Models for IP/MPLS routing performance: convergence, fast reroute, and QoS impact

NASA Astrophysics Data System (ADS)

Choudhury, Gagan L.

2004-09-01

We show how to model the black-holing and looping of traffic during an Interior Gateway Protocol (IGP) convergence event at an IP network and how to significantly improve both the convergence time and packet loss duration through IGP parameter tuning and algorithmic improvement. We also explore some congestion avoidance and congestion control algorithms that can significantly improve stability of networks in the face of occasional massive control message storms. Specifically we show the positive impacts of prioritizing Hello and Acknowledgement packets and slowing down LSA generation and retransmission generation on detecting congestion in the network. For some types of video, voice signaling and circuit emulation applications it is necessary to reduce traffic loss durations following a convergence event to below 100 ms and we explore that using Fast Reroute algorithms based on Multiprotocol Label Switching Traffic Engineering (MPLS-TE) that effectively bypasses IGP convergence. We explore the scalability of primary and backup MPLS-TE tunnels where MPLS-TE domain is in the backbone-only or edge-to-edge. We also show how much extra backbone resource is needed to support Fast Reroute and how can that be reduced by taking advantage of Constrained Shortest Path (CSPF) routing of MPLS-TE and by reserving less than 100% of primary tunnel bandwidth during Fast Reroute.

Mixed Traffic Information Collection System based on Pressure Sensor

NASA Astrophysics Data System (ADS)

Liao, Wenzhe; Liu, Mingsheng; Meng, Qingli

The traffic information collection is the base of Intelligent Traffic.At present, there exist mixed traffic situation in urban road in China. This paper researched and implemented a system through collecting the vehicle and bicycle mixed traffic flow parameters based on pressure sensor. According to information collection requirements, we selected pressure sensor, designed the data collection, storage and other hardware circuitries and information processing software. The experiment shows that the system can meet the demand of traffic information collection in the actual.

Improving the roadside environment through integrating air quality and traffic-related data.

DOT National Transportation Integrated Search

2016-12-01

Urban arterial corridors are landscapes that give rise to short and long-term : exposures to transportation-related pollution. With high traffic volumes, congestion, and : a wide mix of road users and land uses at the road edge, urban arterial enviro...

Discrete Mathematical Approaches to Graph-Based Traffic Analysis

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

Joslyn, Cliff A.; Cowley, Wendy E.; Hogan, Emilie A.

2014-04-01

Modern cyber defense and anlaytics requires general, formal models of cyber systems. Multi-scale network models are prime candidates for such formalisms, using discrete mathematical methods based in hierarchically-structured directed multigraphs which also include rich sets of labels. An exemplar of an application of such an approach is traffic analysis, that is, observing and analyzing connections between clients, servers, hosts, and actors within IP networks, over time, to identify characteristic or suspicious patterns. Towards that end, NetFlow (or more generically, IPFLOW) data are available from routers and servers which summarize coherent groups of IP packets flowing through the network. In thismore » paper, we consider traffic analysis of Netflow using both basic graph statistics and two new mathematical measures involving labeled degree distributions and time interval overlap measures. We do all of this over the VAST test data set of 96M synthetic Netflow graph edges, against which we can identify characteristic patterns of simulated ground-truth network attacks.« less

Real-time 3D reconstruction of road curvature in far look-ahead distance from analysis of image sequences

NASA Astrophysics Data System (ADS)

Behringer, Reinhold

1995-12-01

A system for visual road recognition in far look-ahead distance, implemented in the autonomous road vehicle VaMP (a passenger car), is described. Visual cues of a road in a video image are the bright lane markings and the edges formed at the road borders. In a distance of more than 100 m, the most relevant road cue is the homogeneous road area, limited by the two border edges. These cues can be detected by the image processing module KRONOS applying edge detection techniques and areal 2D segmentation based on resolution triangles (analogous to a resolution pyramid). An estimation process performs an update of a state vector, which describes spatial road shape and vehicle orientation relative to the road. This state vector is estimated every 40 ms by exploiting knowledge about the vehicle movement (spatio-temporal model of vehicle dynamics) and the road design rules (clothoidal segments). Kalman filter techniques are applied to obtain an optimal estimate of the state vector by evaluating the measurements of the road border positions in the image sequence taken by a set of CCD cameras. The road consists of segments with piecewise constant curvature parameters. The borders between these segments can be detected by applying methods which have been developed for detection of discontinuities during time-discrete measurements. The road recognition system has been tested in autonomous rides with VaMP on public Autobahnen in real traffic at speeds up to 130 km/h.

Real-Time Lane Region Detection Using a Combination of Geometrical and Image Features

PubMed Central

Cáceres Hernández, Danilo; Kurnianggoro, Laksono; Filonenko, Alexander; Jo, Kang Hyun

2016-01-01

Over the past few decades, pavement markings have played a key role in intelligent vehicle applications such as guidance, navigation, and control. However, there are still serious issues facing the problem of lane marking detection. For example, problems include excessive processing time and false detection due to similarities in color and edges between traffic signs (channeling lines, stop lines, crosswalk, arrows, etc.). This paper proposes a strategy to extract the lane marking information taking into consideration its features such as color, edge, and width, as well as the vehicle speed. Firstly, defining the region of interest is a critical task to achieve real-time performance. In this sense, the region of interest is dependent on vehicle speed. Secondly, the lane markings are detected by using a hybrid color-edge feature method along with a probabilistic method, based on distance-color dependence and a hierarchical fitting model. Thirdly, the following lane marking information is extracted: the number of lane markings to both sides of the vehicle, the respective fitting model, and the centroid information of the lane. Using these parameters, the region is computed by using a road geometric model. To evaluate the proposed method, a set of consecutive frames was used in order to validate the performance. PMID:27869657

Graph Coloring Used to Model Traffic Lights.

ERIC Educational Resources Information Center

Williams, John

1992-01-01

Two scheduling problems, one involving setting up an examination schedule and the other describing traffic light problems, are modeled as colorings of graphs consisting of a set of vertices and edges. The chromatic number, the least number of colors necessary for coloring a graph, is employed in the solutions. (MDH)

Impact of edge lines on safety of rural two-lane highways.

DOT National Transportation Integrated Search

2005-10-01

This report documents the results of the project for Impact of Edge Lines on Safety of Rural Two Lane Highways. This research project was initiated in the effort of compliance with the updated version of the Manual on Uniform Traffic Control De...

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.

Electronic rumble strip

NASA Astrophysics Data System (ADS)

Stauffer, Donald R.; Lenz, James

1997-02-01

Single vehicle run-off-road accidents are responsible for significant numbers of injuries and fatalities, and significant property damage. This fact spurs interest in warning systems to alert drivers that vehicles are drifting towards the edge of the road, and that a run-off road accident is imminent. An early attempt at such a warning system is the use of machined grooves on the shoulder to create a rumble strip. Such a system only provides warning, however, as the vehicle actually leaves the traffic lane. More desirable is a system that warns in anticipation of such departure. Honeywell has under development a magnetic lateral guidance system that couples a sensitive magnetoresistive transducer with a magnetic traffic marking tape being developed by 3M. While this development was initially undertaken for use in automated highways, or for special tasks such as guiding snowplow owners, the system can provide an effective, all-weather warning system to provide alert of impending departure from the roadway. This electronic rumble strip is actually a simpler system than the baseline guidance system, and can monitor both distance from the traffic lane edge and the speed of approach to the edge with a low cost sensor.

Switching performance of OBS network model under prefetched real traffic

NASA Astrophysics Data System (ADS)

Huang, Zhenhua; Xu, Du; Lei, Wen

2005-11-01

Optical Burst Switching (OBS) [1] is now widely considered as an efficient switching technique in building the next generation optical Internet .So it's very important to precisely evaluate the performance of the OBS network model. The performance of the OBS network model is variable in different condition, but the most important thing is that how it works under real traffic load. In the traditional simulation models, uniform traffics are usually generated by simulation software to imitate the data source of the edge node in the OBS network model, and through which the performance of the OBS network is evaluated. Unfortunately, without being simulated by real traffic, the traditional simulation models have several problems and their results are doubtable. To deal with this problem, we present a new simulation model for analysis and performance evaluation of the OBS network, which uses prefetched IP traffic to be data source of the OBS network model. The prefetched IP traffic can be considered as real IP source of the OBS edge node and the OBS network model has the same clock rate with a real OBS system. So it's easy to conclude that this model is closer to the real OBS system than the traditional ones. The simulation results also indicate that this model is more accurate to evaluate the performance of the OBS network system and the results of this model are closer to the actual situation.

