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.

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.

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.

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.

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

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.

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.

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.

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.

Mapping from Space - Ontology Based Map Production Using Satellite Imageries

NASA Astrophysics Data System (ADS)

Asefpour Vakilian, A.; Momeni, M.

2013-09-01

Determination of the maximum ability for feature extraction from satellite imageries based on ontology procedure using cartographic feature determination is the main objective of this research. Therefore, a special ontology has been developed to extract maximum volume of information available in different high resolution satellite imageries and compare them to the map information layers required in each specific scale due to unified specification for surveying and mapping. ontology seeks to provide an explicit and comprehensive classification of entities in all sphere of being. This study proposes a new method for automatic maximum map feature extraction and reconstruction of high resolution satellite images. For example, in order to extract building blocks to produce 1 : 5000 scale and smaller maps, the road networks located around the building blocks should be determined. Thus, a new building index has been developed based on concepts obtained from ontology. Building blocks have been extracted with completeness about 83%. Then, road networks have been extracted and reconstructed to create a uniform network with less discontinuity on it. In this case, building blocks have been extracted with proper performance and the false positive value from confusion matrix was reduced by about 7%. Results showed that vegetation cover and water features have been extracted completely (100%) and about 71% of limits have been extracted. Also, the proposed method in this article had the ability to produce a map with largest scale possible from any multi spectral high resolution satellite imagery equal to or smaller than 1 : 5000.

Mapping from Space - Ontology Based Map Production Using Satellite Imageries

NASA Astrophysics Data System (ADS)

Asefpour Vakilian, A.; Momeni, M.

2013-09-01

Determination of the maximum ability for feature extraction from satellite imageries based on ontology procedure using cartographic feature determination is the main objective of this research. Therefore, a special ontology has been developed to extract maximum volume of information available in different high resolution satellite imageries and compare them to the map information layers required in each specific scale due to unified specification for surveying and mapping. ontology seeks to provide an explicit and comprehensive classification of entities in all sphere of being. This study proposes a new method for automatic maximum map feature extraction and reconstruction of high resolution satellite images. For example, in order to extract building blocks to produce 1 : 5000 scale and smaller maps, the road networks located around the building blocks should be determined. Thus, a new building index has been developed based on concepts obtained from ontology. Building blocks have been extracted with completeness about 83 %. Then, road networks have been extracted and reconstructed to create a uniform network with less discontinuity on it. In this case, building blocks have been extracted with proper performance and the false positive value from confusion matrix was reduced by about 7 %. Results showed that vegetation cover and water features have been extracted completely (100 %) and about 71 % of limits have been extracted. Also, the proposed method in this article had the ability to produce a map with largest scale possible from any multi spectral high resolution satellite imagery equal to or smaller than 1 : 5000.

Multispectral Image Road Extraction Based Upon Automated Map Conflation

NASA Astrophysics Data System (ADS)

Chen, Bin

Road network extraction from remotely sensed imagery enables many important and diverse applications such as vehicle tracking, drone navigation, and intelligent transportation studies. There are, however, a number of challenges to road detection from an image. Road pavement material, width, direction, and topology vary across a scene. Complete or partial occlusions caused by nearby buildings, trees, and the shadows cast by them, make maintaining road connectivity difficult. The problems posed by occlusions are exacerbated with the increasing use of oblique imagery from aerial and satellite platforms. Further, common objects such as rooftops and parking lots are made of materials similar or identical to road pavements. This problem of common materials is a classic case of a single land cover material existing for different land use scenarios. This work addresses these problems in road extraction from geo-referenced imagery by leveraging the OpenStreetMap digital road map to guide image-based road extraction. The crowd-sourced cartography has the advantages of worldwide coverage that is constantly updated. The derived road vectors follow only roads and so can serve to guide image-based road extraction with minimal confusion from occlusions and changes in road material. On the other hand, the vector road map has no information on road widths and misalignments between the vector map and the geo-referenced image are small but nonsystematic. Properly correcting misalignment between two geospatial datasets, also known as map conflation, is an essential step. A generic framework requiring minimal human intervention is described for multispectral image road extraction and automatic road map conflation. The approach relies on the road feature generation of a binary mask and a corresponding curvilinear image. A method for generating the binary road mask from the image by applying a spectral measure is presented. The spectral measure, called anisotropy-tunable distance (ATD), differs from conventional measures and is created to account for both changes of spectral direction and spectral magnitude in a unified fashion. The ATD measure is particularly suitable for differentiating urban targets such as roads and building rooftops. The curvilinear image provides estimates of the width and orientation of potential road segments. Road vectors derived from OpenStreetMap are then conflated to image road features by applying junction matching and intermediate point matching, followed by refinement with mean-shift clustering and morphological processing to produce a road mask with piecewise width estimates. The proposed approach is tested on a set of challenging, large, and diverse image data sets and the performance accuracy is assessed. The method is effective for road detection and width estimation of roads, even in challenging scenarios when extensive occlusion occurs.

A semi-automatic method for extracting thin line structures in images as rooted tree network

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

Brazzini, Jacopo; Dillard, Scott; Soille, Pierre

2010-01-01

This paper addresses the problem of semi-automatic extraction of line networks in digital images - e.g., road or hydrographic networks in satellite images, blood vessels in medical images, robust. For that purpose, we improve a generic method derived from morphological and hydrological concepts and consisting in minimum cost path estimation and flow simulation. While this approach fully exploits the local contrast and shape of the network, as well as its arborescent nature, we further incorporate local directional information about the structures in the image. Namely, an appropriate anisotropic metric is designed by using both the characteristic features of the targetmore » network and the eigen-decomposition of the gradient structure tensor of the image. Following, the geodesic propagation from a given seed with this metric is combined with hydrological operators for overland flow simulation to extract the line network. The algorithm is demonstrated for the extraction of blood vessels in a retina image and of a river network in a satellite image.« less

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.

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.

Delineation and geometric modeling of road networks

NASA Astrophysics Data System (ADS)

Poullis, Charalambos; You, Suya

In this work we present a novel vision-based system for automatic detection and extraction of complex road networks from various sensor resources such as aerial photographs, satellite images, and LiDAR. Uniquely, the proposed system is an integrated solution that merges the power of perceptual grouping theory (Gabor filtering, tensor voting) and optimized segmentation techniques (global optimization using graph-cuts) into a unified framework to address the challenging problems of geospatial feature detection and classification. Firstly, the local precision of the Gabor filters is combined with the global context of the tensor voting to produce accurate classification of the geospatial features. In addition, the tensorial representation used for the encoding of the data eliminates the need for any thresholds, therefore removing any data dependencies. Secondly, a novel orientation-based segmentation is presented which incorporates the classification of the perceptual grouping, and results in segmentations with better defined boundaries and continuous linear segments. Finally, a set of gaussian-based filters are applied to automatically extract centerline information (magnitude, width and orientation). This information is then used for creating road segments and transforming them to their polygonal representations.

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.

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.

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.

A data storage and retrieval model for Louisiana traffic operations data : technical summary.

DOT National Transportation Integrated Search

1996-08-01

The overall goal of this research study was to develop a prototype computer-based indexing model for traffic operation data in DOTD. The methodology included: 1) extraction of state road network, 2) development of geographic reference model, 3) engin...

Automotive System for Remote Surface Classification.

PubMed

Bystrov, Aleksandr; Hoare, Edward; Tran, Thuy-Yung; Clarke, Nigel; Gashinova, Marina; Cherniakov, Mikhail

2017-04-01

In this paper we shall discuss a novel approach to road surface recognition, based on the analysis of backscattered microwave and ultrasonic signals. The novelty of our method is sonar and polarimetric radar data fusion, extraction of features for separate swathes of illuminated surface (segmentation), and using of multi-stage artificial neural network for surface classification. The developed system consists of 24 GHz radar and 40 kHz ultrasonic sensor. The features are extracted from backscattered signals and then the procedures of principal component analysis and supervised classification are applied to feature data. The special attention is paid to multi-stage artificial neural network which allows an overall increase in classification accuracy. The proposed technique was tested for recognition of a large number of real surfaces in different weather conditions with the average accuracy of correct classification of 95%. The obtained results thereby demonstrate that the use of proposed system architecture and statistical methods allow for reliable discrimination of various road surfaces in real conditions.

Automotive System for Remote Surface Classification

PubMed Central

Bystrov, Aleksandr; Hoare, Edward; Tran, Thuy-Yung; Clarke, Nigel; Gashinova, Marina; Cherniakov, Mikhail

2017-01-01

In this paper we shall discuss a novel approach to road surface recognition, based on the analysis of backscattered microwave and ultrasonic signals. The novelty of our method is sonar and polarimetric radar data fusion, extraction of features for separate swathes of illuminated surface (segmentation), and using of multi-stage artificial neural network for surface classification. The developed system consists of 24 GHz radar and 40 kHz ultrasonic sensor. The features are extracted from backscattered signals and then the procedures of principal component analysis and supervised classification are applied to feature data. The special attention is paid to multi-stage artificial neural network which allows an overall increase in classification accuracy. The proposed technique was tested for recognition of a large number of real surfaces in different weather conditions with the average accuracy of correct classification of 95%. The obtained results thereby demonstrate that the use of proposed system architecture and statistical methods allow for reliable discrimination of various road surfaces in real conditions. PMID:28368297

A Robust Concurrent Approach for Road Extraction and Urbanization Monitoring Based on Superpixels Acquired from Spectral Remote Sensing Images

NASA Astrophysics Data System (ADS)

Seppke, Benjamin; Dreschler-Fischer, Leonie; Wilms, Christian

2016-08-01

The extraction of road signatures from remote sensing images as a promising indicator for urbanization is a classical segmentation problem. However, some segmentation algorithms often lead to non-sufficient results. One way to overcome this problem is the usage of superpixels, that represent a locally coherent cluster of connected pixels. Superpixels allow flexible, highly adaptive segmentation approaches due to the possibility of merging as well as splitting and form new basic image entities. On the other hand, superpixels require an appropriate representation containing all relevant information about topology and geometry to maximize their advantages.In this work, we present a combined geometric and topological representation based on a special graph representation, the so-called RS-graph. Moreover, we present the use of the RS-graph by means of a case study: the extraction of partially occluded road networks in rural areas from open source (spectral) remote sensing images by tracking. In addition, multiprocessing and GPU-based parallelization is used to speed up the construction of the representation and the application.

Scan Line Based Road Marking Extraction from Mobile LiDAR Point Clouds.

PubMed

Yan, Li; Liu, Hua; Tan, Junxiang; Li, Zan; Xie, Hong; Chen, Changjun

2016-06-17

Mobile Mapping Technology (MMT) is one of the most important 3D spatial data acquisition technologies. The state-of-the-art mobile mapping systems, equipped with laser scanners and named Mobile LiDAR Scanning (MLS) systems, have been widely used in a variety of areas, especially in road mapping and road inventory. With the commercialization of Advanced Driving Assistance Systems (ADASs) and self-driving technology, there will be a great demand for lane-level detailed 3D maps, and MLS is the most promising technology to generate such lane-level detailed 3D maps. Road markings and road edges are necessary information in creating such lane-level detailed 3D maps. This paper proposes a scan line based method to extract road markings from mobile LiDAR point clouds in three steps: (1) preprocessing; (2) road points extraction; (3) road markings extraction and refinement. In preprocessing step, the isolated LiDAR points in the air are removed from the LiDAR point clouds and the point clouds are organized into scan lines. In the road points extraction step, seed road points are first extracted by Height Difference (HD) between trajectory data and road surface, then full road points are extracted from the point clouds by moving least squares line fitting. In the road markings extraction and refinement step, the intensity values of road points in a scan line are first smoothed by a dynamic window median filter to suppress intensity noises, then road markings are extracted by Edge Detection and Edge Constraint (EDEC) method, and the Fake Road Marking Points (FRMPs) are eliminated from the detected road markings by segment and dimensionality feature-based refinement. The performance of the proposed method is evaluated by three data samples and the experiment results indicate that road points are well extracted from MLS data and road markings are well extracted from road points by the applied method. A quantitative study shows that the proposed method achieves an average completeness, correctness, and F-measure of 0.96, 0.93, and 0.94, respectively. The time complexity analysis shows that the scan line based road markings extraction method proposed in this paper provides a promising alternative for offline road markings extraction from MLS data.

Scan Line Based Road Marking Extraction from Mobile LiDAR Point Clouds†

PubMed Central

Yan, Li; Liu, Hua; Tan, Junxiang; Li, Zan; Xie, Hong; Chen, Changjun

2016-01-01

Mobile Mapping Technology (MMT) is one of the most important 3D spatial data acquisition technologies. The state-of-the-art mobile mapping systems, equipped with laser scanners and named Mobile LiDAR Scanning (MLS) systems, have been widely used in a variety of areas, especially in road mapping and road inventory. With the commercialization of Advanced Driving Assistance Systems (ADASs) and self-driving technology, there will be a great demand for lane-level detailed 3D maps, and MLS is the most promising technology to generate such lane-level detailed 3D maps. Road markings and road edges are necessary information in creating such lane-level detailed 3D maps. This paper proposes a scan line based method to extract road markings from mobile LiDAR point clouds in three steps: (1) preprocessing; (2) road points extraction; (3) road markings extraction and refinement. In preprocessing step, the isolated LiDAR points in the air are removed from the LiDAR point clouds and the point clouds are organized into scan lines. In the road points extraction step, seed road points are first extracted by Height Difference (HD) between trajectory data and road surface, then full road points are extracted from the point clouds by moving least squares line fitting. In the road markings extraction and refinement step, the intensity values of road points in a scan line are first smoothed by a dynamic window median filter to suppress intensity noises, then road markings are extracted by Edge Detection and Edge Constraint (EDEC) method, and the Fake Road Marking Points (FRMPs) are eliminated from the detected road markings by segment and dimensionality feature-based refinement. The performance of the proposed method is evaluated by three data samples and the experiment results indicate that road points are well extracted from MLS data and road markings are well extracted from road points by the applied method. A quantitative study shows that the proposed method achieves an average completeness, correctness, and F-measure of 0.96, 0.93, and 0.94, respectively. The time complexity analysis shows that the scan line based road markings extraction method proposed in this paper provides a promising alternative for offline road markings extraction from MLS data. PMID:27322279

Built-Up Area Feature Extraction: Second Year Technical Progress Report

DTIC Science & Technology

1990-02-01

Contract DACA 72-87-C-001. During this year we have built on previous research, in road network extraction and in the detection and delineation of buildings...methods to perform stereo analysis using loosely coupled techniques where comparison is deferred until each method has performed a complete estimate...or missing information. A course of action may be suggested to the user depending on the error. Although the checks do not guarantee the correctness

Using high resolution DEMs to assess the effects of roads and trails on hydrological pathways that contribute to gully development

NASA Astrophysics Data System (ADS)

Sidle, R. C.; Jarihani, B.

2017-12-01

Dry savannas of northern Queensland, Australia experience severe gully erosion, particularly areas that have been heavily grazed. Field surveys have also noted the influence of unpaved roads and cattle trails on concentrating storm runoff into gully systems. To better quantify the effect of these roads and trails we use high resolution digital elevation models (DEMs) to develop indices of hydrological connectivity (IC) throughout drainage areas above and downstream of gully systems. High resolution (0.5m) DEMs from LiDAR were used to extract road and trail networks and drone-based very high resolution (0.1m) DEMs were used to extract cattle trials. IC is a function of the ratio of upslope to downslope sediment routing functions, which are based on upslope area, mean slope gradient, a weighting factor related to impedance to overland flow, and flow path distance (for the downstream function). Maps of IC within the heavily grazed Weany Creek catchment (13 km2) of northeast Queensland show that existing roads can increase hydrologic connectivity to gully systems. Furthermore, by adding roads and cattle trails into existing DEMs, we show how the extent and location of these curvilinear features affect overland flow concentration. Our findings can inform important hydrogeomorphic issues such as which gullies will likely headcut or expand and where new gullies may arise. Our analysis can also contribute to better management practices for grazing and road location.

Image feature based GPS trace filtering for road network generation and road segmentation

DOE PAGES

Yuan, Jiangye; Cheriyadat, Anil M.

2015-10-19

We propose a new method to infer road networks from GPS trace data and accurately segment road regions in high-resolution aerial images. Unlike previous efforts that rely on GPS traces alone, we exploit image features to infer road networks from noisy trace data. The inferred road network is used to guide road segmentation. We show that the number of image segments spanned by the traces and the trace orientation validated with image features are important attributes for identifying GPS traces on road regions. Based on filtered traces , we construct road networks and integrate them with image features to segmentmore » road regions. Lastly, our experiments show that the proposed method produces more accurate road networks than the leading method that uses GPS traces alone, and also achieves high accuracy in segmenting road regions even with very noisy GPS data.« less

Image feature based GPS trace filtering for road network generation and road segmentation

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

Yuan, Jiangye; Cheriyadat, Anil M.

We propose a new method to infer road networks from GPS trace data and accurately segment road regions in high-resolution aerial images. Unlike previous efforts that rely on GPS traces alone, we exploit image features to infer road networks from noisy trace data. The inferred road network is used to guide road segmentation. We show that the number of image segments spanned by the traces and the trace orientation validated with image features are important attributes for identifying GPS traces on road regions. Based on filtered traces , we construct road networks and integrate them with image features to segmentmore » road regions. Lastly, our experiments show that the proposed method produces more accurate road networks than the leading method that uses GPS traces alone, and also achieves high accuracy in segmenting road regions even with very noisy GPS data.« less

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.

Transition Characteristic Analysis of Traffic Evolution Process for Urban Traffic Network

PubMed Central

Chen, Hong; Li, Yang

2014-01-01

The characterization of the dynamics of traffic states remains fundamental to seeking for the solutions of diverse traffic problems. To gain more insights into traffic dynamics in the temporal domain, this paper explored temporal characteristics and distinct regularity in the traffic evolution process of urban traffic network. We defined traffic state pattern through clustering multidimensional traffic time series using self-organizing maps and construct a pattern transition network model that is appropriate for representing and analyzing the evolution progress. The methodology is illustrated by an application to data flow rate of multiple road sections from Network of Shenzhen's Nanshan District, China. Analysis and numerical results demonstrated that the methodology permits extracting many useful traffic transition characteristics including stability, preference, activity, and attractiveness. In addition, more information about the relationships between these characteristics was extracted, which should be helpful in understanding the complex behavior of the temporal evolution features of traffic patterns. PMID:24982969

Identifying the Critical Links in Road Transportation Networks: Centrality-based approach utilizing structural properties

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

Chinthavali, Supriya

Surface transportation road networks share structural properties similar to other complex networks (e.g., social networks, information networks, biological networks, and so on). This research investigates the structural properties of road networks for any possible correlation with the traffic characteristics such as link flows those determined independently. Additionally, we define a criticality index for the links of the road network that identifies the relative importance in the network. We tested our hypotheses with two sample road networks. Results show that, correlation exists between the link flows and centrality measures of a link of the road (dual graph approach is followed) andmore » the criticality index is found to be effective for one test network to identify the vulnerable nodes.« less

Construction of road network vulnerability evaluation index based on general travel cost

NASA Astrophysics Data System (ADS)

Leng, Jun-qiang; Zhai, Jing; Li, Qian-wen; Zhao, Lin

2018-03-01

With the development of China's economy and the continuous improvement of her urban road network, the vulnerability of the urban road network has attracted increasing attention. Based on general travel cost, this work constructs the vulnerability evaluation index for the urban road network, and evaluates the vulnerability of the urban road network from the perspective of user generalised travel cost. Firstly, the generalised travel cost model is constructed based on vehicle cost, travel time, and traveller comfort. Then, the network efficiency index is selected as an evaluation index of vulnerability: the network efficiency index is composed of the traffic volume and the generalised travel cost, which are obtained from the equilibrium state of the network. In addition, the research analyses the influence of traffic capacity decrease, road section attribute value, and location of road section, on vulnerability. Finally, the vulnerability index is used to analyse the local area network of Harbin and verify its applicability.

