streams and rivers constrains evolutionary, demographic and ecological processes of freshwater organisms. This consistent architecture also makes stream networks useful for testing general models of population genetic structure and the scaling of gene flow. We examined genetic structure and gene flow in the facultatively paedomorphic Idaho...

Research on public logistics centers of Zhenzhou city based on GIS

NASA Astrophysics Data System (ADS)

Zeng, Yuhuai; Chen, Shuisen; Tian, Zhihui; Miao, Quansheng

2008-10-01

The regional public logistics center (PLC) is the intermedium that transports goods or commodity from producer to wholesaler, retailer and end consumer through whole supply chains. According to the Central Place Theory, the PLC should be multi-centric and of more kinds of graded degrees. From the road network planning discipline, an unique index---Importance Degree, is presented to measure the capacity of a PLC. The Importance Degree selects three township criteria: total population, gross industry product and budget income as weights to calculate the weighted vectors by principle component analysis method. Finally, through the clustering analysis, we can get the graded degrees of PLCs. It proves that that this research method is very effective for the road network planning of Zhengzhou City.

Regional analysis of the effect of paved roads on sodium and chloride in lakes.

PubMed

Kelting, Daniel L; Laxson, Corey L; Yerger, Elizabeth C

2012-05-15

Salinization of surface water from sodium chloride (road salt) applied to paved roads is a widely recognized environmental concern in the northern hemisphere, yet practical information to improve winter road management to reduce the environmental impacts of this deicer is lacking. The purpose of our study was to provide such information by developing baseline concentrations for sodium and chloride for lakes in watersheds without paved roads, and then determining the relationship between these ions and density, type, and proximity of paved roads to shoreline. We used average summer (June-September) sodium and chloride data for 138 lakes combined in a watershed based analysis of paved road networks in the Adirondack Park of New York, U.S.A. The watersheds used in our study represented a broad range in paved road density and type, 56 of which had no paved roads. Median lake sodium and chloride concentrations in these 56 watersheds averaged 0.55 and 0.24 mg/L, respectively. In contrast, the median sodium and chloride concentrations for the 82 lakes in watersheds with paved roads were 3.60 and 7.22 mg/L, respectively. Paved road density (lane-km/km(2)) was positively correlated with sodium and chloride concentrations, but only state roads were significantly correlated with sodium and chloride while local roads were not. State road density alone explained 84 percent of the variation in both ions. We also successfully modeled the relationship between road proximity to shoreline and sodium and chloride concentrations in lakes, which allowed us to identify sections of road that contributed more to explaining the variation in sodium and chloride in lakes. This model and our approach could be used as part of larger efforts to identify environmentally sensitive areas where alternative winter road management treatments should be applied. Copyright © 2012 Elsevier Ltd. All rights reserved.

A research of road centerline extraction algorithm from high resolution remote sensing images

NASA Astrophysics Data System (ADS)

Zhang, Yushan; Xu, Tingfa

2017-09-01

Satellite remote sensing technology has become one of the most effective methods for land surface monitoring in recent years, due to its advantages such as short period, large scale and rich information. Meanwhile, road extraction is an important field in the applications of high resolution remote sensing images. An intelligent and automatic road extraction algorithm with high precision has great significance for transportation, road network updating and urban planning. The fuzzy c-means (FCM) clustering segmentation algorithms have been used in road extraction, but the traditional algorithms did not consider spatial information. An improved fuzzy C-means clustering algorithm combined with spatial information (SFCM) is proposed in this paper, which is proved to be effective for noisy image segmentation. Firstly, the image is segmented using the SFCM. Secondly, the segmentation result is processed by mathematical morphology to remover the joint region. Thirdly, the road centerlines are extracted by morphology thinning and burr trimming. The average integrity of the centerline extraction algorithm is 97.98%, the average accuracy is 95.36% and the average quality is 93.59%. Experimental results show that the proposed method in this paper is effective for road centerline extraction.

Walking- and cycling track networks in Norwegian cities : cost-benefit analyses including health effects and external costs of road traffic : summary

DOT National Transportation Integrated Search

2002-04-01

Cost- benefit analyses of walking- and cycling track net-works in three Norwegian cities are presented in this study. A project group working with a National Cycling Strategy in Norway initialised the study. Motivation for starting the study is the P...

Long-Term Agroecosystem Research Advancing Sustainable Intensification in Fields, Farms, and Regions Across the United States

USDA-ARS?s Scientific Manuscript database

The Long-Term Agroecosystem Research network is building a road map for the sustainable intensification of U.S. agriculture by designing strategies that are locally appropriate and applicable to multiple scales of agricultural organization. The 18 sites in the LTAR network represent a diversity of l...