Empirical study on neural network based predictive techniques for automatic number plate recognition

NASA Astrophysics Data System (ADS)

Shashidhara, M. S.; Indrakumar, S. S.

2011-10-01

The objective of this study is to provide an easy, accurate and effective technology for the Bangalore city traffic control. This is based on the techniques of image processing and laser beam technology. The core concept chosen here is an image processing technology by the method of automatic number plate recognition system. First number plate is recognized if any vehicle breaks the traffic rules in the signals. The number is fetched from the database of the RTO office by the process of automatic database fetching. Next this sends the notice and penalty related information to the vehicle owner email-id and an SMS sent to vehicle owner. In this paper, we use of cameras with zooming options & laser beams to get accurate pictures further applied image processing techniques such as Edge detection to understand the vehicle, Identifying the location of the number plate, Identifying the number plate for further use, Plain plate number, Number plate with additional information, Number plates in the different fonts. Accessing the database of the vehicle registration office to identify the name and address and other information of the vehicle number. The updates to be made to the database for the recording of the violation and penalty issues. A feed forward artificial neural network is used for OCR. This procedure is particularly important for glyphs that are visually similar such as '8' and '9' and results in training sets of between 25,000 and 40,000 training samples. Over training of the neural network is prevented by Bayesian regularization. The neural network output value is set to 0.05 when the input is not desired glyph, and 0.95 for correct input.

Discharge characteristics of four highway drainage systems in Ohio

USGS Publications Warehouse

Straub, D.E.

1995-01-01

Excessive water in the subbase of high-way combined with large traffic volumes and heavy loads is a major cause of road deterioration. Prompt removal of any excess water in a subbase will decrease the road deterioration and extend the effective life of a highway. This study presents discharge characteristics of four highway subbase drainage systems. These systems consisted of shallow, longitudal trenches with geocomposite drain materials (edge drains made from a polyethylene core surrounded by a geotextile filter fabric) that underline the joint between the shoulder and the traffic lane of State Route 16, approximately 1.0 mile southeast of Granville, Ohio. For selected rainfall-runoff events the maximum discharge, discharge characteristics from April 1991 through November 1993 were computed for three geocomposite products- a post type, an oblong-pipe type, and a cusp type-and a conventional perforated pipe edge drain. In general, the discharge characteristics of the conventional edge drain and that of the oblong-pipe edge drain were similar for most of the rainfall-runoff event characteristics. Both produced most of the highest maximum discharges and largest discharge volumes among the four longitudal edge drains. The post edge drain produced smaller maximum discharge and volumes than the conventional and oblong-pipe edge drains, but it had the shortest lag times for most of the event characteristics. The cusp edge drain produced small maximum discharges and small volumes similar to those from the post edge drain, but it had the longest lag times of all the edge drains for most of the event characteristics. The cusp edge drain may have also had some problems during installation which could have affected the discharge characteristics.

Characterization of air pollutant concentrations, fleet emission factors, and dispersion near a North Carolina interstate freeway across two seasons

NASA Astrophysics Data System (ADS)

Saha, Provat K.; Khlystov, Andrey; Snyder, Michelle G.; Grieshop, Andrew P.

2018-03-01

We present field measurement data and modeling of multiple traffic-related air pollutants during two seasons at a site adjoining Interstate 40, near Durham, North Carolina. We analyze spatial-temporal and seasonal trends and fleet-average pollutant emission factors and use our data to evaluate a line source dispersion model. Month-long measurement campaigns were performed in summer 2015 and winter 2016. Data were collected at a fixed near-road site located within 10 m from the highway edge, an upwind background site and, under favorable meteorological conditions, along downwind perpendicular transects. Measurements included the size distribution, chemical composition, and volatility of submicron particles, black carbon (BC), nitrogen oxides (NOx), meteorological conditions and traffic activity data. Results show strong seasonal and diurnal differences in spatial distribution of traffic sourced pollutants. A strong signature of vehicle emissions was observed within 100-150 m from the highway edge with significantly higher concentrations during morning. Substantially higher concentrations and less-sharp near-road gradients were observed in winter for many species. Season-specific fleet-average fuel-based emission factors for NO, NOx, BC, and particle number (PN) were derived based on up- and down-wind roadside measurements. The campaign-average NOx and PN emission factors were 20% and 300% higher in winter than summer, respectively. These results suggest that the combined effect of higher emissions and their slower downwind dispersion in winter dictate the observed higher downwind concentrations and wider highway influence zone in winter for several species. Finally, measurements of traffic data, emission factors, and pollutant concentrations were integrated to evaluate a line source dispersion model (R-LINE). The dispersion model captured the general trends in the spatial and temporal patterns in near-road concentrations. However, there was a tendency for the model to under-predict concentrations near the road in the mornings and over-predict concentrations in the evenings.

Traffic Flow Density Distribution Based on FEM

NASA Astrophysics Data System (ADS)

Ma, Jing; Cui, Jianming

In analysis of normal traffic flow, it usually uses the static or dynamic model to numerical analyze based on fluid mechanics. However, in such handling process, the problem of massive modeling and data handling exist, and the accuracy is not high. Finite Element Method (FEM) is a production which is developed from the combination of a modern mathematics, mathematics and computer technology, and it has been widely applied in various domain such as engineering. Based on existing theory of traffic flow, ITS and the development of FEM, a simulation theory of the FEM that solves the problems existing in traffic flow is put forward. Based on this theory, using the existing Finite Element Analysis (FEA) software, the traffic flow is simulated analyzed with fluid mechanics and the dynamics. Massive data processing problem of manually modeling and numerical analysis is solved, and the authenticity of simulation is enhanced.

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.

Real-time traffic sign recognition based on a general purpose GPU and deep-learning.

PubMed

Lim, Kwangyong; Hong, Yongwon; Choi, Yeongwoo; Byun, Hyeran

2017-01-01

We present a General Purpose Graphics Processing Unit (GPGPU) based real-time traffic sign detection and recognition method that is robust against illumination changes. There have been many approaches to traffic sign recognition in various research fields; however, previous approaches faced several limitations when under low illumination or wide variance of light conditions. To overcome these drawbacks and improve processing speeds, we propose a method that 1) is robust against illumination changes, 2) uses GPGPU-based real-time traffic sign detection, and 3) performs region detecting and recognition using a hierarchical model. This method produces stable results in low illumination environments. Both detection and hierarchical recognition are performed in real-time, and the proposed method achieves 0.97 F1-score on our collective dataset, which uses the Vienna convention traffic rules (Germany and South Korea).

32 CFR 636.26 - Pedestrian's rights and duties.

Code of Federal Regulations, 2012 CFR

2012-07-01

... shoulder of the roadway as far from the edge of the roadway as possible. When neither sidewalks nor a shoulder are available, pedestrians will walk on the extreme edge of the roadway, facing traffic, and will... pedestrians or joggers while walking or jogging on roadways or on the shoulders of roadways is prohibited. ...

32 CFR 636.26 - Pedestrian's rights and duties.

Code of Federal Regulations, 2014 CFR

2014-07-01

... shoulder of the roadway as far from the edge of the roadway as possible. When neither sidewalks nor a shoulder are available, pedestrians will walk on the extreme edge of the roadway, facing traffic, and will... pedestrians or joggers while walking or jogging on roadways or on the shoulders of roadways is prohibited. ...

32 CFR 636.26 - Pedestrian's rights and duties.

Code of Federal Regulations, 2011 CFR

2011-07-01

... shoulder of the roadway as far from the edge of the roadway as possible. When neither sidewalks nor a shoulder are available, pedestrians will walk on the extreme edge of the roadway, facing traffic, and will... pedestrians or joggers while walking or jogging on roadways or on the shoulders of roadways is prohibited. ...

32 CFR 636.26 - Pedestrian's rights and duties.

Code of Federal Regulations, 2013 CFR

2013-07-01

... shoulder of the roadway as far from the edge of the roadway as possible. When neither sidewalks nor a shoulder are available, pedestrians will walk on the extreme edge of the roadway, facing traffic, and will... pedestrians or joggers while walking or jogging on roadways or on the shoulders of roadways is prohibited. ...

Towards a Cloud Based Smart Traffic Management Framework

NASA Astrophysics Data System (ADS)

Rahimi, M. M.; Hakimpour, F.