Main Road Extraction from ZY-3 Grayscale Imagery Based on Directional Mathematical Morphology and VGI Prior Knowledge in Urban Areas

PubMed Central

Liu, Bo; Wu, Huayi; Wang, Yandong; Liu, Wenming

2015-01-01

Main road features extracted from remotely sensed imagery play an important role in many civilian and military applications, such as updating Geographic Information System (GIS) databases, urban structure analysis, spatial data matching and road navigation. Current methods for road feature extraction from high-resolution imagery are typically based on threshold value segmentation. It is difficult however, to completely separate road features from the background. We present a new method for extracting main roads from high-resolution grayscale imagery based on directional mathematical morphology and prior knowledge obtained from the Volunteered Geographic Information found in the OpenStreetMap. The two salient steps in this strategy are: (1) using directional mathematical morphology to enhance the contrast between roads and non-roads; (2) using OpenStreetMap roads as prior knowledge to segment the remotely sensed imagery. Experiments were conducted on two ZiYuan-3 images and one QuickBird high-resolution grayscale image to compare our proposed method to other commonly used techniques for road feature extraction. The results demonstrated the validity and better performance of the proposed method for urban main road feature extraction. PMID:26397832

Chain-Wise Generalization of Road Networks Using Model Selection

NASA Astrophysics Data System (ADS)

Bulatov, D.; Wenzel, S.; Häufel, G.; Meidow, J.

2017-05-01

Streets are essential entities of urban terrain and their automatized extraction from airborne sensor data is cumbersome because of a complex interplay of geometric, topological and semantic aspects. Given a binary image, representing the road class, centerlines of road segments are extracted by means of skeletonization. The focus of this paper lies in a well-reasoned representation of these segments by means of geometric primitives, such as straight line segments as well as circle and ellipse arcs. We propose the fusion of raw segments based on similarity criteria; the output of this process are the so-called chains which better match to the intuitive perception of what a street is. Further, we propose a two-step approach for chain-wise generalization. First, the chain is pre-segmented using circlePeucker and finally, model selection is used to decide whether two neighboring segments should be fused to a new geometric entity. Thereby, we consider both variance-covariance analysis of residuals and model complexity. The results on a complex data-set with many traffic roundabouts indicate the benefits of the proposed procedure.

Mathematical model of highways network optimization

NASA Astrophysics Data System (ADS)

Sakhapov, R. L.; Nikolaeva, R. V.; Gatiyatullin, M. H.; Makhmutov, M. M.

2017-12-01

The article deals with the issue of highways network design. Studies show that the main requirement from road transport for the road network is to ensure the realization of all the transport links served by it, with the least possible cost. The goal of optimizing the network of highways is to increase the efficiency of transport. It is necessary to take into account a large number of factors that make it difficult to quantify and qualify their impact on the road network. In this paper, we propose building an optimal variant for locating the road network on the basis of a mathematical model. The article defines the criteria for optimality and objective functions that reflect the requirements for the road network. The most fully satisfying condition for optimality is the minimization of road and transport costs. We adopted this indicator as a criterion of optimality in the economic-mathematical model of a network of highways. Studies have shown that each offset point in the optimal binding road network is associated with all other corresponding points in the directions providing the least financial costs necessary to move passengers and cargo from this point to the other corresponding points. The article presents general principles for constructing an optimal network of roads.

Drawing Road Networks with Mental Maps.

PubMed

Lin, Shih-Syun; Lin, Chao-Hung; Hu, Yan-Jhang; Lee, Tong-Yee

2014-09-01

Tourist and destination maps are thematic maps designed to represent specific themes in maps. The road network topologies in these maps are generally more important than the geometric accuracy of roads. A road network warping method is proposed to facilitate map generation and improve theme representation in maps. The basic idea is deforming a road network to meet a user-specified mental map while an optimization process is performed to propagate distortions originating from road network warping. To generate a map, the proposed method includes algorithms for estimating road significance and for deforming a road network according to various geometric and aesthetic constraints. The proposed method can produce an iconic mark of a theme from a road network and meet a user-specified mental map. Therefore, the resulting map can serve as a tourist or destination map that not only provides visual aids for route planning and navigation tasks, but also visually emphasizes the presentation of a theme in a map for the purpose of advertising. In the experiments, the demonstrations of map generations show that our method enables map generation systems to generate deformed tourist and destination maps efficiently.

Measuring Road Network Vulnerability with Sensitivity Analysis

PubMed Central

Jun-qiang, Leng; Long-hai, Yang; Liu, Wei-yi; Zhao, Lin

2017-01-01

This paper focuses on the development of a method for road network vulnerability analysis, from the perspective of capacity degradation, which seeks to identify the critical infrastructures in the road network and the operational performance of the whole traffic system. This research involves defining the traffic utility index and modeling vulnerability of road segment, route, OD (Origin Destination) pair and road network. Meanwhile, sensitivity analysis method is utilized to calculate the change of traffic utility index due to capacity degradation. This method, compared to traditional traffic assignment, can improve calculation efficiency and make the application of vulnerability analysis to large actual road network possible. Finally, all the above models and calculation method is applied to actual road network evaluation to verify its efficiency and utility. This approach can be used as a decision-supporting tool for evaluating the performance of road network and identifying critical infrastructures in transportation planning and management, especially in the resource allocation for mitigation and recovery. PMID:28125706

Spatial resolution requirements for automated cartographic road extraction

USGS Publications Warehouse

Benjamin, S.; Gaydos, L.

1990-01-01

Ground resolution requirements for detection and extraction of road locations in a digitized large-scale photographic database were investigated. A color infrared photograph of Sunnyvale, California was scanned, registered to a map grid, and spatially degraded to 1- to 5-metre resolution pixels. Road locations in each data set were extracted using a combination of image processing and CAD programs. These locations were compared to a photointerpretation of road locations to determine a preferred pixel size for the extraction method. Based on road pixel omission error computations, a 3-metre pixel resolution appears to be the best choice for this extraction method. -Authors

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.

Encapsulating urban traffic rhythms into road networks.

PubMed

Wang, Junjie; Wei, Dong; He, Kun; Gong, Hang; Wang, Pu

2014-02-20

Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution.

Encapsulating Urban Traffic Rhythms into Road Networks

PubMed Central

Wang, Junjie; Wei, Dong; He, Kun; Gong, Hang; Wang, Pu

2014-01-01

Using road GIS (geographical information systems) data and travel demand data for two U.S. urban areas, the dynamical driver sources of each road segment were located. A method to target road clusters closely related to urban traffic congestion was then developed to improve road network efficiency. The targeted road clusters show different spatial distributions at different times of a day, indicating that our method can encapsulate dynamical travel demand information into the road networks. As a proof of concept, when we lowered the speed limit or increased the capacity of road segments in the targeted road clusters, we found that both the number of congested roads and extra travel time were effectively reduced. In addition, the proposed modeling framework provided new insights on the optimization of transport efficiency in any infrastructure network with a specific supply and demand distribution. PMID:24553203

A user exposure based approach for non-structural road network vulnerability analysis

PubMed Central

Jin, Lei; Wang, Haizhong; Yu, Le; Liu, Lin

2017-01-01

Aiming at the dense urban road network vulnerability without structural negative consequences, this paper proposes a novel non-structural road network vulnerability analysis framework. Three aspects of the framework are mainly described: (i) the rationality of non-structural road network vulnerability, (ii) the metrics for negative consequences accounting for variant road conditions, and (iii) the introduction of a new vulnerability index based on user exposure. Based on the proposed methodology, a case study in the Sioux Falls network which was usually threatened by regular heavy snow during wintertime is detailedly discussed. The vulnerability ranking of links of Sioux Falls network with respect to heavy snow scenario is identified. As a result of non-structural consequences accompanied by conceivable degeneration of network, there are significant increases in generalized travel time costs which are measurements for “emotionally hurt” of topological road network. PMID:29176832

Analysis of Road Network Pattern Considering Population Distribution and Central Business District

PubMed Central

Zhao, Fangxia; Sun, Huijun; Wu, Jianjun; Gao, Ziyou; Liu, Ronghui

2016-01-01

This paper proposes a road network growing model with the consideration of population distribution and central business district (CBD) attraction. In the model, the relative neighborhood graph (RNG) is introduced as the connection mechanism to capture the characteristics of road network topology. The simulation experiment is set up to illustrate the effects of population distribution and CBD attraction on the characteristics of road network. Moreover, several topological attributes of road network is evaluated by using coverage, circuitness, treeness and total length in the experiment. Finally, the suggested model is verified in the simulation of China and Beijing Highway networks. PMID:26981857

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

Road Damage Extraction from Post-Earthquake Uav Images Assisted by Vector Data

NASA Astrophysics Data System (ADS)

Chen, Z.; Dou, A.

2018-04-01

Extraction of road damage information after earthquake has been regarded as urgent mission. To collect information about stricken areas, Unmanned Aerial Vehicle can be used to obtain images rapidly. This paper put forward a novel method to detect road damage and bring forward a coefficient to assess road accessibility. With the assistance of vector road data, image data of the Jiuzhaigou Ms7.0 Earthquake is tested. In the first, the image is clipped according to vector buffer. Then a large-scale segmentation is applied to remove irrelevant objects. Thirdly, statistics of road features are analysed, and damage information is extracted. Combining with the on-filed investigation, the extraction result is effective.

Visual traffic jam analysis based on trajectory data.

PubMed

Wang, Zuchao; Lu, Min; Yuan, Xiaoru; Zhang, Junping; van de Wetering, Huub

2013-12-01

In this work, we present an interactive system for visual analysis of urban traffic congestion based on GPS trajectories. For these trajectories we develop strategies to extract and derive traffic jam information. After cleaning the trajectories, they are matched to a road network. Subsequently, traffic speed on each road segment is computed and traffic jam events are automatically detected. Spatially and temporally related events are concatenated in, so-called, traffic jam propagation graphs. These graphs form a high-level description of a traffic jam and its propagation in time and space. Our system provides multiple views for visually exploring and analyzing the traffic condition of a large city as a whole, on the level of propagation graphs, and on road segment level. Case studies with 24 days of taxi GPS trajectories collected in Beijing demonstrate the effectiveness of our system.

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.

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.

Automatic Road Gap Detection Using Fuzzy Inference System

NASA Astrophysics Data System (ADS)

Hashemi, S.; Valadan Zoej, M. J.; Mokhtarzadeh, M.

2011-09-01

Automatic feature extraction from aerial and satellite images is a high-level data processing which is still one of the most important research topics of the field. In this area, most of the researches are focused on the early step of road detection, where road tracking methods, morphological analysis, dynamic programming and snakes, multi-scale and multi-resolution methods, stereoscopic and multi-temporal analysis, hyper spectral experiments, are some of the mature methods in this field. Although most researches are focused on detection algorithms, none of them can extract road network perfectly. On the other hand, post processing algorithms accentuated on the refining of road detection results, are not developed as well. In this article, the main is to design an intelligent method to detect and compensate road gaps remained on the early result of road detection algorithms. The proposed algorithm consists of five main steps as follow: 1) Short gap coverage: In this step, a multi-scale morphological is designed that covers short gaps in a hierarchical scheme. 2) Long gap detection: In this step, the long gaps, could not be covered in the previous stage, are detected using a fuzzy inference system. for this reason, a knowledge base consisting of some expert rules are designed which are fired on some gap candidates of the road detection results. 3) Long gap coverage: In this stage, detected long gaps are compensated by two strategies of linear and polynomials for this reason, shorter gaps are filled by line fitting while longer ones are compensated by polynomials.4) Accuracy assessment: In order to evaluate the obtained results, some accuracy assessment criteria are proposed. These criteria are obtained by comparing the obtained results with truly compensated ones produced by a human expert. The complete evaluation of the obtained results whit their technical discussions are the materials of the full paper.

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.

A framework to predict the impacts of shale gas infrastructures on the forest fragmentation of an agroforest region.

PubMed

Racicot, Alexandre; Babin-Roussel, Véronique; Dauphinais, Jean-François; Joly, Jean-Sébastien; Noël, Pascal; Lavoie, Claude

2014-05-01

We propose a framework to facilitate the evaluation of the impacts of shale gas infrastructures (well pads, roads, and pipelines) on land cover features, especially with regards to forest fragmentation. We used a geographic information system and realistic development scenarios largely inspired by the PA (United States) experience, but adapted to a region of QC (Canada) with an already fragmented forest cover and a high gas potential. The scenario with the greatest impact results from development limited by regulatory constraints only, with no access to private roads for connecting well pads to the public road network. The scenario with the lowest impact additionally integrates ecological constraints (deer yards, maple woodlots, and wetlands). Overall the differences between these two scenarios are relatively minor, with <1 % of the forest cover lost in each case. However, large areas of core forests would be lost in both scenarios and the number of forest patches would increase by 13-21 % due to fragmentation. The pipeline network would have a much greater footprint on the land cover than access roads. Using data acquired since the beginning of the shale gas industry, we show that it is possible, within a reasonable time frame, to produce a robust assessment of the impacts of shale gas extraction. The framework we propose could easily be applied to other contexts or jurisdictions.

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.

[Evolution pattern of impervious surface in the Yuqiao Reservoir Watershed, Tianjin, China during the process of urbanization.

PubMed

Xie, Hui Jun; Li, Chong Wei; Zhang, Ya Juan; Song, Ai Yun

2016-04-22

Imperviousness in watershed is a key index to measure urbanization status which exerts an important impact on both eco-hydrological process and spatio-temporal pattern. Taking Yuqiao Reservoir Watershed as a case study area, based on the ENVI 5.1 software, the basic impervious surface information was extracted from remote sensing images taken in 1984, 1994, 2004 and 2013. The linear spectral mixture analysis (LSMA) model was applied to extract the impervious surface area (ISA) in nine coverage classes of watershed in order to analyze its spatio-temporal varying trend in terms of the landscape pattern metrics. Results showed that the RMSE and IS pixel accuracy of all samples were 0.005 and 85.4% respectively, which indicated that the method of extracting impervious surface on a basin scale was feasible. The average of ISA showed a linear growth, from 0.16 to 0.23, the impervious surface area increased by 4.9% in the whole watershed, and the total impervious surface area increased by 1 time. In the sub-basin road network, the impervious surface area increased gradually with the density of the road network, and its expansion pattern was of infilling growth. The patch shape of the middle coverage degree was irregular, and its fragmentation degree was the highest. The fragmentation degree and diversity of the landscape in the whole river basin increased year by year due to increasing human disturbance.

Using Mobile Laser Scanning Data for Features Extraction of High Accuracy Driving Maps

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Liu, Yuan; Liang, Fuxun; Dong, Zhen

2016-06-01

High Accuracy Driving Maps (HADMs) are the core component of Intelligent Drive Assistant Systems (IDAS), which can effectively reduce the traffic accidents due to human error and provide more comfortable driving experiences. Vehicle-based mobile laser scanning (MLS) systems provide an efficient solution to rapidly capture three-dimensional (3D) point clouds of road environments with high flexibility and precision. This paper proposes a novel method to extract road features (e.g., road surfaces, road boundaries, road markings, buildings, guardrails, street lamps, traffic signs, roadside-trees, power lines, vehicles and so on) for HADMs in highway environment. Quantitative evaluations show that the proposed algorithm attains an average precision and recall in terms of 90.6% and 91.2% in extracting road features. Results demonstrate the efficiencies and feasibilities of the proposed method for extraction of road features for HADMs.

A Method for Extracting Road Boundary Information from Crowdsourcing Vehicle GPS Trajectories.

PubMed

Yang, Wei; Ai, Tinghua; Lu, Wei

2018-04-19

Crowdsourcing trajectory data is an important approach for accessing and updating road information. In this paper, we present a novel approach for extracting road boundary information from crowdsourcing vehicle traces based on Delaunay triangulation (DT). First, an optimization and interpolation method is proposed to filter abnormal trace segments from raw global positioning system (GPS) traces and interpolate the optimization segments adaptively to ensure there are enough tracking points. Second, constructing the DT and the Voronoi diagram within interpolated tracking lines to calculate road boundary descriptors using the area of Voronoi cell and the length of triangle edge. Then, the road boundary detection model is established integrating the boundary descriptors and trajectory movement features (e.g., direction) by DT. Third, using the boundary detection model to detect road boundary from the DT constructed by trajectory lines, and a regional growing method based on seed polygons is proposed to extract the road boundary. Experiments were conducted using the GPS traces of taxis in Beijing, China, and the results show that the proposed method is suitable for extracting the road boundary from low-frequency GPS traces, multi-type road structures, and different time intervals. Compared with two existing methods, the automatically extracted boundary information was proved to be of higher quality.

A Method for Extracting Road Boundary Information from Crowdsourcing Vehicle GPS Trajectories

PubMed Central

Yang, Wei

2018-01-01

Crowdsourcing trajectory data is an important approach for accessing and updating road information. In this paper, we present a novel approach for extracting road boundary information from crowdsourcing vehicle traces based on Delaunay triangulation (DT). First, an optimization and interpolation method is proposed to filter abnormal trace segments from raw global positioning system (GPS) traces and interpolate the optimization segments adaptively to ensure there are enough tracking points. Second, constructing the DT and the Voronoi diagram within interpolated tracking lines to calculate road boundary descriptors using the area of Voronoi cell and the length of triangle edge. Then, the road boundary detection model is established integrating the boundary descriptors and trajectory movement features (e.g., direction) by DT. Third, using the boundary detection model to detect road boundary from the DT constructed by trajectory lines, and a regional growing method based on seed polygons is proposed to extract the road boundary. Experiments were conducted using the GPS traces of taxis in Beijing, China, and the results show that the proposed method is suitable for extracting the road boundary from low-frequency GPS traces, multi-type road structures, and different time intervals. Compared with two existing methods, the automatically extracted boundary information was proved to be of higher quality. PMID:29671792

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.

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.

The impact of logging roads on dung beetle assemblages in a tropical rainforest reserve.