Clarifying evacuation options through fire behavior and traffic modeling

Treesearch

Carol L. Rice; Ronny J. Coleman; Mike Price

2011-01-01

Communities are becoming increasingly concerned with the variety of choices related to wildfire evacuation. We used ArcView with Network Analyst to evaluate the different options for evacuations during wildfire in a case study community. We tested overlaying fire growth patterns with the road network and population characteristics to determine recommendations for...

Predicting Energy Consumption for Potential Effective Use in Hybrid Vehicle Powertrain Management Using Driver Prediction

NASA Astrophysics Data System (ADS)

Magnuson, Brian

A proof-of-concept software-in-the-loop study is performed to assess the accuracy of predicted net and charge-gaining energy consumption for potential effective use in optimizing powertrain management of hybrid vehicles. With promising results of improving fuel efficiency of a thermostatic control strategy for a series, plug-ing, hybrid-electric vehicle by 8.24%, the route and speed prediction machine learning algorithms are redesigned and implemented for real- world testing in a stand-alone C++ code-base to ingest map data, learn and predict driver habits, and store driver data for fast startup and shutdown of the controller or computer used to execute the compiled algorithm. Speed prediction is performed using a multi-layer, multi-input, multi- output neural network using feed-forward prediction and gradient descent through back- propagation training. Route prediction utilizes a Hidden Markov Model with a recurrent forward algorithm for prediction and multi-dimensional hash maps to store state and state distribution constraining associations between atomic road segments and end destinations. Predicted energy is calculated using the predicted time-series speed and elevation profile over the predicted route and the road-load equation. Testing of the code-base is performed over a known road network spanning 24x35 blocks on the south hill of Spokane, Washington. A large set of training routes are traversed once to add randomness to the route prediction algorithm, and a subset of the training routes, testing routes, are traversed to assess the accuracy of the net and charge-gaining predicted energy consumption. Each test route is traveled a random number of times with varying speed conditions from traffic and pedestrians to add randomness to speed prediction. Prediction data is stored and analyzed in a post process Matlab script. The aggregated results and analysis of all traversals of all test routes reflect the performance of the Driver Prediction algorithm. The error of average energy gained through charge-gaining events is 31.3% and the error of average net energy consumed is 27.3%. The average delta and average standard deviation of the delta of predicted energy gained through charge-gaining events is 0.639 and 0.601 Wh respectively for individual time-series calculations. Similarly, the average delta and average standard deviation of the delta of the predicted net energy consumed is 0.567 and 0.580 Wh respectively for individual time-series calculations. The average delta and standard deviation of the delta of the predicted speed is 1.60 and 1.15 respectively also for the individual time-series measurements. The percentage of accuracy of route prediction is 91%. Overall, test routes are traversed 151 times for a total test distance of 276.4 km.

Use of radar rainfall estimates and forecasts to prevent flash flood in real time by using a road inundation warning system

NASA Astrophysics Data System (ADS)

Versini, Pierre-Antoine

2012-01-01

SummaryImportant damages occur in small headwater catchments when they are hit by severe storms with complex spatio-temporal structure, sometimes resulting in flash floods. As these catchments are mostly not covered by sensor networks, it is difficult to forecast these floods. This is particularly true for road submersions, representing major concerns for flood event managers. The use of Quantitative Precipitation Estimates and Forecasts (QPE/QPF) especially based on radar measurements could particularly be adequate to evaluate rainfall-induced risks. Although their characteristic time and space scales would make them suitable for flash flood modelling, the impact of their uncertainties remain uncertain and have to be evaluated. The Gard region (France) has been chosen as case study. This area is frequently affected by severe flash floods, and an application devoted to the road network has also been recently developed for the North part of this region. This warning system combines distributed hydro-meteorological modelling and susceptibility analysis to provide warnings of road inundations. The warning system has been tested on the specific storm of the 29-30 September 2007. During this event, around 200 mm dropped on the South part of the Gard and many roads were submerged. Radar-based QPE and QPF have been used to forecast the exact location of road submersions and the results have been compared to the effective road submersions actually occurred during the event as listed by the emergency services. Used on an area it has not been calibrated, the results confirm that the road submersion warning system represents a promising tool for anticipating and quantifying the consequences of storm events at ground. It rates the submersion risk with an acceptable level of accuracy and demonstrates also the quality of high spatial and temporal resolution radar rainfall data in real time, and the possibility to use them despite their uncertainties. However because of the quality of rainfall forecasts falls drastically with time, it is not often sufficient to provide valuable information for lead times exceeding 1 h.