2017-09-01

Traffic big data has brought many opportunities for traffic management applications. However several challenges like heterogeneity, storage, management, processing and analysis of traffic big data may hinder their efficient and real-time applications. All these challenges call for well-adapted distributed framework for smart traffic management that can efficiently handle big traffic data integration, indexing, query processing, mining and analysis. In this paper, we present a novel, distributed, scalable and efficient framework for traffic management applications. The proposed cloud computing based framework can answer technical challenges for efficient and real-time storage, management, process and analyse of traffic big data. For evaluation of the framework, we have used OpenStreetMap (OSM) real trajectories and road network on a distributed environment. Our evaluation results indicate that speed of data importing to this framework exceeds 8000 records per second when the size of datasets is near to 5 million. We also evaluate performance of data retrieval in our proposed framework. The data retrieval speed exceeds 15000 records per second when the size of datasets is near to 5 million. We have also evaluated scalability and performance of our proposed framework using parallelisation of a critical pre-analysis in transportation applications. The results show that proposed framework achieves considerable performance and efficiency in traffic management applications.

An agent-based model for queue formation of powered two-wheelers in heterogeneous traffic

NASA Astrophysics Data System (ADS)

Lee, Tzu-Chang; Wong, K. I.

2016-11-01

This paper presents an agent-based model (ABM) for simulating the queue formation of powered two-wheelers (PTWs) in heterogeneous traffic at a signalized intersection. The main novelty is that the proposed interaction rule describing the position choice behavior of PTWs when queuing in heterogeneous traffic can capture the stochastic nature of the decision making process. The interaction rule is formulated as a multinomial logit model, which is calibrated by using a microscopic traffic trajectory dataset obtained from video footage. The ABM is validated against the survey data for the vehicular trajectory patterns, queuing patterns, queue lengths, and discharge rates. The results demonstrate that the proposed model is capable of replicating the observed queue formation process for heterogeneous traffic.

Real-time traffic sign recognition based on a general purpose GPU and deep-learning

PubMed Central

Hong, Yongwon; Choi, Yeongwoo; Byun, Hyeran

2017-01-01

We present a General Purpose Graphics Processing Unit (GPGPU) based real-time traffic sign detection and recognition method that is robust against illumination changes. There have been many approaches to traffic sign recognition in various research fields; however, previous approaches faced several limitations when under low illumination or wide variance of light conditions. To overcome these drawbacks and improve processing speeds, we propose a method that 1) is robust against illumination changes, 2) uses GPGPU-based real-time traffic sign detection, and 3) performs region detecting and recognition using a hierarchical model. This method produces stable results in low illumination environments. Both detection and hierarchical recognition are performed in real-time, and the proposed method achieves 0.97 F1-score on our collective dataset, which uses the Vienna convention traffic rules (Germany and South Korea). PMID:28264011

Fast traffic sign recognition with a rotation invariant binary pattern based feature.

PubMed

Yin, Shouyi; Ouyang, Peng; Liu, Leibo; Guo, Yike; Wei, Shaojun

2015-01-19

Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern) based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network) based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed.

Fast Traffic Sign Recognition with a Rotation Invariant Binary Pattern Based Feature

PubMed Central

Yin, Shouyi; Ouyang, Peng; Liu, Leibo; Guo, Yike; Wei, Shaojun

2015-01-01

Robust and fast traffic sign recognition is very important but difficult for safe driving assistance systems. This study addresses fast and robust traffic sign recognition to enhance driving safety. The proposed method includes three stages. First, a typical Hough transformation is adopted to implement coarse-grained location of the candidate regions of traffic signs. Second, a RIBP (Rotation Invariant Binary Pattern) based feature in the affine and Gaussian space is proposed to reduce the time of traffic sign detection and achieve robust traffic sign detection in terms of scale, rotation, and illumination. Third, the techniques of ANN (Artificial Neutral Network) based feature dimension reduction and classification are designed to reduce the traffic sign recognition time. Compared with the current work, the experimental results in the public datasets show that this work achieves robustness in traffic sign recognition with comparable recognition accuracy and faster processing speed, including training speed and recognition speed. PMID:25608217

Automatic Traffic Advisory and Resolution Service (ATARS) Multi-Site Algorithms. Revision 1,

DTIC Science & Technology

1980-10-01

Summary Concept Description The Automatic Traffic Advisory and Resolution Service is a ground based collision avoidance system to be implemented in the...capability. A ground based computer processes the data and continuously provides proximity warning information and, when necessary, resolution advisories to...of ground- based air traffic control which provides proximity warning and separation services to uncontrolled aircraft in a given region of airspace. it

Capacity planning of a wide-sense nonblocking generalized survivable network

NASA Astrophysics Data System (ADS)

Ho, Kwok Shing; Cheung, Kwok Wai

2006-06-01

Generalized survivable networks (GSNs) have two interesting properties that are essential attributes for future backbone networks--full survivability against link failures and support for dynamic traffic demands. GSNs incorporate the nonblocking network concept into the survivable network models. Given a set of nodes and a topology that is at least two-edge connected, a certain minimum capacity is required for each edge to form a GSN. The edge capacity is bounded because each node has an input-output capacity limit that serves as a constraint for any allowable traffic demand matrix. The GSN capacity planning problem is nondeterministic polynomial time (NP) hard. We first give a rigorous mathematical framework; then we offer two different solution approaches. The two-phase approach is fast, but the joint optimization approach yields a better bound. We carried out numerical computations for eight networks with different topologies and found that the cost of a GSN is only a fraction (from 52% to 89%) more than that of a static survivable network.

Designing Scenarios for Controller-in-the-Loop Air Traffic Simulations

NASA Technical Reports Server (NTRS)

Kupfer, Michael; Mercer, Joey S.; Cabrall, Christopher; Callantine, Todd

2013-01-01

Well prepared traffic scenarios contribute greatly to the success of controller-in-the-loop simulations. This paper describes each stage in the design process of realistic scenarios based on real-world traffic, to be used in the Airspace Operations Laboratory for simulations within the Air Traffic Management Technology Demonstration 1 effort. The steps from the initial analysis of real-world traffic, to the editing of individual aircraft records in the scenario file, until the final testing of the scenarios before the simulation conduct, are all described. The iterative nature of the design process and the various efforts necessary to reach the required fidelity, as well as the applied design strategies, challenges, and tools used during this process are also discussed.

Laminar Flow Control Leading Edge Systems in Simulated Airline Service

NASA Technical Reports Server (NTRS)

Wagner, R. D.; Maddalon, D. V.; Fisher, D. F.

1988-01-01

Achieving laminar flow on the wings of a commercial transport involves difficult problems associated with the wing leading edge. The NASA Leading Edge Flight Test Program has made major progress toward the solution of these problems. The effectiveness and practicality of candidate laminar flow leading edge systems were proven under representative airline service conditions. This was accomplished in a series of simulated airline service flights by modifying a JetStar aircraft with laminar flow leading edge systems and operating it out of three commercial airports in the United States. The aircraft was operated as an airliner would under actual air traffic conditions, in bad weather, and in insect infested environments.

A study on efficient detection of network-based IP spoofing DDoS and malware-infected Systems.

PubMed

Seo, Jung Woo; Lee, Sang Jin

2016-01-01

Large-scale network environments require effective detection and response methods against DDoS attacks. Depending on the advancement of IT infrastructure such as the server or network equipment, DDoS attack traffic arising from a few malware-infected systems capable of crippling the organization's internal network has become a significant threat. This study calculates the frequency of network-based packet attributes and analyzes the anomalies of the attributes in order to detect IP-spoofed DDoS attacks. Also, a method is proposed for the effective detection of malware infection systems triggering IP-spoofed DDoS attacks on an edge network. Detection accuracy and performance of the collected real-time traffic on a core network is analyzed thru the use of the proposed algorithm, and a prototype was developed to evaluate the performance of the algorithm. As a result, DDoS attacks on the internal network were detected in real-time and whether or not IP addresses were spoofed was confirmed. Detecting hosts infected by malware in real-time allowed the execution of intrusion responses before stoppage of the internal network caused by large-scale attack traffic.

14 CFR 139.311 - Marking, signs, and lighting.

Code of Federal Regulations, 2011 CFR

2011-01-01

... prevent interference with air traffic control and aircraft operations. (f) Standards. FAA Advisory... following taxiway lighting systems: (i) Centerline lights. (ii) Centerline reflectors. (iii) Edge lights...

Evaluation of the traffic parameters in a metropolitan area by fusing visual perceptions and CNN processing of webcam images.