PubMed

Edwards, Felicity A; Finan, Jessica; Graham, Lucy K; Larsen, Trond H; Wilcove, David S; Hsu, Wayne W; Chey, V K; Hamer, Keith C

2017-01-01

The demand for timber products is facilitating the degradation and opening up of large areas of intact habitats rich in biodiversity. Logging creates an extensive network of access roads within the forest, yet these are commonly ignored or excluded when assessing impacts of logging on forest biodiversity. Here we determine the impact of these roads on the overall condition of selectively logged forests in Borneo, Southeast Asia. Focusing on dung beetles along > 40 km logging roads we determine: (i) the magnitude and extent of edge effects alongside logging roads; (ii) whether vegetation characteristics can explain patterns in dung beetle communities, and; (iii) how the inclusion of road edge forest impacts dung beetle assemblages within the overall logged landscape. We found that while vegetation structure was significantly affected up to 34 m from the road edge, impacts on dung beetle communities penetrated much further and were discernible up to 170 m into the forest interior. We found larger species and particularly tunnelling species responded more than other functional groups which were also influenced by micro-habitat variation. We provide important new insights into the long-term ecological impacts of tropical logging. We also support calls for improved logging road design both during and after timber extraction to conserve more effectively biodiversity in production forests, for instance, by considering the minimum volume of timber, per unit length of logging road needed to justify road construction. In particular, we suggest that governments and certification bodies need to highlight more clearly the biodiversity and environmental impacts of logging roads.

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.

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.

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.

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.

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

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.

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.

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.

Exploring the evolution of London's street network in the information space: A dual approach

NASA Astrophysics Data System (ADS)

Masucci, A. Paolo; Stanilov, Kiril; Batty, Michael

2014-01-01

We study the growth of London's street network in its dual representation, as the city has evolved over the past 224 years. The dual representation of a planar graph is a content-based network, where each node is a set of edges of the planar graph and represents a transportation unit in the so-called information space, i.e., the space where information is handled in order to navigate through the city. First, we discuss a novel hybrid technique to extract dual graphs from planar graphs, called the hierarchical intersection continuity negotiation principle. Then we show that the growth of the network can be analytically described by logistic laws and that the topological properties of the network are governed by robust log-normal distributions characterizing the network's connectivity and small-world properties that are consistent over time. Moreover, we find that the double-Pareto-like distributions for the connectivity emerge for major roads and can be modeled via a stochastic content-based network model using simple space-filling principles.

A tank-to-wheel analysis tool for energy and emissions studies in road vehicles.

PubMed

Silva, C M; Gonçalves, G A; Farias, T L; Mendes-Lopes, J M C

2006-08-15

Currently, oil based fuels are the primary energy source of road transport. The growing need for oil independence and CO(2) mitigation has lead to the increasing importance of alternative fuel usage. CO(2) is produced not only as the fuel is used in the vehicle (tank-to-wheel contribution), but also upstream, from the fuel extraction to the refueling station (well-to-tank contribution), and the life cycle of the fuel production (well-to-wheel contribution) must be considered in order to analyse the global impact of the fuel utilization. A road vehicle tank-to-wheel analysis tool that may be integrated with well-to-tank models was developed in the present study. The integration in a demonstration case study allowed to perform a life cycle assessment concerning the utilization of diesel and natural gas fuels in a specific network line of a bus transit company operating in the city of Porto, Portugal.

An evaluation of object-oriented image analysis techniques to identify motorized vehicle effects in semi-arid to arid ecosystems of the American West

USGS Publications Warehouse

Mladinich, C.

2010-01-01

Human disturbance is a leading ecosystem stressor. Human-induced modifications include transportation networks, areal disturbances due to resource extraction, and recreation activities. High-resolution imagery and object-oriented classification rather than pixel-based techniques have successfully identified roads, buildings, and other anthropogenic features. Three commercial, automated feature-extraction software packages (Visual Learning Systems' Feature Analyst, ENVI Feature Extraction, and Definiens Developer) were evaluated by comparing their ability to effectively detect the disturbed surface patterns from motorized vehicle traffic. Each package achieved overall accuracies in the 70% range, demonstrating the potential to map the surface patterns. The Definiens classification was more consistent and statistically valid. Copyright ?? 2010 by Bellwether Publishing, Ltd. All rights reserved.

Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction.

PubMed

Ma, Xiaolei; Dai, Zhuang; He, Zhengbing; Ma, Jihui; Wang, Yong; Wang, Yunpeng

2017-04-10

This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks.

Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction

PubMed Central

Ma, Xiaolei; Dai, Zhuang; He, Zhengbing; Ma, Jihui; Wang, Yong; Wang, Yunpeng

2017-01-01

This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks. PMID:28394270

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.

3D local feature BKD to extract road information from mobile laser scanning point clouds

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Liu, Yuan; Dong, Zhen; Liang, Fuxun; Li, Bijun; Peng, Xiangyang

2017-08-01

Extracting road information from point clouds obtained through mobile laser scanning (MLS) is essential for autonomous vehicle navigation, and has hence garnered a growing amount of research interest in recent years. However, the performance of such systems is seriously affected due to varying point density and noise. This paper proposes a novel three-dimensional (3D) local feature called the binary kernel descriptor (BKD) to extract road information from MLS point clouds. The BKD consists of Gaussian kernel density estimation and binarization components to encode the shape and intensity information of the 3D point clouds that are fed to a random forest classifier to extract curbs and markings on the road. These are then used to derive road information, such as the number of lanes, the lane width, and intersections. In experiments, the precision and recall of the proposed feature for the detection of curbs and road markings on an urban dataset and a highway dataset were as high as 90%, thus showing that the BKD is accurate and robust against varying point density and noise.

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.

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.

Identification of platinum nanoparticles in road dust leachate by single particle inductively coupled plasma-mass spectrometry.

PubMed

Folens, Karel; Van Acker, Thibaut; Bolea-Fernandez, Eduardo; Cornelis, Geert; Vanhaecke, Frank; Du Laing, Gijs; Rauch, Sebastien

2018-02-15

Elevated platinum (Pt) concentrations are found in road dust as a result of emissions from catalytic converters in vehicles. This study investigates the occurrence of Pt in road dust collected in Ghent (Belgium) and Gothenburg (Sweden). Total Pt contents, determined by tandem ICP-mass spectrometry (ICP-MS/MS), were in the range of 5 to 79ngg -1 , comparable to the Pt content in road dust of other medium-sized cities. Further sample characterization was performed by single particle (sp) ICP-MS following an ultrasonic extraction procedure using stormwater runoff for leaching. The method was found to be suitable for the characterization of Pt nanoparticles in road dust leachates. The extraction was optimized using road dust reference material BCR-723, for which an extraction efficiency of 2.7% was obtained by applying 144kJ of ultrasonic energy. Using this method, between 0.2% and 18% of the Pt present was extracted from road dust samples. spICP-MS analysis revealed that Pt in the leachate is entirely present as nanoparticles of sizes between 9 and 21nm. Although representing only a minor fraction of the total content in road dust, the nanoparticulate Pt leachate is most susceptible to biological uptake and hence most relevant in terms of bioavailability. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Fusion method of SAR and optical images for urban object extraction

NASA Astrophysics Data System (ADS)

Jia, Yonghong; Blum, Rick S.; Li, Fangfang

2007-11-01

A new image fusion method of SAR, Panchromatic (Pan) and multispectral (MS) data is proposed. First of all, SAR texture is extracted by ratioing the despeckled SAR image to its low pass approximation, and is used to modulate high pass details extracted from the available Pan image by means of the á trous wavelet decomposition. Then, high pass details modulated with the texture is applied to obtain the fusion product by HPFM (High pass Filter-based Modulation) fusion method. A set of image data including co-registered Landsat TM, ENVISAT SAR and SPOT Pan is used for the experiment. The results demonstrate accurate spectral preservation on vegetated regions, bare soil, and also on textured areas (buildings and road network) where SAR texture information enhances the fusion product, and the proposed approach is effective for image interpret and classification.

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...

[Road Extraction in Remote Sensing Images Based on Spectral and Edge Analysis].

PubMed

Zhao, Wen-zhi; Luo, Li-qun; Guo, Zhou; Yue, Jun; Yu, Xue-ying; Liu, Hui; Wei, Jing

2015-10-01

Roads are typically man-made objects in urban areas. Road extraction from high-resolution images has important applications for urban planning and transportation development. However, due to the confusion of spectral characteristic, it is difficult to distinguish roads from other objects by merely using traditional classification methods that mainly depend on spectral information. Edge is an important feature for the identification of linear objects (e. g. , roads). The distribution patterns of edges vary greatly among different objects. It is crucial to merge edge statistical information into spectral ones. In this study, a new method that combines spectral information and edge statistical features has been proposed. First, edge detection is conducted by using self-adaptive mean-shift algorithm on the panchromatic band, which can greatly reduce pseudo-edges and noise effects. Then, edge statistical features are obtained from the edge statistical model, which measures the length and angle distribution of edges. Finally, by integrating the spectral and edge statistical features, SVM algorithm is used to classify the image and roads are ultimately extracted. A series of experiments are conducted and the results show that the overall accuracy of proposed method is 93% comparing with only 78% overall accuracy of the traditional. The results demonstrate that the proposed method is efficient and valuable for road extraction, especially on high-resolution images.

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.

Automatic Blocked Roads Assessment after Earthquake Using High Resolution Satellite Imagery

NASA Astrophysics Data System (ADS)

Rastiveis, H.; Hosseini-Zirdoo, E.; Eslamizade, F.

2015-12-01

In 2010, an earthquake in the city of Port-au-Prince, Haiti, happened quite by chance an accident and killed over 300000 people. According to historical data such an earthquake has not occurred in the area. Unpredictability of earthquakes has necessitated the need for comprehensive mitigation efforts to minimize deaths and injuries. Blocked roads, caused by debris of destroyed buildings, may increase the difficulty of rescue activities. In this case, a damage map, which specifies blocked and unblocked roads, can be definitely helpful for a rescue team. In this paper, a novel method for providing destruction map based on pre-event vector map and high resolution world view II satellite images after earthquake, is presented. For this purpose, firstly in pre-processing step, image quality improvement and co-coordination of image and map are performed. Then, after extraction of texture descriptor from the image after quake and SVM classification, different terrains are detected in the image. Finally, considering the classification results, specifically objects belong to "debris" class, damage analysis are performed to estimate the damage percentage. In this case, in addition to the area objects in the "debris" class their shape should also be counted. The aforementioned process are performed on all the roads in the road layer.In this research, pre-event digital vector map and post-event high resolution satellite image, acquired by Worldview-2, of the city of Port-au-Prince, Haiti's capital, were used to evaluate the proposed method. The algorithm was executed on 1200×800 m2 of the data set, including 60 roads, and all the roads were labelled correctly. The visual examination have authenticated the abilities of this method for damage assessment of urban roads network after an earthquake.

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.

Automatic drawing for traffic marking with MMS LIDAR intensity

NASA Astrophysics Data System (ADS)

Takahashi, G.; Takeda, H.; Shimano, Y.

2014-05-01

Upgrading the database of CYBER JAPAN has been strategically promoted because the "Basic Act on Promotion of Utilization of Geographical Information", was enacted in May 2007. In particular, there is a high demand for road information that comprises a framework in this database. Therefore, road inventory mapping work has to be accurate and eliminate variation caused by individual human operators. Further, the large number of traffic markings that are periodically maintained and possibly changed require an efficient method for updating spatial data. Currently, we apply manual photogrammetry drawing for mapping traffic markings. However, this method is not sufficiently efficient in terms of the required productivity, and data variation can arise from individual operators. In contrast, Mobile Mapping Systems (MMS) and high-density Laser Imaging Detection and Ranging (LIDAR) scanners are rapidly gaining popularity. The aim in this study is to build an efficient method for automatically drawing traffic markings using MMS LIDAR data. The key idea in this method is extracting lines using a Hough transform strategically focused on changes in local reflection intensity along scan lines. However, also note that this method processes every traffic marking. In this paper, we discuss a highly accurate and non-human-operator-dependent method that applies the following steps: (1) Binarizing LIDAR points by intensity and extracting higher intensity points; (2) Generating a Triangulated Irregular Network (TIN) from higher intensity points; (3) Deleting arcs by length and generating outline polygons on the TIN; (4) Generating buffers from the outline polygons; (5) Extracting points from the buffers using the original LIDAR points; (6) Extracting local-intensity-changing points along scan lines using the extracted points; (7) Extracting lines from intensity-changing points through a Hough transform; and (8) Connecting lines to generate automated traffic marking mapping data.

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 Study on the Influence of Speed on Road Roughness Sensing: The SmartRoadSense Case †

PubMed Central

Alessandroni, Giacomo; Carini, Alberto; Lattanzi, Emanuele; Freschi, Valerio; Bogliolo, Alessandro

2017-01-01

SmartRoadSense is a crowdsensing project aimed at monitoring the conditions of the road surface. Using the sensors of a smartphone, SmartRoadSense monitors the vertical accelerations inside a vehicle traveling the road and extracts a roughness index conveying information about the road conditions. The roughness index and the smartphone GPS data are periodically sent to a central server where they are processed, associated with the specific road, and aggregated with data measured by other smartphones. This paper studies how the smartphone vertical accelerations and the roughness index are related to the vehicle speed. It is shown that the dependence can be locally approximated with a gamma (power) law. Extensive experimental results using data extracted from SmartRoadSense database confirm the gamma law relationship between the roughness index and the vehicle speed. The gamma law is then used for improving the SmartRoadSense data aggregation accounting for the effect of vehicle speed. PMID:28178224

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.

Road Development and the Geography of Hunting by an Amazonian Indigenous Group: Consequences for Wildlife Conservation

PubMed Central

Espinosa, Santiago; Branch, Lyn C.; Cueva, Rubén

2014-01-01

Protected areas are essential for conservation of wildlife populations. However, in the tropics there are two important factors that may interact to threaten this objective: 1) road development associated with large-scale resource extraction near or within protected areas; and 2) historical occupancy by traditional or indigenous groups that depend on wildlife for their survival. To manage wildlife populations in the tropics, it is critical to understand the effects of roads on the spatial extent of hunting and how wildlife is used. A geographical analysis can help us answer questions such as: How do roads affect spatial extent of hunting? How does market vicinity relate to local consumption and trade of bushmeat? How does vicinity to markets influence choice of game? A geographical analysis also can help evaluate the consequences of increased accessibility in landscapes that function as source-sink systems. We applied spatial analyses to evaluate the effects of increased landscape and market accessibility by road development on spatial extent of harvested areas and wildlife use by indigenous hunters. Our study was conducted in Yasuní Biosphere Reserve, Ecuador, which is impacted by road development for oil extraction, and inhabited by the Waorani indigenous group. Hunting activities were self-reported for 12–14 months and each kill was georeferenced. Presence of roads was associated with a two-fold increase of the extraction area. Rates of bushmeat extraction and trade were higher closer to markets than further away. Hunters located closer to markets concentrated their effort on large-bodied species. Our results clearly demonstrate that placing roads within protected areas can seriously reduce their capacity to sustain wildlife populations and potentially threaten livelihoods of indigenous groups who depend on these resources for their survival. Our results critically inform current policy debates regarding resource extraction and road building near or within protected areas. PMID:25489954

Road development and the geography of hunting by an Amazonian indigenous group: consequences for wildlife conservation.

PubMed

Espinosa, Santiago; Branch, Lyn C; Cueva, Rubén

2014-01-01

Protected areas are essential for conservation of wildlife populations. However, in the tropics there are two important factors that may interact to threaten this objective: 1) road development associated with large-scale resource extraction near or within protected areas; and 2) historical occupancy by traditional or indigenous groups that depend on wildlife for their survival. To manage wildlife populations in the tropics, it is critical to understand the effects of roads on the spatial extent of hunting and how wildlife is used. A geographical analysis can help us answer questions such as: How do roads affect spatial extent of hunting? How does market vicinity relate to local consumption and trade of bushmeat? How does vicinity to markets influence choice of game? A geographical analysis also can help evaluate the consequences of increased accessibility in landscapes that function as source-sink systems. We applied spatial analyses to evaluate the effects of increased landscape and market accessibility by road development on spatial extent of harvested areas and wildlife use by indigenous hunters. Our study was conducted in Yasuní Biosphere Reserve, Ecuador, which is impacted by road development for oil extraction, and inhabited by the Waorani indigenous group. Hunting activities were self-reported for 12-14 months and each kill was georeferenced. Presence of roads was associated with a two-fold increase of the extraction area. Rates of bushmeat extraction and trade were higher closer to markets than further away. Hunters located closer to markets concentrated their effort on large-bodied species. Our results clearly demonstrate that placing roads within protected areas can seriously reduce their capacity to sustain wildlife populations and potentially threaten livelihoods of indigenous groups who depend on these resources for their survival. Our results critically inform current policy debates regarding resource extraction and road building near or within protected areas.

Automatic Extraction of Road Markings from Mobile Laser-Point Cloud Using Intensity Data

NASA Astrophysics Data System (ADS)

Yao, L.; Chen, Q.; Qin, C.; Wu, H.; Zhang, S.

2018-04-01

With the development of intelligent transportation, road's high precision information data has been widely applied in many fields. This paper proposes a concise and practical way to extract road marking information from point cloud data collected by mobile mapping system (MMS). The method contains three steps. Firstly, road surface is segmented through edge detection from scan lines. Then the intensity image is generated by inverse distance weighted (IDW) interpolation and the road marking is extracted by using adaptive threshold segmentation based on integral image without intensity calibration. Moreover, the noise is reduced by removing a small number of plaque pixels from binary image. Finally, point cloud mapped from binary image is clustered into marking objects according to Euclidean distance, and using a series of algorithms including template matching and feature attribute filtering for the classification of linear markings, arrow markings and guidelines. Through processing the point cloud data collected by RIEGL VUX-1 in case area, the results show that the F-score of marking extraction is 0.83, and the average classification rate is 0.9.

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.

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.

Road marking features extraction using the VIAPIX® system

NASA Astrophysics Data System (ADS)

Kaddah, W.; Ouerhani, Y.; Alfalou, A.; Desthieux, M.; Brosseau, C.; Gutierrez, C.

2016-07-01

Precise extraction of road marking features is a critical task for autonomous urban driving, augmented driver assistance, and robotics technologies. In this study, we consider an autonomous system allowing us lane detection for marked urban roads and analysis of their features. The task is to relate the georeferencing of road markings from images obtained using the VIAPIX® system. Based on inverse perspective mapping and color segmentation to detect all white objects existing on this road, the present algorithm enables us to examine these images automatically and rapidly and also to get information on road marks, their surface conditions, and their georeferencing. This algorithm allows detecting all road markings and identifying some of them by making use of a phase-only correlation filter (POF). We illustrate this algorithm and its robustness by applying it to a variety of relevant scenarios.

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.

Automatic Extraction of Road Markings from Mobile Laser Scanning Data

NASA Astrophysics Data System (ADS)

Ma, H.; Pei, Z.; Wei, Z.; Zhong, R.

2017-09-01

Road markings as critical feature in high-defination maps, which are Advanced Driver Assistance System (ADAS) and self-driving technology required, have important functions in providing guidance and information to moving cars. Mobile laser scanning (MLS) system is an effective way to obtain the 3D information of the road surface, including road markings, at highway speeds and at less than traditional survey costs. This paper presents a novel method to automatically extract road markings from MLS point clouds. Ground points are first filtered from raw input point clouds using neighborhood elevation consistency method. The basic assumption of the method is that the road surface is smooth. Points with small elevation-difference between neighborhood are considered to be ground points. Then ground points are partitioned into a set of profiles according to trajectory data. The intensity histogram of points in each profile is generated to find intensity jumps in certain threshold which inversely to laser distance. The separated points are used as seed points to region grow based on intensity so as to obtain road mark of integrity. We use the point cloud template-matching method to refine the road marking candidates via removing the noise clusters with low correlation coefficient. During experiment with a MLS point set of about 2 kilometres in a city center, our method provides a promising solution to the road markings extraction from MLS data.

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.

Analysis of Urban Expansion of the Resort City of Al Ain Using Remote Sensing and GIS

NASA Astrophysics Data System (ADS)

Issa, S.; Al Shuwaihi, A.

2009-12-01

The urban growth of AL Ain city has been investigated using remote sensing data for three different dates, 1972, 1990 and 2000. We used three Landsat images together with socio-economic data in a post-classification analysis to map the spatial dynamics of land use/cover changes and identify the urbanization process in Al Ain resort city, United Arab Emirates. Land use/cover statistics, extracted from Landsat Multi-spectral Scanner (MSS). Thematic Mapper (TM) and Enhanced Thematic Mapper plus (ETM +) images for 1972. 1990 and 2000 respectively, revealed that the built-up area has expanded by about 170.53km2. The city was found to have a tendency for major expansion in four different directions: along the Abu Dhabi highway, along Dubai highway, Myziad direction and Hafeet recreational area. Expansion in any direction was found to be governed by the availability of road network, suitability for construction, utilities, economic activities, geographical constraints, and legal factors (boundary with Sultanate of Oman). The road network in particular has influenced the spatial patterns and structure of urban development, so that the expansion of the built-up areas has assumed an accretive as well as linear growth along the major roads. The research concludes that the development is based on conservation of agricultural areas (oases) and reclamation of the desert for farming and agricultural activities. The integration of remote sensing and GIS was found to be effective in monitoring LULC changes and providing valuable information necessary for planning and research.

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.

Multi-Feature Based Information Extraction of Urban Green Space Along Road

NASA Astrophysics Data System (ADS)

Zhao, H. H.; Guan, H. Y.

2018-04-01

Green space along road of QuickBird image was studied in this paper based on multi-feature-marks in frequency domain. The magnitude spectrum of green along road was analysed, and the recognition marks of the tonal feature, contour feature and the road were built up by the distribution of frequency channels. Gabor filters in frequency domain were used to detect the features based on the recognition marks built up. The detected features were combined as the multi-feature-marks, and watershed based image segmentation were conducted to complete the extraction of green space along roads. The segmentation results were evaluated by Fmeasure with P = 0.7605, R = 0.7639, F = 0.7622.

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.

A bibliometric analysis of the published road traffic injuries research in India, post-1990.

PubMed

Sharma, Neeraj; Bairwa, Mohan; Gowthamghosh, B; Gupta, S D; Mangal, D K

2018-03-01

Globally, road traffic injuries are the leading cause of death among those aged 15-29 years. However, road traffic injury research has not received adequate attention from the scientific community in low- and middle-income countries, including India. The present study aims to provide a bibliometric overview of research assessing road traffic injuries in India. We used Scopus to extract relevant research in road traffic injuries published from 1991 to 2017. This study presented the key bibliometric indicators such as trends of annual publications and citations, top 10 authors, journals, institutions and highly cited articles, citation analysis of articles, co-occurrence of keywords, etc. Analysis was performed using Scopus, Microsoft Excel, and VOS-viewer. A total of 242 articles were retrieved with an h-index of 18, excluding self-citations. A steadfast growth of publications was documented in last decade, especially after the year 2010. The h-index of the top 10 authors, institutions, journals and highly cited articles did not surpass single digits. A network visualisation map showed that 'traffic accident', 'male', 'adolescent' and 'child' were the most commonly encountered key terms. The prominent authors were Gururaj G, Dandona R, and Hyder AA, whereas the top journals were the Indian Journal of Forensic Medicine and Toxicology, Medico Legal Update, and the International Journal of Applied Engineering Research and top institutions were the All India Institute of Medical Sciences, New Delhi, the Indian Institute of Technology, Delhi, and the Administrative Staff College of India. In India, road traffic injuries research is inadequate in quantity and quality, warranting greater attention from researchers and policy planners to address the burden of road traffic injuries.

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.

Semantic Segmentation and Difference Extraction via Time Series Aerial Video Camera and its Application

NASA Astrophysics Data System (ADS)

Amit, S. N. K.; Saito, S.; Sasaki, S.; Kiyoki, Y.; Aoki, Y.

2015-04-01

Google earth with high-resolution imagery basically takes months to process new images before online updates. It is a time consuming and slow process especially for post-disaster application. The objective of this research is to develop a fast and effective method of updating maps by detecting local differences occurred over different time series; where only region with differences will be updated. In our system, aerial images from Massachusetts's road and building open datasets, Saitama district datasets are used as input images. Semantic segmentation is then applied to input images. Semantic segmentation is a pixel-wise classification of images by implementing deep neural network technique. Deep neural network technique is implemented due to being not only efficient in learning highly discriminative image features such as road, buildings etc., but also partially robust to incomplete and poorly registered target maps. Then, aerial images which contain semantic information are stored as database in 5D world map is set as ground truth images. This system is developed to visualise multimedia data in 5 dimensions; 3 dimensions as spatial dimensions, 1 dimension as temporal dimension, and 1 dimension as degenerated dimensions of semantic and colour combination dimension. Next, ground truth images chosen from database in 5D world map and a new aerial image with same spatial information but different time series are compared via difference extraction method. The map will only update where local changes had occurred. Hence, map updating will be cheaper, faster and more effective especially post-disaster application, by leaving unchanged region and only update changed region.

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.

Identification of the potential gap areas for the developing green infrastructure in the Urban area using High resolution satellite Imagery

NASA Astrophysics Data System (ADS)

Kanaparthi, M. B.

2017-12-01

In India urban population is growing day by day which is causing air pollution less air quality finally leading to climate change and global warming. To mitigate the effect of the climate change we need to plant more trees in the urban area. The objective of this study is develop a plan to improve the urban Green Infrastructure (GI) to fight against the climate change and global warming. Improving GI is a challenging and difficult task in the urban areas because land unavailability of land, to overcome the problem greenways is a good the solution. Greenway is a linear open space developed along the rivers, canals, roads in the urban areas to form a network of green spaces. Roads are the most common structures in the urban area. The idea is to develop the greenways alongside the road to connecting the different green spaces. Tree crowns will act as culverts to connect the green spaces. This will require the spatial structure of the green space, distribution of trees along the roads and the gap areas along the road where more trees can be planted. This can be achieved with help of high resolution Satellite Imagery and the object extraction techniques. This study was carried in the city Bhimavaram which is located in state Andhra Pradesh. The final outcome of this study is potential gap areas for planting trees in the city.

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.

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

The Segmentation of Point Clouds with K-Means and ANN (artifical Neural Network)

NASA Astrophysics Data System (ADS)

Kuçak, R. A.; Özdemir, E.; Erol, S.

2017-05-01

Segmentation of point clouds is recently used in many Geomatics Engineering applications such as the building extraction in urban areas, Digital Terrain Model (DTM) generation and the road or urban furniture extraction. Segmentation is a process of dividing point clouds according to their special characteristic layers. The present paper discusses K-means and self-organizing map (SOM) which is a type of ANN (Artificial Neural Network) segmentation algorithm which treats the segmentation of point cloud. The point clouds which generate with photogrammetric method and Terrestrial Lidar System (TLS) were segmented according to surface normal, intensity and curvature. Thus, the results were evaluated. LIDAR (Light Detection and Ranging) and Photogrammetry are commonly used to obtain point clouds in many remote sensing and geodesy applications. By photogrammetric method or LIDAR method, it is possible to obtain point cloud from terrestrial or airborne systems. In this study, the measurements were made with a Leica C10 laser scanner in LIDAR method. In photogrammetric method, the point cloud was obtained from photographs taken from the ground with a 13 MP non-metric camera.

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.

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.

Oil industry and road traffic fatalities in contemporary Colombia.

PubMed

Tasciotti, Luca; Alejo, Didier; Romero, Andrés

2016-12-01

This paper studies the effects that oil extraction activities in Colombia have on the number of dead/injured people as a consequence of road-related accidents. Starting in 2004, the increasing exploitation of oil wells in some Colombian departments has worsened the traffic conditions due to the increased presence of trucks transporting crude oil from the wells to the refineries; this phenomenon has not been accompanied by an improvement in the road system with dramatic consequences in terms of road viability. The descriptive and empirical analysis presented here focuses on the period 2004-2011; results from descriptive statistics indicate a positive relationship between the presence of oil extraction activities and the number of either dead/injured people. Panel regressions for the period 2004-2011 confirm that, among other factors, the presence of oil-extraction activities did play a positive and statistical significant role in increasing the number of dead/injured people.

Road extraction from aerial images using a region competition algorithm.

PubMed

Amo, Miriam; Martínez, Fernando; Torre, Margarita

2006-05-01

In this paper, we present a user-guided method based on the region competition algorithm to extract roads, and therefore we also provide some clues concerning the placement of the points required by the algorithm. The initial points are analyzed in order to find out whether it is necessary to add more initial points, and this process will be based on image information. Not only is the algorithm able to obtain the road centerline, but it also recovers the road sides. An initial simple model is deformed by using region growing techniques to obtain a rough road approximation. This model will be refined by region competition. The result of this approach is that it delivers the simplest output vector information, fully recovering the road details as they are on the image, without performing any kind of symbolization. Therefore, we tried to refine a general road model by using a reliable method to detect transitions between regions. This method is proposed in order to obtain information for feeding large-scale Geographic Information System.

Spatial Distribution Characteristics of Healthcare Facilities in Nanjing: Network Point Pattern Analysis and Correlation Analysis.

PubMed

Ni, Jianhua; Qian, Tianlu; Xi, Changbai; Rui, Yikang; Wang, Jiechen

2016-08-18

The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities.

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...

Characterizing spatial variability of air pollution from vehicle traffic around the Houston Ship Channel area

NASA Astrophysics Data System (ADS)

Zhang, Xueying; Craft, Elena; Zhang, Kai

2017-07-01

Mobile emissions are a major source of urban air pollution and have been associated with a variety of adverse health outcomes. The Houston Ship Channel area is the home of a large number of diesel-powered vehicles emitting fine particulate matter (PM2.5; ≤2.5 μm in aerodynamic diameter) and nitrogen oxides (NOx). However, the spatial variability of traffic-related air pollutants in the Houston Ship Channel area has rarely been investigated. The objective of this study is to characterize spatial variability of PM2.5 and NOx concentrations attributable to on-road traffic in the Houston Ship Channel area in the year of 2011. We extracted the road network from the Texas Department of Transportation Road Inventory, and calculated emission rates using the Motor Vehicle Emission Simulator version 2014a (MOVES2014a). These parameters and preprocessed meteorological parameters were entered into a Research LINE-source Dispersion Model (RLINE) to conduct a simulation. Receptors were placed at 50 m resolution within 300 m to major roads and at 150 m resolution in the rest of the area. Our findings include that traffic-related PM2.5 were mainly emitted from trucks, while traffic-related NOx were emitted from both trucks and cars. The traffic contributed 0.90 μg/m3 PM2.5 and 29.23 μg/m3 NOx to the annual average mass concentrations of on-road air pollution, and the concentrations of the two pollutants decreased by nearly 40% within 500 m distance to major roads. The pollution level of traffic-related PM2.5 and NOx was higher in winter than those in the other three seasons. The Houston Ship Channel has earlier morning peak hours and relative late afternoon hours, which indicates the influence of goods movement from port activity. The varied near-road gradients illustrate that proximities to major roads are not an accurate surrogate of traffic-related air pollution.

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...

Estimating Vehicle Fuel Consumption and Emissions Using GPS Big Data

PubMed Central

Kan, Zihan; Zhang, Xia

2018-01-01

The energy consumption and emissions from vehicles adversely affect human health and urban sustainability. Analysis of GPS big data collected from vehicles can provide useful insights about the quantity and distribution of such energy consumption and emissions. Previous studies, which estimated fuel consumption/emissions from traffic based on GPS sampled data, have not sufficiently considered vehicle activities and may have led to erroneous estimations. By adopting the analytical construct of the space-time path in time geography, this study proposes methods that more accurately estimate and visualize vehicle energy consumption/emissions based on analysis of vehicles’ mobile activities (MA) and stationary activities (SA). First, we build space-time paths of individual vehicles, extract moving parameters, and identify MA and SA from each space-time path segment (STPS). Then we present an N-Dimensional framework for estimating and visualizing fuel consumption/emissions. For each STPS, fuel consumption, hot emissions, and cold start emissions are estimated based on activity type, i.e., MA, SA with engine-on and SA with engine-off. In the case study, fuel consumption and emissions of a single vehicle and a road network are estimated and visualized with GPS data. The estimation accuracy of the proposed approach is 88.6%. We also analyze the types of activities that produced fuel consumption on each road segment to explore the patterns and mechanisms of fuel consumption in the study area. The results not only show the effectiveness of the proposed approaches in estimating fuel consumption/emissions but also indicate their advantages for uncovering the relationships between fuel consumption and vehicles’ activities in road networks. PMID:29561813

Estimating Vehicle Fuel Consumption and Emissions Using GPS Big Data.

PubMed

Kan, Zihan; Tang, Luliang; Kwan, Mei-Po; Zhang, Xia

2018-03-21

The energy consumption and emissions from vehicles adversely affect human health and urban sustainability. Analysis of GPS big data collected from vehicles can provide useful insights about the quantity and distribution of such energy consumption and emissions. Previous studies, which estimated fuel consumption/emissions from traffic based on GPS sampled data, have not sufficiently considered vehicle activities and may have led to erroneous estimations. By adopting the analytical construct of the space-time path in time geography, this study proposes methods that more accurately estimate and visualize vehicle energy consumption/emissions based on analysis of vehicles' mobile activities ( MA ) and stationary activities ( SA ). First, we build space-time paths of individual vehicles, extract moving parameters, and identify MA and SA from each space-time path segment (STPS). Then we present an N-Dimensional framework for estimating and visualizing fuel consumption/emissions. For each STPS, fuel consumption, hot emissions, and cold start emissions are estimated based on activity type, i.e., MA , SA with engine-on and SA with engine-off. In the case study, fuel consumption and emissions of a single vehicle and a road network are estimated and visualized with GPS data. The estimation accuracy of the proposed approach is 88.6%. We also analyze the types of activities that produced fuel consumption on each road segment to explore the patterns and mechanisms of fuel consumption in the study area. The results not only show the effectiveness of the proposed approaches in estimating fuel consumption/emissions but also indicate their advantages for uncovering the relationships between fuel consumption and vehicles' activities in road networks.

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.

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...

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

FEX: A Knowledge-Based System For Planimetric Feature Extraction

NASA Astrophysics Data System (ADS)

Zelek, John S.

1988-10-01

Topographical planimetric features include natural surfaces (rivers, lakes) and man-made surfaces (roads, railways, bridges). In conventional planimetric feature extraction, a photointerpreter manually interprets and extracts features from imagery on a stereoplotter. Visual planimetric feature extraction is a very labour intensive operation. The advantages of automating feature extraction include: time and labour savings; accuracy improvements; and planimetric data consistency. FEX (Feature EXtraction) combines techniques from image processing, remote sensing and artificial intelligence for automatic feature extraction. The feature extraction process co-ordinates the information and knowledge in a hierarchical data structure. The system simulates the reasoning of a photointerpreter in determining the planimetric features. Present efforts have concentrated on the extraction of road-like features in SPOT imagery. Keywords: Remote Sensing, Artificial Intelligence (AI), SPOT, image understanding, knowledge base, apars.

Tyre-road grip coefficient assessment - Part II: online estimation using instrumented vehicle, extended Kalman filter, and neural network

NASA Astrophysics Data System (ADS)

Luque, Pablo; Mántaras, Daniel A.; Fidalgo, Eloy; Álvarez, Javier; Riva, Paolo; Girón, Pablo; Compadre, Diego; Ferran, Jordi

2013-12-01

The main objective of this work is to determine the limit of safe driving conditions by identifying the maximal friction coefficient in a real vehicle. The study will focus on finding a method to determine this limit before reaching the skid, which is valuable information in the context of traffic safety. Since it is not possible to measure the friction coefficient directly, it will be estimated using the appropriate tools in order to get the most accurate information. A real vehicle is instrumented to collect information of general kinematics and steering tie-rod forces. A real-time algorithm is developed to estimate forces and aligning torque in the tyres using an extended Kalman filter and neural networks techniques. The methodology is based on determining the aligning torque; this variable allows evaluation of the behaviour of the tyre. It transmits interesting information from the tyre-road contact and can be used to predict the maximal tyre grip and safety margin. The maximal grip coefficient is estimated according to a knowledge base, extracted from computer simulation of a high detailed three-dimensional model, using Adams® software. The proposed methodology is validated and applied to real driving conditions, in which maximal grip and safety margin are properly estimated.

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%).

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.

Research related to roads in USDA experimental forests [Chapter 16

Treesearch

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

2014-01-01

Forest roads are essential in experimental forests and rangelands (EFRs) to allow researchers and the public access to research sites and for fire suppression, timber extraction, and fuel management. Sediment from roads can adversely impact watershed health. Since the 1930s, the design and management of forest roads has addressed both access issues and watershed health...

Autonomous navigation method for substation inspection robot based on travelling deviation

NASA Astrophysics Data System (ADS)

Yang, Guoqing; Xu, Wei; Li, Jian; Fu, Chongguang; Zhou, Hao; Zhang, Chuanyou; Shao, Guangting

2017-06-01

A new method of edge detection is proposed in substation environment, which can realize the autonomous navigation of the substation inspection robot. First of all, the road image and information are obtained by using an image acquisition device. Secondly, the noise in the region of interest which is selected in the road image, is removed with the digital image processing algorithm, the road edge is extracted by Canny operator, and the road boundaries are extracted by Hough transform. Finally, the distance between the robot and the left and the right boundaries is calculated, and the travelling distance is obtained. The robot's walking route is controlled according to the travel deviation and the preset threshold. Experimental results show that the proposed method can detect the road area in real time, and the algorithm has high accuracy and stable performance.

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.

Extraction of basic roadway information for non-state roads in Florida.

DOT National Transportation Integrated Search

2015-06-01

The Florida Department of Transportation (FDOT) has continued to maintain a linear-referenced All-Roads map : that includes both state and non-state local roads. The state portion of the map could be populated with select data : from FDOTs R...