PubMed

Faro, Alberto; Giordano, Daniela; Spampinato, Concetto

2008-06-01

This paper proposes a traffic monitoring architecture based on a high-speed communication network whose nodes are equipped with fuzzy processors and cellular neural network (CNN) embedded systems. It implements a real-time mobility information system where visual human perceptions sent by people working on the territory and video-sequences of traffic taken from webcams are jointly processed to evaluate the fundamental traffic parameters for every street of a metropolitan area. This paper presents the whole methodology for data collection and analysis and compares the accuracy and the processing time of the proposed soft computing techniques with other existing algorithms. Moreover, this paper discusses when and why it is recommended to fuse the visual perceptions of the traffic with the automated measurements taken from the webcams to compute the maximum traveling time that is likely needed to reach any destination in the traffic network.

Planning and deployment of DWDM systems: a reality

NASA Astrophysics Data System (ADS)

Mishra, Data S.

2001-10-01

The new definition and implementation of new communication network architectures and elements in the present data-centric world are due to dramatic change in technology, explosive growth in bandwidth requirement and de-regulated, privatized and competitive telecommunication market. Network Convergence, Disruptive Technology and Convulsive Market are the basic forces who are pushing the future network towards Packet based Optical Core Network and varieties of Access Network along with integrated NMS. Well-known Moore's law governs the result of progress in silicon processing and accordingly the present capacity of network must be multiplied by 100 times in 10 years. To build a global network which is 100 times powerful than present one by scaling up today's technology can not be a practical solution due to requirement of 100 fold increase in cost, power and size. Today's two network (Low delay, fixed bandwidth, Poisson voice traffic based, circuit-switched PSTN/PLMN and variable delay, variable bandwidth, no-guaranteed QoS based packet switched internet) are converging towards two-layer network (IP and ATM in lower layer; DWDM in network layer). SDH Network which was well drafted before explosive data traffic and was best suitable for Interoperability, Survivability, Reliability and Manageability will be taken over by DWDM Network by 2005 due to 90% of data traffic. This paper describes the way to build the Communication Network (either by migration or by overlay) with an overview of the equipment and technologies required to design the DWDM Network. Service Providers are facing tough challenges for selection of emerging technologies and advances in network standard for bandwidth hungry, valued customers. The reduction of cost of services due to increased competition , explosive growth of internet and 10GbE Ethernet (which is being considered as an end-to-end network solution) have given surprise to many network architects and designers. To provide transparency to data-rate and data-format the gap between electrical layer and Optical backbone layer has to be filled. By partitioning the Optical Bandwidth of Optical Fibre Cable into the wavelengths (32 to 120) Wavelength Division Multiplexing can transport data rate from 10MB/s to 10GB/s on each wavelength. In this paper we will analyze the difficult strategies of suppliers and obstacles in the way of service providers to make DWDM a reality in the field either as Upgrade or Overlay or New Network. The difficult constraint of protection scheme with respect to compatibility with existing network and network under development has to sorted out along with present standard of Optical Fibre to carry DWDM signal in cost effective way to Access , Edge and Metro part of our network. The future of IP under DWDM is going to be key element for Network Planners in future. Fundamental limitation of bit manipulation in Photonic domain will have implication on the network design, cost and migration to all optical network because Photons are computer un-friendly and not mature enough to give memory and logic devices. In the environment of heterogeneous traffic the DWDM based All Optical Network should behave as per expectation of users whose primary traffic will be multi-media IP type. The quality of service (QoS), Virtual Path Network (VPN) over DWDM, OXC and intelligence at the edge will play a major role in future deployment of DWDM in our network . The development of improved fiber characteristics, EDFAs and Photonic component has led the carriers to go for Dense WDM Network.

Framework based on stochastic L-Systems for modeling IP traffic with multifractal behavior

NASA Astrophysics Data System (ADS)

Salvador, Paulo S.; Nogueira, Antonio; Valadas, Rui

2003-08-01

In a previous work we have introduced a multifractal traffic model based on so-called stochastic L-Systems, which were introduced by biologist A. Lindenmayer as a method to model plant growth. L-Systems are string rewriting techniques, characterized by an alphabet, an axiom (initial string) and a set of production rules. In this paper, we propose a novel traffic model, and an associated parameter fitting procedure, which describes jointly the packet arrival and the packet size processes. The packet arrival process is modeled through a L-System, where the alphabet elements are packet arrival rates. The packet size process is modeled through a set of discrete distributions (of packet sizes), one for each arrival rate. In this way the model is able to capture correlations between arrivals and sizes. We applied the model to measured traffic data: the well-known pOct Bellcore, a trace of aggregate WAN traffic and two traces of specific applications (Kazaa and Operation Flashing Point). We assess the multifractality of these traces using Linear Multiscale Diagrams. The suitability of the traffic model is evaluated by comparing the empirical and fitted probability mass and autocovariance functions; we also compare the packet loss ratio and average packet delay obtained with the measured traces and with traces generated from the fitted model. Our results show that our L-System based traffic model can achieve very good fitting performance in terms of first and second order statistics and queuing behavior.

Stationary LiDAR for traffic and safety applications - vehicles interpretation and tracking.

DOT National Transportation Integrated Search

2014-01-01

The goal of the T-Scan project is to develop a data processing module for a novel LiDAR-based traffic scanner to collect highly accurate microscopic traffic data at road intersections. : T-Scan uses Light Detection and Ranging (LiDAR) technology that...

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-07-11

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

Entropy-based heavy tailed distribution transformation and visual analytics for monitoring massive network traffic

NASA Astrophysics Data System (ADS)

Han, Keesook J.; Hodge, Matthew; Ross, Virginia W.

2011-06-01

For monitoring network traffic, there is an enormous cost in collecting, storing, and analyzing network traffic datasets. Data mining based network traffic analysis has a growing interest in the cyber security community, but is computationally expensive for finding correlations between attributes in massive network traffic datasets. To lower the cost and reduce computational complexity, it is desirable to perform feasible statistical processing on effective reduced datasets instead of on the original full datasets. Because of the dynamic behavior of network traffic, traffic traces exhibit mixtures of heavy tailed statistical distributions or overdispersion. Heavy tailed network traffic characterization and visualization are important and essential tasks to measure network performance for the Quality of Services. However, heavy tailed distributions are limited in their ability to characterize real-time network traffic due to the difficulty of parameter estimation. The Entropy-Based Heavy Tailed Distribution Transformation (EHTDT) was developed to convert the heavy tailed distribution into a transformed distribution to find the linear approximation. The EHTDT linearization has the advantage of being amenable to characterize and aggregate overdispersion of network traffic in realtime. Results of applying the EHTDT for innovative visual analytics to real network traffic data are presented.

Concept for a Satellite-Based Advanced Air Traffic Management System : Volume 3. Subsystem Functional Description.

DOT National Transportation Integrated Search

1974-02-01

The volume presents a detailed description of the subsystems that comprise the Satellite-Based Advanced Air Traffic Management System. Described in detail are the surveillance, navigation, communications, data processing, and airport subsystems. The ...

Android-based E-Traffic law enforcement system in Surakarta City

NASA Astrophysics Data System (ADS)

Yulianto, Budi; Setiono

2018-03-01

The urban advancement is always overpowered by the increasing number of vehicles as the need for movement of people and goods. This can lead to traffic problems if there is no effort on the implementation of traffic management and engineering, and traffic law enforcement. In this case, the Government of Surakarta City has implemented various policies and regulations related to traffic management and engineering in order to run traffic in an orderly, safe and comfortable manner according to the applicable law. However, conditions in the field shows that traffic violations still occurred frequently due to the weakness of traffic law enforcement in terms of human resources and the system. In this connection, a tool is needed to support traffic law enforcement, especially in relation to the reporting system of traffic violations. This study aims to develop an Android-based traffic violations reporting application (E-Traffic Law Enforcement) as part of the traffic law enforcement system in Surakarta City. The Android-apps records the location and time of the traffic violations incident along with the visual evidence of the infringement. This information will be connected to the database system to detect offenders and to do the traffic law enforcement process.

Is vehicle automation enough to prevent crashes? Role of traffic operations in automated driving environments for traffic safety.