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.

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.

The research of road and vehicle information extraction algorithm based on high resolution remote sensing image

NASA Astrophysics Data System (ADS)

Zhou, Tingting; Gu, Lingjia; Ren, Ruizhi; Cao, Qiong

2016-09-01

With the rapid development of remote sensing technology, the spatial resolution and temporal resolution of satellite imagery also have a huge increase. Meanwhile, High-spatial-resolution images are becoming increasingly popular for commercial applications. The remote sensing image technology has broad application prospects in intelligent traffic. Compared with traditional traffic information collection methods, vehicle information extraction using high-resolution remote sensing image has the advantages of high resolution and wide coverage. This has great guiding significance to urban planning, transportation management, travel route choice and so on. Firstly, this paper preprocessed the acquired high-resolution multi-spectral and panchromatic remote sensing images. After that, on the one hand, in order to get the optimal thresholding for image segmentation, histogram equalization and linear enhancement technologies were applied into the preprocessing results. On the other hand, considering distribution characteristics of road, the normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used to suppress water and vegetation information of preprocessing results. Then, the above two processing result were combined. Finally, the geometric characteristics were used to completed road information extraction. The road vector extracted was used to limit the target vehicle area. Target vehicle extraction was divided into bright vehicles extraction and dark vehicles extraction. Eventually, the extraction results of the two kinds of vehicles were combined to get the final results. The experiment results demonstrated that the proposed algorithm has a high precision for the vehicle information extraction for different high resolution remote sensing images. Among these results, the average fault detection rate was about 5.36%, the average residual rate was about 13.60% and the average accuracy was approximately 91.26%.

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.

Extraction of basic roadway information for non-state roads in Florida : [summary].

DOT National Transportation Integrated Search

2015-07-01

The Florida Department of Transportation (FDOT) maintains a map of all the roads in Florida, : containing over one and a half million road links. For planning purposes, a wide variety : of information, such as stop lights, signage, lane number, and s...

Road dust and its effect on human health: a literature review

PubMed Central

2018-01-01

The purpose of this study was to determine the effects of road dust on human health. A PubMed search was used to extract references that included the words “road dust” and “health” or “fugitive dust” and “health” in the title or abstract. A total of 46 references were extracted and selected for review after the primary screening of 949 articles. The respiratory system was found to be the most affected system in the human body. Lead, platinum-group elements (platinum, rhodium, and bohrium), aluminum, zinc, vanadium, and polycyclic aromatic hydrocarbons were the components of road dust that were most frequently referenced in the articles reviewed. Road dust was found to have harmful effects on the human body, especially on the respiratory system. To determine the complex mechanism of action of various components of road dust on the human body and the results thereof, the authors recommend a further meta-analysis and extensive risk-assessment research into the health impacts of dust exposure. PMID:29642653

Distributed Scene Analysis For Autonomous Road Vehicle Guidance

NASA Astrophysics Data System (ADS)

Mysliwetz, Birger D.; Dickmanns, E. D.

1987-01-01

An efficient distributed processing scheme has been developed for visual road boundary tracking by 'VaMoRs', a testbed vehicle for autonomous mobility and computer vision. Ongoing work described here is directed to improving the robustness of the road boundary detection process in the presence of shadows, ill-defined edges and other disturbing real world effects. The system structure and the techniques applied for real-time scene analysis are presented along with experimental results. All subfunctions of road boundary detection for vehicle guidance, such as edge extraction, feature aggregation and camera pointing control, are executed in parallel by an onboard multiprocessor system. On the image processing level local oriented edge extraction is performed in multiple 'windows', tighly controlled from a hierarchically higher, modelbased level. The interpretation process involving a geometric road model and the observer's relative position to the road boundaries is capable of coping with ambiguity in measurement data. By using only selected measurements to update the model parameters even high noise levels can be dealt with and misleading edges be rejected.

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).

Multi-target Detection, Tracking, and Data Association on Road Networks Using Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Barkley, Brett E.

A cooperative detection and tracking algorithm for multiple targets constrained to a road network is presented for fixed-wing Unmanned Air Vehicles (UAVs) with a finite field of view. Road networks of interest are formed into graphs with nodes that indicate the target likelihood ratio (before detection) and position probability (after detection). A Bayesian likelihood ratio tracker recursively assimilates target observations until the cumulative observations at a particular location pass a detection criterion. At this point, a target is considered detected and a position probability is generated for the target on the graph. Data association is subsequently used to route future measurements to update the likelihood ratio tracker (for undetected target) or to update a position probability (a previously detected target). Three strategies for motion planning of UAVs are proposed to balance searching for new targets with tracking known targets for a variety of scenarios. Performance was tested in Monte Carlo simulations for a variety of mission parameters, including tracking on road networks with varying complexity and using UAVs at various altitudes.

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.

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...

Highway 3D model from image and lidar data

NASA Astrophysics Data System (ADS)

Chen, Jinfeng; Chu, Henry; Sun, Xiaoduan

2014-05-01

We present a new method of highway 3-D model construction developed based on feature extraction in highway images and LIDAR data. We describe the processing road coordinate data that connect the image frames to the coordinates of the elevation data. Image processing methods are used to extract sky, road, and ground regions as well as significant objects (such as signs and building fronts) in the roadside for the 3D model. LIDAR data are interpolated and processed to extract the road lanes as well as other features such as trees, ditches, and elevated objects to form the 3D model. 3D geometry reasoning is used to match the image features to the 3D model. Results from successive frames are integrated to improve the final model.

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.

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,...

Single-channel EEG-based mental fatigue detection based on deep belief network.

PubMed

Pinyi Li; Wenhui Jiang; Fei Su

2016-08-01

Mental fatigue has a pernicious influence on road and work place safety as well as a negative symptom of many acute and chronic illnesses, since the ability of concentrating, responding and judging quickly decreases during the fatigue or drowsiness stage. Electroencephalography (EEG) has been proven to be a robust physiological indicator of human cognitive state over the last few decades. But most existing EEG-based fatigue detection methods have poor performance in accuracy. This paper proposed a single-channel EEG-based mental fatigue detection method based on Deep Belief Network (DBN). The fused nonliear features from specified sub-bands and dynamic analysis, a total of 21 features are extracted as the input of the DBN to discriminate three classes of mental state including alert, slight fatigue and severe fatigue. Experimental results show the good performance of the proposed model comparing with those state-of-art methods.

Traffic intensity monitoring using multiple object detection with traffic surveillance cameras

NASA Astrophysics Data System (ADS)

Hamdan, H. G. Muhammad; Khalifah, O. O.

2017-11-01

Object detection and tracking is a field of research that has many applications in the current generation with increasing number of cameras on the streets and lower cost for Internet of Things(IoT). In this paper, a traffic intensity monitoring system is implemented based on the Macroscopic Urban Traffic model is proposed using computer vision as its source. The input of this program is extracted from a traffic surveillance camera which has another program running a neural network classification which can identify and differentiate the vehicle type is implanted. The neural network toolbox is trained with positive and negative input to increase accuracy. The accuracy of the program is compared to other related works done and the trends of the traffic intensity from a road is also calculated. relevant articles in literature searches, great care should be taken in constructing both. Lastly the limitation and the future work is concluded.

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

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

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.

78 FR 50051 - Notice of Availability of the Final Environmental Impact Statement for the Tarmac King Road...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-16

... DEPARTMENT OF DEFENSE Department of the Army, Corps of Engineers Notice of Availability of the Final Environmental Impact Statement for the Tarmac King Road Limestone Mine Proposed in Levy County... from limestone extraction, material stockpiling, roads, and other infrastructure over a period of...

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.

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.

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.

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

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.

Analysis and simulation of wireless signal propagation applying geostatistical interpolation techniques

NASA Astrophysics Data System (ADS)

Kolyaie, S.; Yaghooti, M.; Majidi, G.

2011-12-01

This paper is a part of an ongoing research to examine the capability of geostatistical analysis for mobile networks coverage prediction, simulation and tuning. Mobile network coverage predictions are used to find network coverage gaps and areas with poor serviceability. They are essential data for engineering and management in order to make better decision regarding rollout, planning and optimisation of mobile networks.The objective of this research is to evaluate different interpolation techniques in coverage prediction. In method presented here, raw data collected from drive testing a sample of roads in study area is analysed and various continuous surfaces are created using different interpolation methods. Two general interpolation methods are used in this paper with different variables; first, Inverse Distance Weighting (IDW) with various powers and number of neighbours and second, ordinary kriging with Gaussian, spherical, circular and exponential semivariogram models with different number of neighbours. For the result comparison, we have used check points coming from the same drive test data. Prediction values for check points are extracted from each surface and the differences with actual value are computed. The output of this research helps finding an optimised and accurate model for coverage prediction.

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.

Extracting decision rules from police accident reports through decision trees.

PubMed

de Oña, Juan; López, Griselda; Abellán, Joaquín

2013-01-01

Given the current number of road accidents, the aim of many road safety analysts is to identify the main factors that contribute to crash severity. To pinpoint those factors, this paper shows an application that applies some of the methods most commonly used to build decision trees (DTs), which have not been applied to the road safety field before. An analysis of accidents on rural highways in the province of Granada (Spain) between 2003 and 2009 (both inclusive) showed that the methods used to build DTs serve our purpose and may even be complementary. Applying these methods has enabled potentially useful decision rules to be extracted that could be used by road safety analysts. For instance, some of the rules may indicate that women, contrary to men, increase their risk of severity under bad lighting conditions. The rules could be used in road safety campaigns to mitigate specific problems. This would enable managers to implement priority actions based on a classification of accidents by types (depending on their severity). However, the primary importance of this proposal is that other databases not used here (i.e. other infrastructure, roads and countries) could be used to identify unconventional problems in a manner easy for road safety managers to understand, as decision rules. Copyright © 2012 Elsevier Ltd. All rights reserved.

On-road anomaly detection by multimodal sensor analysis and multimedia processing

NASA Astrophysics Data System (ADS)

Orhan, Fatih; Eren, P. E.

2014-03-01

The use of smartphones in Intelligent Transportation Systems is gaining popularity, yet many challenges exist in developing functional applications. Due to the dynamic nature of transportation, vehicular social applications face complexities such as developing robust sensor management, performing signal and image processing tasks, and sharing information among users. This study utilizes a multimodal sensor analysis framework which enables the analysis of sensors in multimodal aspect. It also provides plugin-based analyzing interfaces to develop sensor and image processing based applications, and connects its users via a centralized application as well as to social networks to facilitate communication and socialization. With the usage of this framework, an on-road anomaly detector is being developed and tested. The detector utilizes the sensors of a mobile device and is able to identify anomalies such as hard brake, pothole crossing, and speed bump crossing. Upon such detection, the video portion containing the anomaly is automatically extracted in order to enable further image processing analysis. The detection results are shared on a central portal application for online traffic condition monitoring.

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.

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.

Fugitive dust from vehicles traveling on unpaved roads

Treesearch

Thomas A. Cuscino; Robert Jennings Heinsohn; Clotworthy, Jr. Birnie

1977-01-01

A model has been developed for estimating concentrations of fugitive dust downwind of an unpaved road within a factor of 2 for most cases. The model allows for winds oblique to the road and also for extraction of fugitive dust from the plume as it diffuses to the ground. Experiments were performed to determine the accuracy of the model in estimating downwind...

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.

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.

Fuzzylot: a novel self-organising fuzzy-neural rule-based pilot system for automated vehicles.

PubMed

Pasquier, M; Quek, C; Toh, M

2001-10-01

This paper presents part of our research work concerned with the realisation of an Intelligent Vehicle and the technologies required for its routing, navigation, and control. An automated driver prototype has been developed using a self-organising fuzzy rule-based system (POPFNN-CRI(S)) to model and subsequently emulate human driving expertise. The ability of fuzzy logic to represent vague information using linguistic variables makes it a powerful tool to develop rule-based control systems when an exact working model is not available, as is the case of any vehicle-driving task. Designing a fuzzy system, however, is a complex endeavour, due to the need to define the variables and their associated fuzzy sets, and determine a suitable rule base. Many efforts have thus been devoted to automating this process, yielding the development of learning and optimisation techniques. One of them is the family of POP-FNNs, or Pseudo-Outer Product Fuzzy Neural Networks (TVR, AARS(S), AARS(NS), CRI, Yager). These generic self-organising neural networks developed at the Intelligent Systems Laboratory (ISL/NTU) are based on formal fuzzy mathematical theory and are able to objectively extract a fuzzy rule base from training data. In this application, a driving simulator has been developed, that integrates a detailed model of the car dynamics, complete with engine characteristics and environmental parameters, and an OpenGL-based 3D-simulation interface coupled with driving wheel and accelerator/ brake pedals. The simulator has been used on various road scenarios to record from a human pilot driving data consisting of steering and speed control actions associated to road features. Specifically, the POPFNN-CRI(S) system is used to cluster the data and extract a fuzzy rule base modelling the human driving behaviour. Finally, the effectiveness of the generated rule base has been validated using the simulator in autopilot mode.

A machine learning pipeline for automated registration and classification of 3D lidar data

NASA Astrophysics Data System (ADS)

Rajagopal, Abhejit; Chellappan, Karthik; Chandrasekaran, Shivkumar; Brown, Andrew P.

2017-05-01

Despite the large availability of geospatial data, registration and exploitation of these datasets remains a persis- tent challenge in geoinformatics. Popular signal processing and machine learning algorithms, such as non-linear SVMs and neural networks, rely on well-formatted input models as well as reliable output labels, which are not always immediately available. In this paper we outline a pipeline for gathering, registering, and classifying initially unlabeled wide-area geospatial data. As an illustrative example, we demonstrate the training and test- ing of a convolutional neural network to recognize 3D models in the OGRIP 2007 LiDAR dataset using fuzzy labels derived from OpenStreetMap as well as other datasets available on OpenTopography.org. When auxiliary label information is required, various text and natural language processing filters are used to extract and cluster keywords useful for identifying potential target classes. A subset of these keywords are subsequently used to form multi-class labels, with no assumption of independence. Finally, we employ class-dependent geometry extraction routines to identify candidates from both training and testing datasets. Our regression networks are able to identify the presence of 6 structural classes, including roads, walls, and buildings, in volumes as big as 8000 m3 in as little as 1.2 seconds on a commodity 4-core Intel CPU. The presented framework is neither dataset nor sensor-modality limited due to the registration process, and is capable of multi-sensor data-fusion.

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

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.

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.

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.

Landmark-aided localization for air vehicles using learned object detectors

NASA Astrophysics Data System (ADS)

DeAngelo, Mark Patrick

This research presents two methods to localize an aircraft without GPS using fixed landmarks observed from an optical sensor. Onboard absolute localization is useful for vehicle navigation free from an external network. The objective is to achieve practical navigation performance using available autopilot hardware and a downward pointing camera. The first method uses computer vision cascade object detectors, which are trained to detect predetermined, distinct landmarks prior to a flight. The first method also concurrently explores aircraft localization using roads between landmark updates. During a flight, the aircraft navigates with attitude, heading, airspeed, and altitude measurements and obtains measurement updates when landmarks are detected. The sensor measurements and landmark coordinates extracted from the aircraft's camera images are combined into an unscented Kalman filter to obtain an estimate of the aircraft's position and wind velocities. The second method uses computer vision object detectors to detect abundant generic landmarks referred as buildings, fields, trees, and road intersections from aerial perspectives. Various landmark attributes and spatial relationships to other landmarks are used to help associate observed landmarks with reference landmarks. The computer vision algorithms automatically extract reference landmarks from maps, which are processed offline before a flight. During a flight, the aircraft navigates with attitude, heading, airspeed, and altitude measurements and obtains measurement corrections by processing aerial photos with similar generic landmark detection techniques. The method also combines sensor measurements and landmark coordinates into an unscented Kalman filter to obtain an estimate of the aircraft's position and wind velocities.

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.

Albemarle County road orders, 1783-1816.

DOT National Transportation Integrated Search

1975-01-01

During the early stages of the pilot study of Albemarle County it was necessary to examine and extract all the road orders for the counties from which Albemarle was formed, as well as the orders for Albemarle when it still contained the counties of A...

Markov random fields and graphs for uncertainty management and symbolic data fusion in an urban scene interpretation

NASA Astrophysics Data System (ADS)

Moissinac, Henri; Maitre, Henri; Bloch, Isabelle

1995-11-01

An image interpretation method is presented for the automatic processing of aerial pictures of a urban landscape. In order to improve the picture analysis, some a priori knowledge extracted from a geographic map is introduced. A coherent graph-based model of the city is built, starting with the road network. A global uncertainty management scheme has been designed in order to evaluate the final confidence we can have in the final results. This model and the uncertainty management tend to reflect the hierarchy of the available data and the interpretation levels. The symbolic relationships linking the different kinds of elements are taken into account while propagating and combining the confidence measures along the interpretation process.

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.

Road boundary detection

NASA Technical Reports Server (NTRS)

Sowers, J.; Mehrotra, R.; Sethi, I. K.

1989-01-01

A method for extracting road boundaries using the monochrome image of a visual road scene is presented. The statistical information regarding the intensity levels present in the image along with some geometrical constraints concerning the road are the basics of this approach. Results and advantages of this technique compared to others are discussed. The major advantages of this technique, when compared to others, are its ability to process the image in only one pass, to limit the area searched in the image using only knowledge concerning the road geometry and previous boundary information, and dynamically adjust for inconsistencies in the located boundary information, all of which helps to increase the efficacy of this technique.

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

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.

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...

18 CFR 415.33 - Uses by special permit.

Code of Federal Regulations, 2014 CFR

2014-04-01

... transient enterprises. (3) Drive-in theaters, signs and billboards. (4) Extraction of sand, gravel and other...) Utilities, railroad tracks, streets and bridges. Public utility facilities, roads, railroad tracks and... of protection may be provided for minor or auxiliary roads, railroads or utilities. (5) Water supply...

18 CFR 415.33 - Uses by special permit.

Code of Federal Regulations, 2011 CFR

2011-04-01

... transient enterprises. (3) Drive-in theaters, signs and billboards. (4) Extraction of sand, gravel and other...) Utilities, railroad tracks, streets and bridges. Public utility facilities, roads, railroad tracks and... of protection may be provided for minor or auxiliary roads, railroads or utilities. (5) Water supply...

18 CFR 415.33 - Uses by special permit.

Code of Federal Regulations, 2012 CFR

2012-04-01

... transient enterprises. (3) Drive-in theaters, signs and billboards. (4) Extraction of sand, gravel and other...) Utilities, railroad tracks, streets and bridges. Public utility facilities, roads, railroad tracks and... of protection may be provided for minor or auxiliary roads, railroads or utilities. (5) Water supply...

18 CFR 415.33 - Uses by special permit.

Code of Federal Regulations, 2010 CFR

2010-04-01

... transient enterprises. (3) Drive-in theaters, signs and billboards. (4) Extraction of sand, gravel and other...) Utilities, railroad tracks, streets and bridges. Public utility facilities, roads, railroad tracks and... of protection may be provided for minor or auxiliary roads, railroads or utilities. (5) Water supply...