PubMed

Jeong, Eunbi; Oh, Cheol; Lee, Seolyoung

2017-07-01

Automated driving systems (ADSs) are expected to prevent traffic accidents caused by driver carelessness on freeways. There is no doubt regarding this safety benefit if all vehicles in the transportation system were equipped with ADSs; however, it is implausible to expect that ADSs will reach 100% market penetration rate (MPR) in the near future. Therefore, the following question arises: 'Can ADSs, which consider only situations in the vicinity of an equipped vehicle, really contribute to a significant reduction in traffic accidents?' To address this issue, the interactions between equipped and unequipped vehicles must be investigated, which is the purpose of this study. This study evaluated traffic safety at different MPRs based on a proposed index to represent the overall rear-end crash risk of the traffic stream. Two approaches were evaluated for adjusting longitudinal vehicle maneuvers: vehicle safety-based maneuvering (VSM), which considers the crash risk of an equipped vehicle and its neighboring vehicles, and traffic safety-based maneuvering (TSM), which considers the overall crash risk in the traffic stream. TSM assumes that traffic operational agencies are able to monitor all the vehicles and to intervene in vehicle maneuvering. An optimization process, which attempts to obtain vehicle maneuvering control parameters to minimize the overall crash risk, is integrated into the proposed evaluation framework. The main purpose of employing the optimization process for vehicle maneuvering in this study is to identify opportunities to improve traffic safety through effective traffic management rather than developing a vehicle control algorithm that can be implemented in practice. The microscopic traffic simulator VISSIM was used to simulate the freeway traffic stream and to conduct systematic evaluations based on the proposed methodology. Both TSM and VSM achieved significant reductions in the potential for rear-end crashes. However, TSM obtained much greater reductions when the MPR was greater than 50%. This study should inspire transportation researchers and engineers to develop effective traffic operations strategies for automated driving environments. Copyright © 2017. Published by Elsevier Ltd.

Real-time color/shape-based traffic signs acquisition and recognition system

NASA Astrophysics Data System (ADS)

Saponara, Sergio

2013-02-01

A real-time system is proposed to acquire from an automotive fish-eye CMOS camera the traffic signs, and provide their automatic recognition on the vehicle network. Differently from the state-of-the-art, in this work color-detection is addressed exploiting the HSI color space which is robust to lighting changes. Hence the first stage of the processing system implements fish-eye correction and RGB to HSI transformation. After color-based detection a noise deletion step is implemented and then, for the classification, a template-based correlation method is adopted to identify potential traffic signs, of different shapes, from acquired images. Starting from a segmented-image a matching with templates of the searched signs is carried out using a distance transform. These templates are organized hierarchically to reduce the number of operations and hence easing real-time processing for several types of traffic signs. Finally, for the recognition of the specific traffic sign, a technique based on extraction of signs characteristics and thresholding is adopted. Implemented on DSP platform the system recognizes traffic signs in less than 150 ms at a distance of about 15 meters from 640x480-pixel acquired images. Tests carried out with hundreds of images show a detection and recognition rate of about 93%.

Assessment of traffic noise levels in urban areas using different soft computing techniques.

PubMed

Tomić, J; Bogojević, N; Pljakić, M; Šumarac-Pavlović, D

2016-10-01

Available traffic noise prediction models are usually based on regression analysis of experimental data, and this paper presents the application of soft computing techniques in traffic noise prediction. Two mathematical models are proposed and their predictions are compared to data collected by traffic noise monitoring in urban areas, as well as to predictions of commonly used traffic noise models. The results show that application of evolutionary algorithms and neural networks may improve process of development, as well as accuracy of traffic noise prediction.

A Police and Insurance Joint Management System Based on High Precision BDS/GPS Positioning

PubMed Central

Zuo, Wenwei; Guo, Chi; Liu, Jingnan; Peng, Xuan; Yang, Min

2018-01-01

Car ownership in China reached 194 million vehicles at the end of 2016. The traffic congestion index (TCI) exceeds 2.0 during rush hour in some cities. Inefficient processing for minor traffic accidents is considered to be one of the leading causes for road traffic jams. Meanwhile, the process after an accident is quite troublesome. The main reason is that it is almost always impossible to get the complete chain of evidence when the accident happens. Accordingly, a police and insurance joint management system is developed which is based on high precision BeiDou Navigation Satellite System (BDS)/Global Positioning System (GPS) positioning to process traffic accidents. First of all, an intelligent vehicle rearview mirror terminal is developed. The terminal applies a commonly used consumer electronic device with single frequency navigation. Based on the high precision BDS/GPS positioning algorithm, its accuracy can reach sub-meter level in the urban areas. More specifically, a kernel driver is built to realize the high precision positioning algorithm in an Android HAL layer. Thus the third-party application developers can call the general location Application Programming Interface (API) of the original standard Global Navigation Satellite System (GNSS) to get high precision positioning results. Therefore, the terminal can provide lane level positioning service for car users. Next, a remote traffic accident processing platform is built to provide big data analysis and management. According to the big data analysis of information collected by BDS high precision intelligent sense service, vehicle behaviors can be obtained. The platform can also automatically match and screen the data that uploads after an accident to achieve accurate reproduction of the scene. Thus, it helps traffic police and insurance personnel to complete remote responsibility identification and survey for the accident. Thirdly, a rapid processing flow is established in this article to meet the requirements to quickly handle traffic accidents. The traffic police can remotely identify accident responsibility and the insurance personnel can remotely survey an accident. Moreover, the police and insurance joint management system has been carried out in Wuhan, Central China’s Hubei Province, and Wuxi, Eastern China’s Jiangsu Province. In a word, a system is developed to obtain and analyze multisource data including precise positioning and visual information, and a solution is proposed for efficient processing of traffic accidents. PMID:29320406

A Police and Insurance Joint Management System Based on High Precision BDS/GPS Positioning.

PubMed

Zuo, Wenwei; Guo, Chi; Liu, Jingnan; Peng, Xuan; Yang, Min

2018-01-10

Car ownership in China reached 194 million vehicles at the end of 2016. The traffic congestion index (TCI) exceeds 2.0 during rush hour in some cities. Inefficient processing for minor traffic accidents is considered to be one of the leading causes for road traffic jams. Meanwhile, the process after an accident is quite troublesome. The main reason is that it is almost always impossible to get the complete chain of evidence when the accident happens. Accordingly, a police and insurance joint management system is developed which is based on high precision BeiDou Navigation Satellite System (BDS)/Global Positioning System (GPS) positioning to process traffic accidents. First of all, an intelligent vehicle rearview mirror terminal is developed. The terminal applies a commonly used consumer electronic device with single frequency navigation. Based on the high precision BDS/GPS positioning algorithm, its accuracy can reach sub-meter level in the urban areas. More specifically, a kernel driver is built to realize the high precision positioning algorithm in an Android HAL layer. Thus the third-party application developers can call the general location Application Programming Interface (API) of the original standard Global Navigation Satellite System (GNSS) to get high precision positioning results. Therefore, the terminal can provide lane level positioning service for car users. Next, a remote traffic accident processing platform is built to provide big data analysis and management. According to the big data analysis of information collected by BDS high precision intelligent sense service, vehicle behaviors can be obtained. The platform can also automatically match and screen the data that uploads after an accident to achieve accurate reproduction of the scene. Thus, it helps traffic police and insurance personnel to complete remote responsibility identification and survey for the accident. Thirdly, a rapid processing flow is established in this article to meet the requirements to quickly handle traffic accidents. The traffic police can remotely identify accident responsibility and the insurance personnel can remotely survey an accident. Moreover, the police and insurance joint management system has been carried out in Wuhan, Central China's Hubei Province, and Wuxi, Eastern China's Jiangsu Province. In a word, a system is developed to obtain and analyze multisource data including precise positioning and visual information, and a solution is proposed for efficient processing of traffic accidents.

A new cellular automata model of traffic flow with negative exponential weighted look-ahead potential

NASA Astrophysics Data System (ADS)

Ma, Xiao; Zheng, Wei-Fan; Jiang, Bao-Shan; Zhang, Ji-Ye

2016-10-01

With the development of traffic systems, some issues such as traffic jams become more and more serious. Efficient traffic flow theory is needed to guide the overall controlling, organizing and management of traffic systems. On the basis of the cellular automata model and the traffic flow model with look-ahead potential, a new cellular automata traffic flow model with negative exponential weighted look-ahead potential is presented in this paper. By introducing the negative exponential weighting coefficient into the look-ahead potential and endowing the potential of vehicles closer to the driver with a greater coefficient, the modeling process is more suitable for the driver’s random decision-making process which is based on the traffic environment that the driver is facing. The fundamental diagrams for different weighting parameters are obtained by using numerical simulations which show that the negative exponential weighting coefficient has an obvious effect on high density traffic flux. The complex high density non-linear traffic behavior is also reproduced by numerical simulations. Project supported by the National Natural Science Foundation of China (Grant Nos. 11572264, 11172247, 11402214, and 61373009).

Efficient eNB inter-communication scheme in converged mobile and NG-PON2 system

NASA Astrophysics Data System (ADS)

Xiao, Simiao; Sun, Xiao; Zhang, Kaibin

2016-02-01

In LTE, a new X2-interface is defined to facilitate direct communication between neighboring eNBs. Since LTE is an all-IP network, the X2-interface traffic currently needs to be routed and transponded in L3 at the edge router by IP addressing. As mobile data increases, it is a promising trend to backhaul mobile services based on PON. In this paper, an effective approach for eNB inter-communication over TWDM-PON is proposed. By associating the IP address of eNB and the MAC address of ONU, the "inter-eNB communication in L3" can be mapped into "inter-ONU communication in L2" and transponded via the protocol of PON at the OLT. Thus, fast and cost-effective eNB inter-communication can be realized based on TWDM-PON within one wavelength channel and between different wavelength channels. The increasing data traffic pressure to the core network can also be alleviated.

Edge Detection Method Based on Neural Networks for COMS MI Images

NASA Astrophysics Data System (ADS)

Lee, Jin-Ho; Park, Eun-Bin; Woo, Sun-Hee

2016-12-01

Communication, Ocean And Meteorological Satellite (COMS) Meteorological Imager (MI) images are processed for radiometric and geometric correction from raw image data. When intermediate image data are matched and compared with reference landmark images in the geometrical correction process, various techniques for edge detection can be applied. It is essential to have a precise and correct edged image in this process, since its matching with the reference is directly related to the accuracy of the ground station output images. An edge detection method based on neural networks is applied for the ground processing of MI images for obtaining sharp edges in the correct positions. The simulation results are analyzed and characterized by comparing them with the results of conventional methods, such as Sobel and Canny filters.

Simulation of Automatic Incidents Detection Algorithm on the Transport Network

ERIC Educational Resources Information Center

Nikolaev, Andrey B.; Sapego, Yuliya S.; Jakubovich, Anatolij N.; Berner, Leonid I.; Ivakhnenko, Andrey M.

2016-01-01

Management of traffic incident is a functional part of the whole approach to solving traffic problems in the framework of intelligent transport systems. Development of an effective process of traffic incident management is an important part of the transport system. In this research, it's suggested algorithm based on fuzzy logic to detect traffic…

49 CFR 393.26 - Requirements for reflectors.

Code of Federal Regulations, 2014 CFR

2014-10-01

..., shall meet the applicable requirements of FMVSS No. 108 in effect on the date of manufacture of the...) Designs do not resemble traffic control signs, lights, or devices, except that straight edge striping...

49 CFR 393.26 - Requirements for reflectors.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., shall meet the applicable requirements of FMVSS No. 108 in effect on the date of manufacture of the...) Designs do not resemble traffic control signs, lights, or devices, except that straight edge striping...

49 CFR 393.26 - Requirements for reflectors.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., shall meet the applicable requirements of FMVSS No. 108 in effect on the date of manufacture of the...) Designs do not resemble traffic control signs, lights, or devices, except that straight edge striping...

49 CFR 393.26 - Requirements for reflectors.

Code of Federal Regulations, 2012 CFR

2012-10-01

..., shall meet the applicable requirements of FMVSS No. 108 in effect on the date of manufacture of the...) Designs do not resemble traffic control signs, lights, or devices, except that straight edge striping...

An extended car-following model considering the acceleration derivative in some typical traffic environments

NASA Astrophysics Data System (ADS)

Zhou, Tong; Chen, Dong; Liu, Weining

2018-03-01

Based on the full velocity difference and acceleration car-following model, an extended car-following model is proposed by considering the vehicle’s acceleration derivative. The stability condition is given by applying the control theory. Considering some typical traffic environments, the results of theoretical analysis and numerical simulation show the extended model has a more actual acceleration of string vehicles than that of the previous models in starting process, stopping process and sudden brake. Meanwhile, the traffic jams more easily occur when the coefficient of vehicle’s acceleration derivative increases, which is presented by space-time evolution. The results confirm that the vehicle’s acceleration derivative plays an important role in the traffic jamming transition and the evolution of traffic congestion.

[The characteristics of computer simulation of traffic accidents].

PubMed

Zou, Dong-Hua; Liu, Ning-Guo; Chen, Jian-Guo; Jin, Xian-Long; Zhang, Xiao-Yun; Zhang, Jian-Hua; Chen, Yi-Jiu

2008-12-01

To reconstruct the collision process of traffic accident and the injury mode of the victim by computer simulation technology in forensic assessment of traffic accident. Forty actual accidents were reconstructed by stimulation software and high performance computer based on analysis of the trace evidences at the scene, damage of the vehicles and injury of the victims, with 2 cases discussed in details. The reconstruction correlated very well in 28 cases, well in 9 cases, and suboptimal in 3 cases with the above parameters. Accurate reconstruction of the accident would be helpful for assessment of the injury mechanism of the victims. Reconstruction of the collision process of traffic accident and the injury mechanism of the victim by computer simulation is useful in traffic accident assessment.

A new simulation system of traffic flow based on cellular automata principle

NASA Astrophysics Data System (ADS)

Shan, Junru

2017-05-01

Traffic flow is a complex system of multi-behavior so it is difficult to give a specific mathematical equation to express it. With the rapid development of computer technology, it is an important method to study the complex traffic behavior by simulating the interaction mechanism between vehicles and reproduce complex traffic behavior. Using the preset of multiple operating rules, cellular automata is a kind of power system which has discrete time and space. It can be a good simulation of the real traffic process and a good way to solve the traffic problems.

Calibrated Multi-Temporal Edge Images for City Infrastructure Growth Assessment and Prediction

NASA Astrophysics Data System (ADS)

Al-Ruzouq, R.; Shanableh, A.; Boharoon, Z.; Khalil, M.

2018-03-01

Urban Growth or urbanization can be defined as the gradual process of city's population growth and infrastructure development. It is typically demonstrated by the expansion of a city's infrastructure, mainly development of its roads and buildings. Uncontrolled urban Growth in cities has been responsible for several problems that include living environment, drinking water, noise and air pollution, waste management, traffic congestion and hydraulic processes. Accurate identification of urban growth is of great importance for urban planning and water/land management. Recent advances in satellite imagery, in terms of improved spatial and temporal resolutions, allows for efficient identification of change patterns and the prediction of built-up areas. In this study, two approaches were adapted to quantify and assess the pattern of urbanization, in Ajman City at UAE, during the last three decades. The first approach relies on image processing techniques and multi-temporal Landsat satellite images with ground resolution varying between 15 to 60 meters. In this approach, the derived edge images (roads and buildings) were used as the basis of change detection. The second approach relies on digitizing features from high-resolution images captured at different years. The latest approach was adopted, as a reference and ground truth, to calibrate extracted edges from Landsat images. It has been found that urbanized area almost increased by 12 folds during the period 1975-2015 where the growth of buildings and roads were almost parallel until 2005 when the roads spatial expansion witnessed a steep increase due to the vertical expansion of the City. Extracted Edges features, were successfully used for change detection and quantification in term of buildings and roads.

Variable speed limit strategies analysis with mesoscopic traffic flow model based on complex networks

NASA Astrophysics Data System (ADS)

Li, Shu-Bin; Cao, Dan-Ni; Dang, Wen-Xiu; Zhang, Lin

As a new cross-discipline, the complexity science has penetrated into every field of economy and society. With the arrival of big data, the research of the complexity science has reached its summit again. In recent years, it offers a new perspective for traffic control by using complex networks theory. The interaction course of various kinds of information in traffic system forms a huge complex system. A new mesoscopic traffic flow model is improved with variable speed limit (VSL), and the simulation process is designed, which is based on the complex networks theory combined with the proposed model. This paper studies effect of VSL on the dynamic traffic flow, and then analyzes the optimal control strategy of VSL in different network topologies. The conclusion of this research is meaningful to put forward some reasonable transportation plan and develop effective traffic management and control measures to help the department of traffic management.

Developing a Web-Based Advisory Expert System for Implementing Traffic Calming Strategies

PubMed Central

Falamarzi, Amir; Borhan, Muhamad Nazri; Rahmat, Riza Atiq O. K.

2014-01-01

Lack of traffic safety has become a serious issue in residential areas. In this paper, a web-based advisory expert system for the purpose of applying traffic calming strategies on residential streets is described because there currently lacks a structured framework for the implementation of such strategies. Developing an expert system can assist and advise engineers for dealing with traffic safety problems. This expert system is developed to fill the gap between the traffic safety experts and people who seek to employ traffic calming strategies including decision makers, engineers, and students. In order to build the expert system, examining sources related to traffic calming studies as well as interviewing with domain experts have been carried out. The system includes above 150 rules and 200 images for different types of measures. The system has three main functions including classifying traffic calming measures, prioritizing traffic calming strategies, and presenting solutions for different traffic safety problems. Verifying, validating processes, and comparing the system with similar works have shown that the system is consistent and acceptable for practical uses. Finally, some recommendations for improving the system are presented. PMID:25276861

Developing a web-based advisory expert system for implementing traffic calming strategies.