18 CFR 415.33 - Uses by special permit.

Code of Federal Regulations, 2013 CFR

2013-04-01

... transient enterprises. (3) Drive-in theaters, signs and billboards. (4) Extraction of sand, gravel and other...) Utilities, railroad tracks, streets and bridges. Public utility facilities, roads, railroad tracks and... of protection may be provided for minor or auxiliary roads, railroads or utilities. (5) Water supply...

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.

Manhole Cover Detection Using Vehicle-Based Multi-Sensor Data

NASA Astrophysics Data System (ADS)

Ji, S.; Shi, Y.; Shi, Z.

2012-07-01

A new method combined wit multi-view matching and feature extraction technique is developed to detect manhole covers on the streets using close-range images combined with GPS/IMU and LINDAR data. The covers are an important target on the road traffic as same as transport signs, traffic lights and zebra crossing but with more unified shapes. However, the different shoot angle and distance, ground material, complex street scene especially its shadow, and cars in the road have a great impact on the cover detection rate. The paper introduces a new method in edge detection and feature extraction in order to overcome these difficulties and greatly improve the detection rate. The LIDAR data are used to do scene segmentation and the street scene and cars are excluded from the roads. And edge detection method base on canny which sensitive to arcs and ellipses is applied on the segmented road scene and the interesting areas contain arcs are extracted and fitted to ellipse. The ellipse are then resampled for invariance to shooting angle and distance and then are matched to adjacent images for further checking if covers and . More than 1000 images with different scenes are used in our tests and the detection rate is analyzed. The results verified our method have its advantages in correct covers detection in the complex street scene.

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...

Capacity-constrained traffic assignment in networks with residual queues

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

Lam, W.H.K.; Zhang, Y.

2000-04-01

This paper proposes a capacity-constrained traffic assignment model for strategic transport planning in which the steady-state user equilibrium principle is extended for road networks with residual queues. Therefore, the road-exit capacity and the queuing effects can be incorporated into the strategic transport model for traffic forecasting. The proposed model is applicable to the congested network particularly when the traffic demands exceeds the capacity of the network during the peak period. An efficient solution method is proposed for solving the steady-state traffic assignment problem with residual queues. Then a simple numerical example is employed to demonstrate the application of the proposedmore » model and solution method, while an example of a medium-sized arterial highway network in Sioux Falls, South Dakota, is used to test the applicability of the proposed solution to real problems.« less

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.

Computing multiple aggregation levels and contextual features for road facilities recognition using mobile laser scanning data

NASA Astrophysics Data System (ADS)

Yang, Bisheng; Dong, Zhen; Liu, Yuan; Liang, Fuxun; Wang, Yongjun

2017-04-01

In recent years, updating the inventory of road infrastructures based on field work is labor intensive, time consuming, and costly. Fortunately, vehicle-based mobile laser scanning (MLS) systems provide an efficient solution to rapidly capture three-dimensional (3D) point clouds of road environments with high flexibility and precision. However, robust recognition of road facilities from huge volumes of 3D point clouds is still a challenging issue because of complicated and incomplete structures, occlusions and varied point densities. Most existing methods utilize point or object based features to recognize object candidates, and can only extract limited types of objects with a relatively low recognition rate, especially for incomplete and small objects. To overcome these drawbacks, this paper proposes a semantic labeling framework by combing multiple aggregation levels (point-segment-object) of features and contextual features to recognize road facilities, such as road surfaces, road boundaries, buildings, guardrails, street lamps, traffic signs, roadside-trees, power lines, and cars, for highway infrastructure inventory. The proposed method first identifies ground and non-ground points, and extracts road surfaces facilities from ground points. Non-ground points are segmented into individual candidate objects based on the proposed multi-rule region growing method. Then, the multiple aggregation levels of features and the contextual features (relative positions, relative directions, and spatial patterns) associated with each candidate object are calculated and fed into a SVM classifier to label the corresponding candidate object. The recognition performance of combining multiple aggregation levels and contextual features was compared with single level (point, segment, or object) based features using large-scale highway scene point clouds. Comparative studies demonstrated that the proposed semantic labeling framework significantly improves road facilities recognition precision (90.6%) and recall (91.2%), particularly for incomplete and small objects.

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...

Semantic Labelling of Road Furniture in Mobile Laser Scanning Data

NASA Astrophysics Data System (ADS)

Li, F.; Oude Elberink, S.; Vosselman, G.

2017-09-01

Road furniture semantic labelling is vital for large scale mapping and autonomous driving systems. Much research has been investigated on road furniture interpretation in both 2D images and 3D point clouds. Precise interpretation of road furniture in mobile laser scanning data still remains unexplored. In this paper, a novel method is proposed to interpret road furniture based on their logical relations and functionalities. Our work represents the most detailed interpretation of road furniture in mobile laser scanning data. 93.3 % of poles are correctly extracted and all of them are correctly recognised. 94.3 % of street light heads are detected and 76.9 % of them are correctly identified. Despite errors arising from the recognition of other components, our framework provides a promising solution to automatically map road furniture at a detailed level in urban environments.

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

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.

Accuracy assessment of airborne LIDAR data and automated extraction of features

NASA Astrophysics Data System (ADS)

Cetin, Ali Fuat

Airborne LIDAR technology is becoming more widely used since it provides fast and dense irregularly spaced 3D point clouds. The coordinates produced as a result of calibration of the system are used for surface modeling and information extraction. In this research a new idea of LIDAR detectable targets is introduced. In the second part of this research, a new technique to delineate the edge of road pavements automatically using only LIDAR is presented. The accuracy of LIDAR data should be determined before exploitation for any information extraction to support a Geographic Information System (GIS) database. Until recently there was no definitive research to provide a methodology for common and practical assessment of both horizontal and vertical accuracy of LIDAR data for end users. The idea used in this research was to use targets of such a size and design so that the position of each target can be determined using the Least Squares Image Matching Technique. The technique used in this research can provide end users and data providers an easy way to evaluate the quality of the product, especially when there are accessible hard surfaces to install the targets. The results of the technique are determined to be in a reasonable range when the point spacing of the data is sufficient. To delineate the edge of pavements, trees and buildings are removed from the point cloud, and the road surfaces are segmented from the remaining terrain data. This is accomplished using the homogeneous nature of road surfaces in intensity and height. There are not many studies to delineate the edge of road pavement after the road surfaces are extracted. In this research, template matching techniques are used with criteria computed by Gray Level Co-occurrence Matrix (GLCM) properties, in order to locate seed pixels in the image. The seed pixels are then used for placement of the matched templates along the road. The accuracy of the delineated edge of pavement is determined by comparing the coordinates of reference points collected via photogrammetry with the coordinates of the nearest points along the delineated edge.

Comparing emission rates derived from a model with a plume-based approach and quantifying the contribution of vehicle classes to on-road emissions and air quality.

PubMed

Xu, Junshi; Wang, Jonathan; Hilker, Nathan; Fallah-Shorshani, Masoud; Saleh, Marc; Tu, Ran; Wang, An; Minet, Laura; Stogios, Christos; Evans, Greg; Hatzopoulou, Marianne

2018-06-05

This study presents a comparison of fleet averaged emission factors (EFs) derived from a traffic emission model with EFs estimated using plume-based measurements, including an investigation of the contribution of vehicle classes to carbon monoxide (CO), nitrogen oxides (NO x ), and elemental carbon (EC) along an urban corridor. To this end, a field campaign was conducted over one week in June 2016 on an arterial road in Toronto, Canada. Traffic data were collected using a traffic camera and a radar, while air quality was characterized using two monitoring stations: one located at ground-level and another at the rooftop of a four-storey building. A traffic simulation model was calibrated and validated and sec-by-sec speed profiles for all vehicle trajectories were extracted to model emissions. In addition, dispersion modelling was conducted to identify the extent to which differences in emissions translate to differences in near-road concentrations. Our results indicate that modelled EFs for CO and NO x are twice as high as plume-based EFs. Besides, modelled results indicate that transit bus emissions accounted for 60% and 70% of the total emissions of NO x and EC. Transit bus emission rates in g/passenger.km for NO x and EC were up to 8 and 22 times the emission rates of passenger cars. In contrast, the Toronto streetcars, which are electrically fuelled, were found to improve near-road air quality despite their negative impact on traffic speeds. Finally, we observe that the difference in estimated concentrations derived from the two methods is not as large as the difference in estimated emissions due to the influence of meteorology and of the urban background given that the study network is located in a busy downtown area. Implications This study presents a comparison of fleet averaged emission factors (EFs) derived from a traffic emission model with EFs estimated using plume-based measurements, including an investigation of the contribution of vehicle classes to various pollutants. Besides, dispersion modelling was conducted to identify the extent to which differences in emissions translate to differences in near-road concentrations. We observe that the difference in estimated concentrations derived from the two methods is not as large as the difference in estimated emissions due to the influence of meteorology and of the urban background as the study network is located in a busy downtown area.

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.

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.

Comparative Evaluation of Pavement Crack Detection Using Kernel-Based Techniques in Asphalt Road Surfaces

NASA Astrophysics Data System (ADS)

Miraliakbari, A.; Sok, S.; Ouma, Y. O.; Hahn, M.

2016-06-01

With the increasing demand for the digital survey and acquisition of road pavement conditions, there is also the parallel growing need for the development of automated techniques for the analysis and evaluation of the actual road conditions. This is due in part to the resulting large volumes of road pavement data captured through digital surveys, and also to the requirements for rapid data processing and evaluations. In this study, the Canon 5D Mark II RGB camera with a resolution of 21 megapixels is used for the road pavement condition mapping. Even though many imaging and mapping sensors are available, the development of automated pavement distress detection, recognition and extraction systems for pavement condition is still a challenge. In order to detect and extract pavement cracks, a comparative evaluation of kernel-based segmentation methods comprising line filtering (LF), local binary pattern (LBP) and high-pass filtering (HPF) is carried out. While the LF and LBP methods are based on the principle of rotation-invariance for pattern matching, the HPF applies the same principle for filtering, but with a rotational invariant matrix. With respect to the processing speeds, HPF is fastest due to the fact that it is based on a single kernel, as compared to LF and LBP which are based on several kernels. Experiments with 20 sample images which contain linear, block and alligator cracks are carried out. On an average a completeness of distress extraction with values of 81.2%, 76.2% and 81.1% have been found for LF, HPF and LBP respectively.

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...

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.

Exact extraction method for road rutting laser lines

NASA Astrophysics Data System (ADS)

Hong, Zhiming

2018-02-01

This paper analyzes the importance of asphalt pavement rutting detection in pavement maintenance and pavement administration in today's society, the shortcomings of the existing rutting detection methods are presented and a new rutting line-laser extraction method based on peak intensity characteristic and peak continuity is proposed. The intensity of peak characteristic is enhanced by a designed transverse mean filter, and an intensity map of peak characteristic based on peak intensity calculation for the whole road image is obtained to determine the seed point of the rutting laser line. Regarding the seed point as the starting point, the light-points of a rutting line-laser are extracted based on the features of peak continuity, which providing exact basic data for subsequent calculation of pavement rutting depths.

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).

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.

Automatic 3D Extraction of Buildings, Vegetation and Roads from LIDAR Data

NASA Astrophysics Data System (ADS)

Bellakaout, A.; Cherkaoui, M.; Ettarid, M.; Touzani, A.

2016-06-01

Aerial topographic surveys using Light Detection and Ranging (LiDAR) technology collect dense and accurate information from the surface or terrain; it is becoming one of the important tools in the geosciences for studying objects and earth surface. Classification of Lidar data for extracting ground, vegetation, and buildings is a very important step needed in numerous applications such as 3D city modelling, extraction of different derived data for geographical information systems (GIS), mapping, navigation, etc... Regardless of what the scan data will be used for, an automatic process is greatly required to handle the large amount of data collected because the manual process is time consuming and very expensive. This paper is presenting an approach for automatic classification of aerial Lidar data into five groups of items: buildings, trees, roads, linear object and soil using single return Lidar and processing the point cloud without generating DEM. Topological relationship and height variation analysis is adopted to segment, preliminary, the entire point cloud preliminarily into upper and lower contours, uniform and non-uniform surface, non-uniform surfaces, linear objects, and others. This primary classification is used on the one hand to know the upper and lower part of each building in an urban scene, needed to model buildings façades; and on the other hand to extract point cloud of uniform surfaces which contain roofs, roads and ground used in the second phase of classification. A second algorithm is developed to segment the uniform surface into buildings roofs, roads and ground, the second phase of classification based on the topological relationship and height variation analysis, The proposed approach has been tested using two areas : the first is a housing complex and the second is a primary school. The proposed approach led to successful classification results of buildings, vegetation and road classes.

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

Using expansive grasses for monitoring heavy metal pollution in the vicinity of roads.

PubMed

Vachová, Pavla; Vach, Marek; Najnarová, Eva

2017-10-01

We propose a method for monitoring heavy metal deposition in the vicinity of roads using the leaf surfaces of two expansive grass species which are greatly abundant. A principle of the proposed procedure is to minimize the number of operations in collecting and preparing samples for analysis. The monitored elements are extracted from the leaf surfaces using dilute nitric acid directly in the sample-collection bottle. The ensuing steps, then, are only to filter the extraction solution and the elemental analysis itself. The verification results indicate that the selected grasses Calamagrostis epigejos and Arrhenatherum elatius are well suited to the proposed procedure. Selected heavy metals (Zn, Cu, Pb, Ni, Cr, and Cd) in concentrations appropriate for direct determination using methods of elemental analysis can be extracted from the surface of leaves of these species collected in the vicinity of roads with medium traffic loads. Comparing the two species showed that each had a different relationship between the amounts of deposited heavy metals and distance from the road. This disparity can be explained by specific morphological properties of the two species' leaf surfaces. Due to the abundant occurrence of the two species and the method's general simplicity and ready availability, we regard the proposed approach to constitute a broadly usable and repeatable one for producing reproducible results. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

NGEE Arctic Plant Traits: Soil Nutrient Availability, Kougarok Road Mile Marker 64, Seward Peninsula, Alaska, beginning 2016

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

Verity Salmon; Colleen Iversen; Amy Breen

Soil nutrient availability at all vegetation plots was measured using anion and cation binding resins deployed to vegetation plots at the Kougarok hillslope site located at Kougarok Road Marker 64. Concentrations of ammonia, nitrate, and phosphate in resin extract solutions were determined in the lab.

Experience of the ARGO autonomous vehicle

NASA Astrophysics Data System (ADS)

Bertozzi, Massimo; Broggi, Alberto; Conte, Gianni; Fascioli, Alessandra

1998-07-01

This paper presents and discusses the first results obtained by the GOLD (Generic Obstacle and Lane Detection) system as an automatic driver of ARGO. ARGO is a Lancia Thema passenger car equipped with a vision-based system that allows to extract road and environmental information from the acquired scene. By means of stereo vision, obstacles on the road are detected and localized, while the processing of a single monocular image allows to extract the road geometry in front of the vehicle. The generality of the underlying approach allows to detect generic obstacles (without constraints on shape, color, or symmetry) and to detect lane markings even in dark and in strong shadow conditions. The hardware system consists of a PC Pentium 200 Mhz with MMX technology and a frame-grabber board able to acquire 3 b/w images simultaneously; the result of the processing (position of obstacles and geometry of the road) is used to drive an actuator on the steering wheel, while debug information are presented to the user on an on-board monitor and a led-based control panel.

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.

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

38. DETAIL OF RUINS OF CYANIDE MIXING AND EXTRACTION SHED, ...

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

38. DETAIL OF RUINS OF CYANIDE MIXING AND EXTRACTION SHED, LOOKING SOUTHEAST. CYANIDE SOLUTION WAS PREPARED HERE AND PUMPED UP INTO THE PROCESSING TANKS, AND THE PREGNANT SOLUTION WAS ALSO EXTRACTED HERE AFTER THE LEACHING PROCESS WAS COMPLETE - Skidoo Mine, Park Route 38 (Skidoo Road), Death Valley Junction, Inyo County, CA

Statistical classification of road pavements using near field vehicle rolling noise measurements.

PubMed

Paulo, Joel Preto; Coelho, J L Bento; Figueiredo, Mário A T

2010-10-01

Low noise surfaces have been increasingly considered as a viable and cost-effective alternative to acoustical barriers. However, road planners and administrators frequently lack information on the correlation between the type of road surface and the resulting noise emission profile. To address this problem, a method to identify and classify different types of road pavements was developed, whereby near field road noise is analyzed using statistical learning methods. The vehicle rolling sound signal near the tires and close to the road surface was acquired by two microphones in a special arrangement which implements the Close-Proximity method. A set of features, characterizing the properties of the road pavement, was extracted from the corresponding sound profiles. A feature selection method was used to automatically select those that are most relevant in predicting the type of pavement, while reducing the computational cost. A set of different types of road pavement segments were tested and the performance of the classifier was evaluated. Results of pavement classification performed during a road journey are presented on a map, together with geographical data. This procedure leads to a considerable improvement in the quality of road pavement noise data, thereby increasing the accuracy of road traffic noise prediction models.

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.

Monocular precrash vehicle detection: features and classifiers.

PubMed

Sun, Zehang; Bebis, George; Miller, Ronald

2006-07-01

Robust and reliable vehicle detection from images acquired by a moving vehicle (i.e., on-road vehicle detection) is an important problem with applications to driver assistance systems and autonomous, self-guided vehicles. The focus of this work is on the issues of feature extraction and classification for rear-view vehicle detection. Specifically, by treating the problem of vehicle detection as a two-class classification problem, we have investigated several different feature extraction methods such as principal component analysis, wavelets, and Gabor filters. To evaluate the extracted features, we have experimented with two popular classifiers, neural networks and support vector machines (SVMs). Based on our evaluation results, we have developed an on-board real-time monocular vehicle detection system that is capable of acquiring grey-scale images, using Ford's proprietary low-light camera, achieving an average detection rate of 10 Hz. Our vehicle detection algorithm consists of two main steps: a multiscale driven hypothesis generation step and an appearance-based hypothesis verification step. During the hypothesis generation step, image locations where vehicles might be present are extracted. This step uses multiscale techniques not only to speed up detection, but also to improve system robustness. The appearance-based hypothesis verification step verifies the hypotheses using Gabor features and SVMs. The system has been tested in Ford's concept vehicle under different traffic conditions (e.g., structured highway, complex urban streets, and varying weather conditions), illustrating good performance.

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

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

A study of the landslide potential along the mountain road using environmental indices

NASA Astrophysics Data System (ADS)

Lin, C. Y.