PubMed

Falamarzi, Amir; Borhan, Muhamad Nazri; Rahmat, Riza Atiq O K

2014-01-01

Lack of traffic safety has become a serious issue in residential areas. In this paper, a web-based advisory expert system for the purpose of applying traffic calming strategies on residential streets is described because there currently lacks a structured framework for the implementation of such strategies. Developing an expert system can assist and advise engineers for dealing with traffic safety problems. This expert system is developed to fill the gap between the traffic safety experts and people who seek to employ traffic calming strategies including decision makers, engineers, and students. In order to build the expert system, examining sources related to traffic calming studies as well as interviewing with domain experts have been carried out. The system includes above 150 rules and 200 images for different types of measures. The system has three main functions including classifying traffic calming measures, prioritizing traffic calming strategies, and presenting solutions for different traffic safety problems. Verifying, validating processes, and comparing the system with similar works have shown that the system is consistent and acceptable for practical uses. Finally, some recommendations for improving the system are presented.

Tripped rollover (phase A).

DOT National Transportation Integrated Search

2009-08-01

The Federal Highway Administration (FHWA) has expressed interest in learning more about pavement drop-offs at the edge of roadways and their relationship with the roll stability of heavy vehicles. Statistics kept by the National Highway Traffic Safet...

Estimating Cumulative Traffic Loads, Final Report for Phase 1

DOT National Transportation Integrated Search

2000-07-01

The knowledge of traffic loads is a prerequisite for the pavement analysis process, especially for the development of load-related distress prediction models. Furthermore, the emerging mechanistically based pavement performance models and pavement de...

Traffic safety program for school children through safe action and safe condition

NASA Astrophysics Data System (ADS)

Yulianto, Budi; Setiono, Mahmudah, Amirotul Musthofiah Hidayah; Santoso, Anjar Budi

2017-06-01

The facts indicate that the rights of pedestrians is on the wane. Many motorists are unwilling to provide a space for pedestrians, even when they want to cross the road at zebra-cross facility. The data of traffic accident in Surakarta City showed that 7.0% of accident victims in 2014 to 2015 were children aged 5-15 or the group of school-aged children. In general, the location of schools is on the edge of the road where a lot of vehicles run at high speed. Hence, it is very dangerous for the school children to cross the road. Pertaining to this issue, the Department of Transportation implements a program named School Safety Zone (ZoSS). ZoSS is a time-dependent speed control zone consisting of road markings, traffic signs, optional traffic signals, and rumble strips. The objective of this study was to evaluate the effectiveness of the ZoSS based on the perception of the users, including the students, teachers, parents, and community. This study was conducted through a series of activities including the distribution of questionnaire to obtain the road users' perceptions. The results showed that most of the respondents understood the meaning, aim, and benefit of ZoSS. However, it also found that traffic sign and method of cross the road (Four-T) was not recognized appropriately by the respondents. ZoSS program was generally ineffective since the pedestrians felt unsafe to cross the road due to the high-speed vehicles.

An Experimental Exploration of the Impact of Network-Level Packet Loss on Network Intrusion Detection

DTIC Science & Technology

2015-08-01

Experimental environment 5 Table 1 Hardware specifications Name Manufacture Model CPU Memory Hard Drive IP Address Bilbo Dell PowerEdge R610 Intel...10 we replayed the same hour of network traffic from the CDX 20093 that we used in our theoretical2 exploration to show the impact of our packet... replay the traffic at arbitrary speeds. Table 3 lists the speed multiplier that we used and the packet loss we observed. Table 3 Network packet loss

A sensemaking perspective on framing the mental picture of air traffic controllers.

PubMed

Malakis, Stathis; Kontogiannis, Tom

2013-03-01

It has long been recognized that controller strategies are based on a 'mental picture' or representation of traffic situations. Earlier studies indicated that controllers tend to maintain a selective representation of traffic flows based on a few salient traffic features that point out to interesting events (e.g., potential conflicts). A field study is presented in this paper that examines salient features or 'knowledge variables' that constitute the building blocks of controller mental pictures. Verbal reports from participants, a field experiment and observations of real-life scenarios provided insights into the cognitive processes that shape and reframe the mental pictures of controllers. Several cognitive processes (i.e., problem detection, elaboration, reframing and replanning) have been explored within a particular framework of sensemaking stemming from the data/frame theory (Klein et al., 2007). Cognitive maps, representing standard and non-standard air traffic flows, emerged as an explanatory framework for making sense of traffic patterns and for reframing mental pictures. The data/frame theory proved to be a useful theoretical tool for investigating complex cognitive phenomena. The findings of the study have implications for the design of training curricula and decision support systems in air traffic control systems. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Surface Hold Advisor Using Critical Sections

NASA Technical Reports Server (NTRS)

Law, Caleb Hoi Kei (Inventor); Hsiao, Thomas Kun-Lung (Inventor); Mittler, Nathan C. (Inventor); Couluris, George J. (Inventor)

2013-01-01

The Surface Hold Advisor Using Critical Sections is a system and method for providing hold advisories to surface controllers to prevent gridlock and resolve crossing and merging conflicts among vehicles traversing a vertex-edge graph representing a surface traffic network on an airport surface. The Advisor performs pair-wise comparisons of current position and projected path of each vehicle with other surface vehicles to detect conflicts, determine critical sections, and provide hold advisories to traffic controllers recommending vehicles stop at entry points to protected zones around identified critical sections. A critical section defines a segment of the vertex-edge graph where vehicles are in crossing or merging or opposite direction gridlock contention. The Advisor detects critical sections without reference to scheduled, projected or required times along assigned vehicle paths, and generates hold advisories to prevent conflicts without requiring network path direction-of-movement rules and without requiring rerouting, rescheduling or other network optimization solutions.

An investigation into incident duration forecasting for FleetForward

DOT National Transportation Integrated Search

2000-08-01

Traffic condition forecasting is the process of estimating future traffic conditions based on current and archived data. Real-time forecasting is becoming an important tool in Intelligent Transportation Systems (ITS). This type of forecasting allows ...

Traffic Aware Planner for Cockpit-Based Trajectory Optimization

NASA Technical Reports Server (NTRS)

Woods, Sharon E.; Vivona, Robert A.; Henderson, Jeffrey; Wing, David J.; Burke, Kelly A.

2016-01-01

The Traffic Aware Planner (TAP) software application is a cockpit-based advisory tool designed to be hosted on an Electronic Flight Bag and to enable and test the NASA concept of Traffic Aware Strategic Aircrew Requests (TASAR). The TASAR concept provides pilots with optimized route changes (including altitude) that reduce fuel burn and/or flight time, avoid interactions with known traffic, weather and restricted airspace, and may be used by the pilots to request a route and/or altitude change from Air Traffic Control. Developed using an iterative process, TAP's latest improvements include human-machine interface design upgrades and added functionality based on the results of human-in-the-loop simulation experiments and flight trials. Architectural improvements have been implemented to prepare the system for operational-use trials with partner commercial airlines. Future iterations will enhance coordination with airline dispatch and add functionality to improve the acceptability of TAP-generated route-change requests to pilots, dispatchers, and air traffic controllers.

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.

Multi-agent fare optimization model of two modes problem and its analysis based on edge of chaos

NASA Astrophysics Data System (ADS)

Li, Xue-yan; Li, Xue-mei; Li, Xue-wei; Qiu, He-ting

2017-03-01

This paper proposes a new framework of fare optimization & game model for studying the competition between two travel modes (high speed railway and civil aviation) in which passengers' group behavior is taken into consideration. The small-world network is introduced to construct the multi-agent model of passengers' travel mode choice. The cumulative prospect theory is adopted to depict passengers' bounded rationality, the heterogeneity of passengers' reference point is depicted using the idea of group emotion computing. The conceptions of "Langton parameter" and "evolution entropy" in the theory of "edge of chaos" are introduced to create passengers' "decision coefficient" and "evolution entropy of travel mode choice" which are used to quantify passengers' group behavior. The numerical simulation and the analysis of passengers' behavior show that (1) the new model inherits the features of traditional model well and the idea of self-organizing traffic flow evolution fully embodies passengers' bounded rationality, (2) compared with the traditional model (logit model), when passengers are in the "edge of chaos" state, the total profit of the transportation system is higher.