2014-12-01

Utilization of slope land in recent years is rapid as a result of the dense population and limit of land resources in Taiwan. Therefore, mountain road plays an essential role for the necessity of human life. However, landslide disaster resulting in road failure occurred frequently in Taiwan on the slope land due to earthquake and typhoon. Previous studies found that the extreme rainfall coupled with the property of fragile geology could cause landslide. Nevertheless, the landslide occurrence might be affected by the drainage of the road side ditches. Taiwan Highway No.21 in Chi-Shan watershed and the forest roads located in Xiao-Lin Village, which failure during the hit of Typhoon Morakot in 2009, were selected for exploring the potential of vulnerable to landslides. Topographic Wetness Index (TWI) and Road Curvature (RC) were extracted along the road to indicate the potential sites which are vulnerable to slope failure. The surface runoff diverted by the road side ditches could spoil the sites with high RC due to the straight movement characteristics of the diverted runoff and cause the downslope collapse. The sites with higher mean value and lower standard deviation of Normalized Difference Vegetation Index (NDVI) derived from the SPOT imagery taken in dry and/or rainy seasons could be implied as the vegetation stands showing highly buffer effects in environmental stress due to having deeper soil layer, and are hardly interfered by the drought. The stands located in such sites once collapsed are often resulting in huge volumes of debris. Drainage Density (DD) index could be applied as the degrees of geologic fragile in the slope land. A road across the sites with higher mean value and lower standard deviation of NDVI and/or higher DD should be paid more attention because of having highly vulnerable to deep seated landslide. This study is focusing on extracting and analyzing the environmental indices such as TWI, RC, NDVI and DD for exploring the slope stability along the mountain road. The results could be used as the references of related authorities for understanding the potential landslides along a road.

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.

The Detection of Transport Land-Use Data Using Crowdsourcing Taxi Trajectory

NASA Astrophysics Data System (ADS)

Ai, T.; Yang, W.

2016-06-01

This study tries to explore the question of transport land-use change detection by large volume of vehicle trajectory data, presenting a method based on Deluanay triangulation. The whole method includes three steps. The first one is to pre-process the vehicle trajectory data including the point anomaly removing and the conversion of trajectory point to track line. Secondly, construct Deluanay triangulation within the vehicle trajectory line to detect neighborhood relation. Considering the case that some of the trajectory segments are too long, we use a interpolation measure to add more points for the improved triangulation. Thirdly, extract the transport road by cutting short triangle edge and organizing the polygon topology. We have conducted the experiment of transport land-use change discovery using the data of taxi track in Beijing City. We extract not only the transport land-use area but also the semantic information such as the transformation speed, the traffic jam distribution, the main vehicle movement direction and others. Compared with the existed transport network data, such as OpenStreet Map, our method is proved to be quick and accurate.

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...

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.

Automated analysis of long-term bridge behavior and health using a cyber-enabled wireless monitoring system

NASA Astrophysics Data System (ADS)

O'Connor, Sean M.; Zhang, Yilan; Lynch, Jerome; Ettouney, Mohammed; van der Linden, Gwen

2014-04-01

A worthy goal for the structural health monitoring field is the creation of a scalable monitoring system architecture that abstracts many of the system details (e.g., sensors, data) from the structure owner with the aim of providing "actionable" information that aids in their decision making process. While a broad array of sensor technologies have emerged, the ability for sensing systems to generate large amounts of data have far outpaced advances in data management and processing. To reverse this trend, this study explores the creation of a cyber-enabled wireless SHM system for highway bridges. The system is designed from the top down by considering the damage mechanisms of concern to bridge owners and then tailoring the sensing and decision support system around those concerns. The enabling element of the proposed system is a powerful data repository system termed SenStore. SenStore is designed to combine sensor data with bridge meta-data (e.g., geometric configuration, material properties, maintenance history, sensor locations, sensor types, inspection history). A wireless sensor network deployed to a bridge autonomously streams its measurement data to SenStore via a 3G cellular connection for storage. SenStore securely exposes the bridge meta- and sensor data to software clients that can process the data to extract information relevant to the decision making process of the bridge owner. To validate the proposed cyber-enable SHM system, the system is implemented on the Telegraph Road Bridge (Monroe, MI). The Telegraph Road Bridge is a traditional steel girder-concrete deck composite bridge located along a heavily travelled corridor in the Detroit metropolitan area. A permanent wireless sensor network has been installed to measure bridge accelerations, strains and temperatures. System identification and damage detection algorithms are created to automatically mine bridge response data stored in SenStore over an 18-month period. Tools like Gaussian Process (GP) regression are used to predict changes in the bridge behavior as a function of environmental parameters. Based on these analyses, pertinent behavioral information relevant to bridge management is autonomously extracted.

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.

Study on Stationarity of Random Load Spectrum Based on the Special Road

NASA Astrophysics Data System (ADS)

Yan, Huawen; Zhang, Weigong; Wang, Dong

2017-09-01

In the special road quality assessment method, there is a method using a wheel force sensor, the essence of this method is collecting the load spectrum of the car to reflect the quality of road. According to the definition of stochastic process, it is easy to find that the load spectrum is a stochastic process. However, the analysis method and application range of different random processes are very different, especially in engineering practice, which will directly affect the design and development of the experiment. Therefore, determining the type of a random process has important practical significance. Based on the analysis of the digital characteristics of road load spectrum, this paper determines that the road load spectrum in this experiment belongs to a stationary stochastic process, paving the way for the follow-up modeling and feature extraction of the special road.

Highway extraction from high resolution aerial photography using a geometric active contour model

NASA Astrophysics Data System (ADS)

Niu, Xutong

Highway extraction and vehicle detection are two of the most important steps in traffic-flow analysis from multi-frame aerial photographs. The traditional method of deriving traffic flow trajectories relies on manual vehicle counting from a sequence of aerial photographs, which is tedious and time-consuming. This research presents a new framework for semi-automatic highway extraction. The basis of the new framework is an improved geometric active contour (GAC) model. This novel model seeks to minimize an objective function that transforms a problem of propagation of regular curves into an optimization problem. The implementation of curve propagation is based on level set theory. By using an implicit representation of a two-dimensional curve, a level set approach can be used to deal with topological changes naturally, and the output is unaffected by different initial positions of the curve. However, the original GAC model, on which the new model is based, only incorporates boundary information into the curve propagation process. An error-producing phenomenon called leakage is inevitable wherever there is an uncertain weak edge. In this research, region-based information is added as a constraint into the original GAC model, thereby, giving this proposed method the ability of integrating both boundary and region-based information during the curve propagation. Adding the region-based constraint eliminates the leakage problem. This dissertation applies the proposed augmented GAC model to the problem of highway extraction from high-resolution aerial photography. First, an optimized stopping criterion is designed and used in the implementation of the GAC model. It effectively saves processing time and computations. Second, a seed point propagation framework is designed and implemented. This framework incorporates highway extraction, tracking, and linking into one procedure. A seed point is usually placed at an end node of highway segments close to the boundary of the image or at a position where possible blocking may occur, such as at an overpass bridge or near vehicle crowds. These seed points can be automatically propagated throughout the entire highway network. During the process, road center points are also extracted, which introduces a search direction for solving possible blocking problems. This new framework has been successfully applied to highway network extraction from a large orthophoto mosaic. In the process, vehicles on the highway extracted from mosaic were detected with an 83% success rate.

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.

Pole-Like Road Furniture Detection in Sparse and Unevenly Distributed Mobile Laser Scanning Data

NASA Astrophysics Data System (ADS)

Li, F.; Lehtomäki, M.; Oude Elberink, S.; Vosselman, G.; Puttonen, E.; Kukko, A.; Hyyppä, J.

2018-05-01

Pole-like road furniture detection received much attention due to its traffic functionality in recent years. In this paper, we develop a framework to detect pole-like road furniture from sparse mobile laser scanning data. The framework is carried out in four steps. The unorganised point cloud is first partitioned. Then above ground points are clustered and roughly classified after removing ground points. A slicing check in combination with cylinder masking is proposed to extract pole-like road furniture candidates. Pole-like road furniture are obtained after occlusion analysis in the last stage. The average completeness and correctness of pole-like road furniture in sparse and unevenly distributed mobile laser scanning data was above 0.83. It is comparable to the state of art in the field of pole-like road furniture detection in mobile laser scanning data of good quality and is potentially of practical use in the processing of point clouds collected by autonomous driving platforms.

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.

PAH determination based on a rapid and novel gas purge-microsyringe extraction (GP-MSE) technique in road dust of Shanghai, China: Characterization, source apportionment, and health risk assessment.

PubMed

Zheng, Xin; Yang, Yi; Liu, Min; Yu, Yingpeng; Zhou, John L; Li, Donghao

2016-07-01

A novel cleanup technique termed as gas purge-microsyringe extraction (GP-MSE) was evaluated and applied for polycyclic aromatic hydrocarbon (PAH) determination in road dust samples. A total of 68 road dust samples covering almost the entire Shanghai area were analyzed for 16 priority PAHs using gas chromatography-mass spectrometry. The results indicate that the total PAH concentrations over the investigated sites ranged from 1.04μg/g to 134.02μg/g dw with an average of 13.84μg/g. High-molecular-weight compounds (4-6 rings PAHs) were significantly dominant in the total mass of PAHs, and accounted for 77.85% to 93.62%. Diagnostic ratio analysis showed that the road dust PAHs were mainly from the mixture of petroleum and biomass/coal combustions. Principal component analysis in conjunction with multiple linear regression indicated that the two major origins of road dust PAHs were vehicular emissions and biomass/fossil fuel combustions, which contributed 66.7% and 18.8% to the total road dust PAH burden, respectively. The concentration of benzo[a]pyrene equivalent (BaPeq) varied from 0.16μg/g to 24.47μg/g. The six highly carcinogenic PAH species (benz(a)anthracene, benzo(a)pyrene, benzo(b)fluoranthene, benzo(k)fluoranthene, dibenz(a,h)anthracene, and indeno(1,2,3-cd)pyrene) accounted for 98.57% of the total BaPeq concentration. Thus, the toxicity of PAHs in road dust was highly associated with high-molecular-weight compounds. Copyright © 2016 Elsevier B.V. All rights reserved.

Automatic extraction of pavement markings on streets from point cloud data of mobile LiDAR

NASA Astrophysics Data System (ADS)

Gao, Yang; Zhong, Ruofei; Tang, Tao; Wang, Liuzhao; Liu, Xianlin

2017-08-01

Pavement markings provide an important foundation as they help to keep roads users safe. Accurate and comprehensive information about pavement markings assists the road regulators and is useful in developing driverless technology. Mobile light detection and ranging (LiDAR) systems offer new opportunities to collect and process accurate pavement markings’ information. Mobile LiDAR systems can directly obtain the three-dimensional (3D) coordinates of an object, thus defining spatial data and the intensity of (3D) objects in a fast and efficient way. The RGB attribute information of data points can be obtained based on the panoramic camera in the system. In this paper, we present a novel method process to automatically extract pavement markings using multiple attribute information of the laser scanning point cloud from the mobile LiDAR data. This method process utilizes a differential grayscale of RGB color, laser pulse reflection intensity, and the differential intensity to identify and extract pavement markings. We utilized point cloud density to remove the noise and used morphological operations to eliminate the errors. In the application, we tested our method process on different sections of roads in Beijing, China, and Buffalo, NY, USA. The results indicated that both correctness (p) and completeness (r) were higher than 90%. The method process of this research can be applied to extract pavement markings from huge point cloud data produced by mobile LiDAR.

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.

North End Runway Material Extraction and Transport Environmental Assessment

DTIC Science & Technology

2006-05-01

commercial providers, non -commercial providers, or a combination thereof Material would be transported by public road, commercial rail, ami/or barge...from commercial providers, non -commercial providers, or a combination thereof Material would be transported by public road, commercial rail, ami/or...Terminal Redevelopment NEPA National Environmental Policy Act NFA No further action NFS Non -frost susceptible NHPA National Historic Preservation

Anomaly detection driven active learning for identifying suspicious tracks and events in WAMI video

NASA Astrophysics Data System (ADS)

Miller, David J.; Natraj, Aditya; Hockenbury, Ryler; Dunn, Katherine; Sheffler, Michael; Sullivan, Kevin

2012-06-01

We describe a comprehensive system for learning to identify suspicious vehicle tracks from wide-area motion (WAMI) video. First, since the road network for the scene of interest is assumed unknown, agglomerative hierarchical clustering is applied to all spatial vehicle measurements, resulting in spatial cells that largely capture individual road segments. Next, for each track, both at the cell (speed, acceleration, azimuth) and track (range, total distance, duration) levels, extreme value feature statistics are both computed and aggregated, to form summary (p-value based) anomaly statistics for each track. Here, to fairly evaluate tracks that travel across different numbers of spatial cells, for each cell-level feature type, a single (most extreme) statistic is chosen, over all cells traveled. Finally, a novel active learning paradigm, applied to a (logistic regression) track classifier, is invoked to learn to distinguish suspicious from merely anomalous tracks, starting from anomaly-ranked track prioritization, with ground-truth labeling by a human operator. This system has been applied to WAMI video data (ARGUS), with the tracks automatically extracted by a system developed in-house at Toyon Research Corporation. Our system gives promising preliminary results in highly ranking as suspicious aerial vehicles, dismounts, and traffic violators, and in learning which features are most indicative of suspicious tracks.

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

Research of infrared laser based pavement imaging and crack detection

NASA Astrophysics Data System (ADS)

Hong, Hanyu; Wang, Shu; Zhang, Xiuhua; Jing, Genqiang

2013-08-01

Road crack detection is seriously affected by many factors in actual applications, such as some shadows, road signs, oil stains, high frequency noise and so on. Due to these factors, the current crack detection methods can not distinguish the cracks in complex scenes. In order to solve this problem, a novel method based on infrared laser pavement imaging is proposed. Firstly, single sensor laser pavement imaging system is adopted to obtain pavement images, high power laser line projector is well used to resist various shadows. Secondly, the crack extraction algorithm which has merged multiple features intelligently is proposed to extract crack information. In this step, the non-negative feature and contrast feature are used to extract the basic crack information, and circular projection based on linearity feature is applied to enhance the crack area and eliminate noise. A series of experiments have been performed to test the proposed method, which shows that the proposed automatic extraction method is effective and advanced.

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

A geometric stochastic approach based on marked point processes for road mark detection from high resolution aerial images

NASA Astrophysics Data System (ADS)

Tournaire, O.; Paparoditis, N.

Road detection has been a topic of great interest in the photogrammetric and remote sensing communities since the end of the 70s. Many approaches dealing with various sensor resolutions, the nature of the scene or the wished accuracy of the extracted objects have been presented. This topic remains challenging today as the need for accurate and up-to-date data is becoming more and more important. Based on this context, we will study in this paper the road network from a particular point of view, focusing on road marks, and in particular dashed lines. Indeed, they are very useful clues, for evidence of a road, but also for tasks of a higher level. For instance, they can be used to enhance quality and to improve road databases. It is also possible to delineate the different circulation lanes, their width and functionality (speed limit, special lanes for buses or bicycles...). In this paper, we propose a new robust and accurate top-down approach for dashed line detection based on stochastic geometry. Our approach is automatic in the sense that no intervention from a human operator is necessary to initialise the algorithm or to track errors during the process. The core of our approach relies on defining geometric, radiometric and relational models for dashed lines objects. The model also has to deal with the interactions between the different objects making up a line, meaning that it introduces external knowledge taken from specifications. Our strategy is based on a stochastic method, and in particular marked point processes. Our goal is to find the objects configuration minimising an energy function made-up of a data attachment term measuring the consistency of the image with respect to the objects and a regularising term managing the relationship between neighbouring objects. To sample the energy function, we use Green algorithm's; coupled with a simulated annealing to find its minimum. Results from aerial images at various resolutions are presented showing that our approach is relevant and accurate as it can handle the most frequent layouts of dashed lines. Some issues, for instance, such as the relative weighting of both terms of the energy are also discussed in the conclusion.

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...

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.

Displacement-dispersive liquid-liquid microextraction based on solidification of floating organic drop of trace amounts of palladium in water and road dust samples prior to graphite furnace atomic absorption spectrometry determination.

PubMed

Ghanbarian, Maryam; Afzali, Daryoush; Mostafavi, Ali; Fathirad, Fariba

2013-01-01

A new displacement-dispersive liquid-liquid microextraction method based on the solidification of floating organic drop was developed for separation and preconcentration of Pd(ll) in road dust and aqueous samples. This method involves two steps of dispersive liquid-liquid microextraction based on solidification. In Step 1, Cu ions react with diethyldithiocarbamate (DDTC) to form Cu-DDTC complex, which is extracted by dispersive liquid-liquid microextraction based on a solidification procedure using 1-undecanol (extraction solvent) and ethanol (dispersive solvent). In Step 2, the extracted complex is first dispersed using ethanol in a sample solution containing Pd ions, then a dispersive liquid-liquid microextraction based on a solidification procedure is performed creating an organic drop. In this step, Pd(ll) replaces Cu(ll) from the pre-extracted Cu-DDTC complex and goes into the extraction solvent phase. Finally, the Pd(ll)-containing drop is introduced into a graphite furnace using a microsyringe, and Pd(ll) is determined using atomic absorption spectrometry. Several factors that influence the extraction efficiency of Pd and its subsequent determination, such as extraction and dispersive solvent type and volume, pH of sample solution, centrifugation time, and concentration of DDTC, are optimized.

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.

A new harvest operation cost model to evaluate forest harvest layout alternatives

Treesearch

Mark M. Clark; Russell D. Meller; Timothy P. McDonald; Chao Chi Ting

1997-01-01

The authors develop a new model for harvest operation costs that can be used to evaluate stands for potential harvest. The model is based on felling, extraction, and access costs, and is unique in its consideration of the interaction between harvest area shapes and access roads. The scientists illustrate the model and evaluate the impact of stand size, volume, and road...

Using Selective Drainage Methods to Extract Continuous Surface Flow from 1-Meter Lidar-Derived Digital Elevation Data

USGS Publications Warehouse

Poppenga, Sandra K.; Worstell, Bruce B.; Stoker, Jason M.; Greenlee, Susan K.

2010-01-01

Digital elevation data commonly are used to extract surface flow features. One source for high-resolution elevation data is light detection and ranging (lidar). Lidar can capture a vast amount of topographic detail because of its fine-scale ability to digitally capture the surface of the earth. Because elevation is a key factor in extracting surface flow features, high-resolution lidar-derived digital elevation models (DEMs) provide the detail needed to consistently integrate hydrography with elevation, land cover, structures, and other geospatial features. The U.S. Geological Survey has developed selective drainage methods to extract continuous surface flow from high-resolution lidar-derived digital elevation data. The lidar-derived continuous surface flow network contains valuable information for water resource management involving flood hazard mapping, flood inundation, and coastal erosion. DEMs used in hydrologic applications typically are processed to remove depressions by filling them. High-resolution DEMs derived from lidar can capture much more detail of the land surface than courser elevation data. Therefore, high-resolution DEMs contain more depressions because of obstructions such as roads, railroads, and other elevated structures. The filling of these depressions can significantly affect the DEM-derived surface flow routing and terrain characteristics in an adverse way. In this report, selective draining methods that modify the elevation surface to drain a depression through an obstruction are presented. If such obstructions are not removed from the elevation data, the filling of depressions to create continuous surface flow can cause the flow to spill over an obstruction in the wrong location. Using this modified elevation surface improves the quality of derived surface flow and retains more of the true surface characteristics by correcting large filled depressions. A reliable flow surface is necessary for deriving a consistently connected drainage network, which is important in understanding surface water movement and developing applications for surface water runoff, flood inundation, and erosion. Improved methods are needed to extract continuous surface flow features from high-resolution elevation data based on lidar.

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.

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.

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.

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.

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.

When Dijkstra Meets Vanishing Point: A Stereo Vision Approach for Road Detection.

PubMed

Zhang, Yigong; Su, Yingna; Yang, Jian; Ponce, Jean; Kong, Hui

2018-05-01

In this paper, we propose a vanishing-point constrained Dijkstra road model for road detection in a stereo-vision paradigm. First, the stereo-camera is used to generate the u- and v-disparity maps of road image, from which the horizon can be extracted. With the horizon and ground region constraints, we can robustly locate the vanishing point of road region. Second, a weighted graph is constructed using all pixels of the image, and the detected vanishing point is treated as the source node of the graph. By computing a vanishing-point constrained Dijkstra minimum-cost map, where both disparity and gradient of gray image are used to calculate cost between two neighbor pixels, the problem of detecting road borders in image is transformed into that of finding two shortest paths that originate from the vanishing point to two pixels in the last row of image. The proposed approach has been implemented and tested over 2600 grayscale images of different road scenes in the KITTI data set. The experimental results demonstrate that this training-free approach can detect horizon, vanishing point, and road regions very accurately and robustly. It can achieve promising performance.

Tyre-road friction coefficient estimation based on tyre sensors and lateral tyre deflection: modelling, simulations and experiments

NASA Astrophysics Data System (ADS)

Hong, Sanghyun; Erdogan, Gurkan; Hedrick, Karl; Borrelli, Francesco

2013-05-01

The estimation of the tyre-road friction coefficient is fundamental for vehicle control systems. Tyre sensors enable the friction coefficient estimation based on signals extracted directly from tyres. This paper presents a tyre-road friction coefficient estimation algorithm based on tyre lateral deflection obtained from lateral acceleration. The lateral acceleration is measured by wireless three-dimensional accelerometers embedded inside the tyres. The proposed algorithm first determines the contact patch using a radial acceleration profile. Then, the portion of the lateral acceleration profile, only inside the tyre-road contact patch, is used to estimate the friction coefficient through a tyre brush model and a simple tyre model. The proposed strategy accounts for orientation-variation of accelerometer body frame during tyre rotation. The effectiveness and performance of the algorithm are demonstrated through finite element model simulations and experimental tests with small tyre slip angles on different road surface conditions.

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.

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.

Real-time road detection in infrared imagery

NASA Astrophysics Data System (ADS)

Andre, Haritini E.; McCoy, Keith

1990-09-01

Automatic road detection is an important part in many scene recognition applications. The extraction of roads provides a means of navigation and position update for remotely piloted vehicles or autonomous vehicles. Roads supply strong contextual information which can be used to improve the performance of automatic target recognition (ATh) systems by directing the search for targets and adjusting target classification confidences. This paper will describe algorithmic techniques for labeling roads in high-resolution infrared imagery. In addition, realtime implementation of this structural approach using a processor array based on the Martin Marietta Geometric Arithmetic Parallel Processor (GAPPTh) chip will be addressed. The algorithm described is based on the hypothesis that a road consists of pairs of line segments separated by a distance "d" with opposite gradient directions (antiparallel). The general nature of the algorithm, in addition to its parallel implementation in a single instruction, multiple data (SIMD) machine, are improvements to existing work. The algorithm seeks to identify line segments meeting the road hypothesis in a manner that performs well, even when the side of the road is fragmented due to occlusion or intersections. The use of geometrical relationships between line segments is a powerful yet flexible method of road classification which is independent of orientation. In addition, this approach can be used to nominate other types of objects with minor parametric changes.

Application of multivariate statistical analysis in the pollution and health risk of traffic-related heavy metals.

PubMed

Ebqa'ai, Mohammad; Ibrahim, Bashar

2017-12-01

This study aims to analyse the heavy metal pollutants in Jeddah, the second largest city in the Gulf Cooperation Council with a population exceeding 3.5 million, and many vehicles. Ninety-eight street dust samples were collected seasonally from the six major roads as well as the Jeddah Beach, and subsequently digested using modified Leeds Public Analyst method. The heavy metals (Fe, Zn, Mn, Cu, Cd, and Pb) were extracted from the ash using methyl isobutyl ketone as solvent extraction and eventually analysed by atomic absorption spectroscopy. Multivariate statistical techniques, principal component analysis (PCA), and hierarchical cluster analysis were applied to these data. Heavy metal concentrations were ranked according to the following descending order: Fe > Zn > Mn > Cu > Pb > Cd. In order to study the pollution and health risk from these heavy metals as well as estimating their effect on the environment, pollution indices, integrated pollution index, enrichment factor, daily dose average, hazard quotient, and hazard index were all analysed. The PCA showed high levels of Zn, Fe, and Cd in Al Kurnish road, while these elements were consistently detected on King Abdulaziz and Al Madina roads. The study indicates that high levels of Zn and Pb pollution were recorded for major roads in Jeddah. Six out of seven roads had high pollution indices. This study is the first step towards further investigations into current health problems in Jeddah, such as anaemia and asthma.

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.

[Determination of cadmium by HG-aFS in soil of virescent zone in Chengdu city].

PubMed

Chen, Yuan; Zeng, Ying; Wu, Hong-ji; Wang, Qin-er

2008-12-01

The different speciations of cadmium in soil samples from Chengdu greenbelt were extracted by Tessier sequential extraction method. The contents of total cadmium and different speciation cadmium were determined using HG-AFS. Under optimization condition of HG-AFS and using 2% HCl as medium, and 30 g x L(-1) KBH4 as reductive reagent, 1 mg x L(-1) Co2+ acting together with 10 g x L(-1) CH4N2S can advance the generating efficiency of cadmium compound. The effects of the coexisting elements in soil on the determination of cadmium can be reduced if certain amount of Na4P2O7, K2SO4 and BaCl2 are added. The linear range is 0-10 mg x L(-1) with r=0.9991 and the detection limit is 0.016 mg x L(-1). The recovery is 97.80%-100.2% with RSD of 1.93%. The analytical method is very sensitive and accurate. The distribution of average percentage of five speciations of cadmium in experimental soil samples is: residual fraction (62.1%) > exchangeable fraction (11.7%) > Fe-Mn oxide-bound (9.71%) > carbonate-bound (4.17%) > organic-bound (3.47%). Although residual fraction is the main speciation of cadmium in soil, the content of exchangeable fraction is relatively high. Thus the bioactivity of cadmium in the research area should be recognized. The concentration of cadmium exceeds the country standard in 19 soil sample, accounting for 86. 4% of all soil samples. The soil from Chengdu greenbelt located in 1st ring road, 2nd ring road and 3rd ring road was polluted to different degree. The relative pollution magnitude of them is: 2nd ring road > 1st ring road > 3rd ring road.

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.

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.

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.

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.

Road user behaviour changes following a self-explaining roads intervention.

PubMed

Mackie, Hamish W; Charlton, Samuel G; Baas, Peter H; Villasenor, Pablo C

2013-01-01

The self-explaining roads (SER) approach uses road designs that evoke correct expectations and driving behaviours from road users to create a safe and user-friendly road network. Following the implementation of an SER process and retrofitting of local and collector roads in a suburb within Auckland City, lower speeds on local roads and less variation in speed on both local and collector roads were achieved, along with a closer match between actual and perceived safe speeds. Preliminary analyses of crash data shows that the project has resulted in a 30% reduction crash numbers and an 86% reduction in crash costs per annum, since the road changes were completed. In order to further understand the outcomes from this project, a study was carried out to measure the effects of the SER intervention on the activity and behaviour of all road users. Video was collected over nine separate days, at nine different locations, both before and after SER construction. Road user behaviour categories were developed for all potential road users at different location types and then used to code the video data. Following SER construction, on local roads there was a relatively higher proportion of pedestrians, less uniformity in vehicle lane keeping and less indicating by motorists along with less through traffic, reflecting a more informal/low speed local road environment. Pedestrians were less constrained on local roads following SER construction, possibly reflecting a perceptually safer and more user-friendly environment. These behaviours were not generally evident on collector roads, a trend also shown by the previous study of speed changes. Given that one of the objectives of SER is to match road user behaviour with functionally different road categories, the road user behaviour differences demonstrated on different road types within the SER trial area provides further reinforcement of a successful SER trial. Copyright © 2012 Elsevier Ltd. All rights reserved.

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.

Efficient Extraction of High Centrality Vertices in Distributed Graphs

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

Kumbhare, Alok; Frincu, Marc; Raghavendra, Cauligi S.

2014-09-09

Betweenness centrality (BC) is an important measure for identifying high value or critical vertices in graphs, in variety of domains such as communication networks, road networks, and social graphs. However, calculating betweenness values is prohibitively expensive and, more often, domain experts are interested only in the vertices with the highest centrality values. In this paper, we first propose a partition-centric algorithm (MS-BC) to calculate BC for a large distributed graph that optimizes resource utilization and improves overall performance. Further, we extend the notion of approximate BC by pruning the graph and removing a subset of edges and vertices that contributemore » the least to the betweenness values of other vertices (MSL-BC), which further improves the runtime performance. We evaluate the proposed algorithms using a mix of real-world and synthetic graphs on an HPC cluster and analyze its strengths and weaknesses. The experimental results show an improvement in performance of upto 12x for large sparse graphs as compared to the state-of-the-art, and at the same time highlights the need for better partitioning methods to enable a balanced workload across partitions for unbalanced graphs such as small-world or power-law graphs.« less

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.

Earliest tea as evidence for one branch of the Silk Road across the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Lu, Houyuan; Zhang, Jianping; Yang, Yimin; Yang, Xiaoyan; Xu, Baiqing; Yang, Wuzhan; Tong, Tao; Jin, Shubo; Shen, Caiming; Rao, Huiyun; Li, Xingguo; Lu, Hongliang; Fuller, Dorian Q.; Wang, Luo; Wang, Can; Xu, Deke; Wu, Naiqin

2016-01-01

Phytoliths and biomolecular components extracted from ancient plant remains from Chang’an (Xi’an, the city where the Silk Road begins) and Ngari (Ali) in western Tibet, China, show that the tea was grown 2100 years ago to cater for the drinking habits of the Western Han Dynasty (207BCE-9CE), and then carried toward central Asia by ca.200CE, several hundred years earlier than previously recorded. The earliest physical evidence of tea from both the Chang’an and Ngari regions suggests that a branch of the Silk Road across the Tibetan Plateau, was established by the second to third century CE.

Earliest tea as evidence for one branch of the Silk Road across the Tibetan Plateau.

PubMed

Lu, Houyuan; Zhang, Jianping; Yang, Yimin; Yang, Xiaoyan; Xu, Baiqing; Yang, Wuzhan; Tong, Tao; Jin, Shubo; Shen, Caiming; Rao, Huiyun; Li, Xingguo; Lu, Hongliang; Fuller, Dorian Q; Wang, Luo; Wang, Can; Xu, Deke; Wu, Naiqin

2016-01-07

Phytoliths and biomolecular components extracted from ancient plant remains from Chang'an (Xi'an, the city where the Silk Road begins) and Ngari (Ali) in western Tibet, China, show that the tea was grown 2100 years ago to cater for the drinking habits of the Western Han Dynasty (207BCE-9CE), and then carried toward central Asia by ca.200CE, several hundred years earlier than previously recorded. The earliest physical evidence of tea from both the Chang'an and Ngari regions suggests that a branch of the Silk Road across the Tibetan Plateau, was established by the second to third century CE.

Multiuse trail intersection safety analysis: A crowdsourced data perspective.

PubMed

Jestico, Ben; Nelson, Trisalyn A; Potter, Jason; Winters, Meghan

2017-06-01

Real and perceived concerns about cycling safety are a barrier to increased ridership in many cities. Many people prefer to bike on facilities separated from motor vehicles, such as multiuse trails. However, due to underreporting, cities lack data on bike collisions, especially along greenways and multiuse paths. We used a crowdsourced cycling incident dataset (2005-2016) from BikeMaps.org for the Capital Regional District (CRD), BC, Canada. Our goal was to identify design characteristics associated with unsafe intersections between multiuse trails and roads. 92.8% of mapped incidents occurred between 2014 and 2016. We extracted both collision and near miss incidents at intersections from BikeMaps.org. We conducted site observations at 32 intersections where a major multiuse trail intersected with roads. We compared attributes of reported incidents at multiuse trail-road intersections to those at road-road intersections. We then used negative binomial regression to model the relationship between the number of incidents and the infrastructure characteristics at multiuse trail-road intersections. We found a higher proportion of collisions (38%, or 17/45 total reports) at multiuse trail-road intersections compared to road-road intersections (23%, or 62/268 total reports). A higher proportion of incidents resulted in an injury at multiuse trail-road intersections compared to road-road intersections (33% versus 15%). Cycling volumes, vehicle volumes, and trail sight distance were all associated with incident frequency at multiuse trail-road intersections. Supplementing traditional crash records with crowdsourced cycling incident data provides valuable evidence on cycling safety at intersections between multiuse trails and roads, and more generally, when conflicts occur between diverse transportation modes. Copyright © 2017. Published by Elsevier Ltd.

The burden of road traffic crashes, injuries and deaths in Africa: a systematic review and meta-analysis

PubMed Central

Thompson, Jacqueline Y; Akanbi, Moses A; Azuh, Dominic; Samuel, Victoria; Omoregbe, Nicholas; Ayo, Charles K

2016-01-01

Abstract Objective To estimate the burden of road traffic injuries and deaths for all road users and among different road user groups in Africa. Methods We searched MEDLINE, EMBASE, Global Health, Google Scholar, websites of African road safety agencies and organizations for registry- and population-based studies and reports on road traffic injury and death estimates in Africa, published between 1980 and 2015. Available data for all road users and by road user group were extracted and analysed. We conducted a random-effects meta-analysis and estimated pooled rates of road traffic injuries and deaths. Findings We identified 39 studies from 15 African countries. The estimated pooled rate for road traffic injury was 65.2 per 100 000 population (95% confidence interval, CI: 60.8–69.5) and the death rate was 16.6 per 100 000 population (95% CI: 15.2–18.0). Road traffic injury rates increased from 40.7 per 100 000 population in the 1990s to 92.9 per 100 000 population between 2010 and 2015, while death rates decreased from 19.9 per 100 000 population in the 1990s to 9.3 per 100 000 population between 2010 and 2015. The highest road traffic death rate was among motorized four-wheeler occupants at 5.9 per 100 000 population (95% CI: 4.4–7.4), closely followed by pedestrians at 3.4 per 100 000 population (95% CI: 2.5–4.2). Conclusion The burden of road traffic injury and death is high in Africa. Since registry-based reports underestimate the burden, a systematic collation of road traffic injury and death data is needed to determine the true burden. PMID:27429490

Speciation distribution and mass balance of copper and zinc in urban rain, sediments, and road runoff.

PubMed

Zuo, Xiaojun; Fu, Dafang; Li, He

2012-11-01

Heavy metal pollution in road runoff had caused widespread concern since the last century. However, there are little references on metal speciation in multiple environmental media (e.g., rain, road sediments, and road runoff). Our research targeted the investigation of metal speciation in rain, road sediments, and runoff; the analysis of speciation variation and mass balance of metals among rain, road sediments, and runoff; the selection of main factors by principal component analysis (PCA); and the establishment of equation to evaluate the impact of rain and road sediments to metals in road runoff. Sequential extraction procedure contains five steps for the chemical fractionation of metals. Flame atomic absorption spectrometry (Shimadzu, AA-6800) was used to determine metal speciation concentration, as well as the total and dissolved fractions. The dissolved fractions for both Cu and Zn were dominant in rain. The speciation distribution of Zn was different from that of Cu in road sediments, while speciation distribution of Zn is similar to that of Cu in runoff. The bound to carbonates for both Cu and Zn in road sediments were prone to be dissolved by rain. The levels of Cu and Zn in runoff were not obviously influenced by rain, but significantly influenced by road sediments. The masses for both Cu and Zn among rain, road sediments, and road runoff approximately meet the mass balance equation for all rainfall patterns. Five principal factors were selected for metal regression equation based on PCA, including rainfall, average rainfall intensity, antecedent dry periods, total suspended particles, and temperature. The established regression equations could be used to predict the effect of road runoff on receiving environments.

Pore network extraction from pore space images of various porous media systems

NASA Astrophysics Data System (ADS)

Yi, Zhixing; Lin, Mian; Jiang, Wenbin; Zhang, Zhaobin; Li, Haishan; Gao, Jian

2017-04-01

Pore network extraction, which is defined as the transformation from irregular pore space to a simplified network in the form of pores connected by throats, is significant to microstructure analysis and network modeling. A physically realistic pore network is not only a representation of the pore space in the sense of topology and morphology, but also a good tool for predicting transport properties accurately. We present a method to extract pore network by employing the centrally located medial axis to guide the construction of maximal-balls-like skeleton where the pores and throats are defined and parameterized. To validate our method, various rock samples including sand pack, sandstones, and carbonates were used to extract pore networks. The pore structures were compared quantitatively with the structures extracted by medial axis method or maximal ball method. The predicted absolute permeability and formation factor were verified against the theoretical solutions obtained by lattice Boltzmann method and finite volume method, respectively. The two-phase flow was simulated through the networks extracted from homogeneous sandstones, and the generated relative permeability curves were compared with the data obtained from experimental method and other numerical models. The results show that the accuracy of our network is higher than that of other networks for predicting transport properties, so the presented method is more reliable for extracting physically realistic pore network.

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.

A model of traffic signs recognition with convolutional neural network

NASA Astrophysics Data System (ADS)

Hu, Haihe; Li, Yujian; Zhang, Ting; Huo, Yi; Kuang, Wenqing

2016-10-01

In real traffic scenes, the quality of captured images are generally low due to some factors such as lighting conditions, and occlusion on. All of these factors are challengeable for automated recognition algorithms of traffic signs. Deep learning has provided a new way to solve this kind of problems recently. The deep network can automatically learn features from a large number of data samples and obtain an excellent recognition performance. We therefore approach this task of recognition of traffic signs as a general vision problem, with few assumptions related to road signs. We propose a model of Convolutional Neural Network (CNN) and apply the model to the task of traffic signs recognition. The proposed model adopts deep CNN as the supervised learning model, directly takes the collected traffic signs image as the input, alternates the convolutional layer and subsampling layer, and automatically extracts the features for the recognition of the traffic signs images. The proposed model includes an input layer, three convolutional layers, three subsampling layers, a fully-connected layer, and an output layer. To validate the proposed model, the experiments are implemented using the public dataset of China competition of fuzzy image processing. Experimental results show that the proposed model produces a recognition accuracy of 99.01 % on the training dataset, and yield a record of 92% on the preliminary contest within the fourth best.