Wyoming Department of Transportation (WYDOT) road condition reporting application for weather responsive traffic management.

DOT National Transportation Integrated Search

2015-10-01

Federal Highway Administrations (FHWA) Road Weather Management Program (RWMP) strives to promote the development and implementation of cutting-edge techniques for maintaining safety, mobility, and productivity of roadways during adverse weather co...

South Dakota Department of Transportation (SDDOT) regional traveler information system for weather responsive traffic management.

DOT National Transportation Integrated Search

2015-11-01

Federal Highway Administrations (FHWA) Road Weather Management Program (RWMP) strives to promote the development and implementation of cutting-edge techniques for maintaining safety, mobility, and productivity of roadways during adverse weather co...

Evidence of Long Range Dependence and Self-similarity in Urban Traffic Systems

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

Thakur, Gautam S; Helmy, Ahmed; Hui, Pan

2015-01-01

Transportation simulation technologies should accurately model traffic demand, distribution, and assignment parame- ters for urban environment simulation. These three param- eters significantly impact transportation engineering bench- mark process, are also critical in realizing realistic traffic modeling situations. In this paper, we model and charac- terize traffic density distribution of thousands of locations around the world. The traffic densities are generated from millions of images collected over several years and processed using computer vision techniques. The resulting traffic den- sity distribution time series are then analyzed. It is found using the goodness-of-fit test that the traffic density dis- tributions follows heavy-tailmore » models such as Log-gamma, Log-logistic, and Weibull in over 90% of analyzed locations. Moreover, a heavy-tail gives rise to long-range dependence and self-similarity, which we studied by estimating the Hurst exponent (H). Our analysis based on seven different Hurst estimators strongly indicate that the traffic distribution pat- terns are stochastically self-similar (0.5 H 1.0). We believe this is an important finding that will influence the design and development of the next generation traffic simu- lation techniques and also aid in accurately modeling traffic engineering of urban systems. In addition, it shall provide a much needed input for the development of smart cities.« less

The crack detection algorithm of pavement image based on edge information

NASA Astrophysics Data System (ADS)

Yang, Chunde; Geng, Mingyue

2018-05-01

As the images of pavement cracks are affected by a large amount of complicated noises, such as uneven illumination and water stains, the detected cracks are discontinuous and the main body information at the edge of the cracks is easily lost. In order to solve the problem, a crack detection algorithm in pavement image based on edge information is proposed. Firstly, the image is pre-processed by the nonlinear gray-scale transform function and reconstruction filter to enhance the linear characteristic of the crack. At the same time, an adaptive thresholding method is designed to coarsely extract the cracks edge according to the gray-scale gradient feature and obtain the crack gradient information map. Secondly, the candidate edge points are obtained according to the gradient information, and the edge is detected based on the single pixel percolation processing, which is improved by using the local difference between pixels in the fixed region. Finally, complete crack is obtained by filling the crack edge. Experimental results show that the proposed method can accurately detect pavement cracks and preserve edge information.

Non-Seismology Seismology: Using QuakeCatchers to Analyze the Frequency of Bridge Vibrations

NASA Astrophysics Data System (ADS)

Courtier, A. M.; Constantin, C.; Wilson, C. F.

2013-12-01

We conducted an experiment to test the feasibility of measuring seismic waves generated by traffic near James Madison University. We used QuakeCatcher seismometers (originally designed for passive seismic measurement) to measure vibrations associated with traffic on a wooden bridge as well as a nearby concrete bridge. This experiment was a signal processing exercise for a student research project and did not draw any conclusions regarding bridge safety or security. The experiment consisted of two temporary measurement stations comprised of a laptop computer and a QuakeCatcher - a small seismometer that plugs directly into the laptop via a USB cable. The QuakeCatcher was taped to the ground at the edge of the bridge to achieve good coupling, and vibrational events were triggered repeatedly with a control vehicle to accumulate a consistent dataset of the bridge response. For the wooden bridge, the resulting 'seismograms' were converted to Seismic Analysis Code (SAC) format and analyzed in MATLAB. The concrete bridge did not generate vibrations significant enough to trigger the recording mechanism on the QuakeCatchers. We will present an overview of the experimental design and frequency content of the traffic patterns, as well as a discussion of the instructional benefits of using the QuakeCatcher sensors in this non-traditional setting.

Development of traffic data input resources for the mechanistic empirical pavement design process.

DOT National Transportation Integrated Search

2011-12-12

The Mechanistic-Empirical Pavement Design Guide (MEPDG) for New and Rehabilitated Pavement Structures uses : nationally based data traffic inputs and recommends that state DOTs develop their own site-specific and regional : values. To support the MEP...

Dynamics of traffic flow with real-time traffic information

NASA Astrophysics Data System (ADS)

Yokoya, Yasushi

2004-01-01

We studied dynamics of traffic flow with real-time information provided. Provision of the real-time traffic information based on advancements in telecommunication technology is expected to facilitate the efficient utilization of available road capacity. This system has a potentiality of not only engineering for road usage but also the science of complexity series. In the system, the information plays a role of feedback connecting microscopic and macroscopic phenomena beyond the hierarchical structure of statistical physics. In this paper, we tried to clarify how the information works in a network of traffic flow from the perspective of statistical physics. The dynamical feature of the traffic flow is abstracted by a contrastive study between the nonequilibrium statistical physics and a computer simulation based on cellular automaton. We found that the information disrupts the local equilibrium of traffic flow by a characteristic dissipation process due to interaction between the information and individual vehicles. The dissipative structure was observed in the time evolution of traffic flow driven far from equilibrium as a consequence of the breakdown of the local-equilibrium hypothesis.

Multi-edge X-ray absorption spectroscopy study of road dust samples from a traffic area of Venice using stoichiometric and environmental references

NASA Astrophysics Data System (ADS)

Valotto, Gabrio; Cattaruzza, Elti; Bardelli, Fabrizio

2017-02-01

The appropriate selection of representative pure compounds to be used as reference is a crucial step for successful analysis of X-ray absorption near edge spectroscopy (XANES) data, and it is often not a trivial task. This is particularly true when complex environmental matrices are investigated, being their elemental speciation a priori unknown. In this paper, an investigation on the speciation of Cu, Zn, and Sb based on the use of conventional (stoichiometric compounds) and non-conventional (environmental samples or relevant certified materials) references is explored. This method can be useful in when the effectiveness of XANES analysis is limited because of the difficulty in obtaining a set of references sufficiently representative of the investigated samples. Road dust samples collected along the bridge connecting Venice to the mainland were used to show the potentialities and the limits of this approach.

Lunar-edge based on-orbit modulation transfer function (MTF) measurement

NASA Astrophysics Data System (ADS)

Cheng, Ying; Yi, Hongwei; Liu, Xinlong

2017-10-01

Modulation transfer function (MTF) is an important parameter for image quality evaluation of on-orbit optical image systems. Various methods have been proposed to determine the MTF of an imaging system which are based on images containing point, pulse and edge features. In this paper, the edge of the moon can be used as a high contrast target to measure on-orbit MTF of image systems based on knife-edge methods. The proposed method is an extension of the ISO 12233 Slanted-edge Spatial Frequency Response test, except that the shape of the edge is a circular arc instead of a straight line. In order to get more accurate edge locations and then obtain a more authentic edge spread function (ESF), we choose circular fitting method based on least square to fit lunar edge in sub-pixel edge detection process. At last, simulation results show that the MTF value at Nyquist frequency calculated using our lunar edge method is reliable and accurate with error less than 2% comparing with theoretical MTF value.

Detection and 3D reconstruction of traffic signs from multiple view color images

NASA Astrophysics Data System (ADS)

Soheilian, Bahman; Paparoditis, Nicolas; Vallet, Bruno

2013-03-01

3D reconstruction of traffic signs is of great interest in many applications such as image-based localization and navigation. In order to reflect the reality, the reconstruction process should meet both accuracy and precision. In order to reach such a valid reconstruction from calibrated multi-view images, accurate and precise extraction of signs in every individual view is a must. This paper presents first an automatic pipeline for identifying and extracting the silhouette of signs in every individual image. Then, a multi-view constrained 3D reconstruction algorithm provides an optimum 3D silhouette for the detected signs. The first step called detection, tackles with a color-based segmentation to generate ROIs (Region of Interests) in image. The shape of every ROI is estimated by fitting an ellipse, a quadrilateral or a triangle to edge points. A ROI is rejected if none of the three shapes can be fitted sufficiently precisely. Thanks to the estimated shape the remained candidates ROIs are rectified to remove the perspective distortion and then matched with a set of reference signs using textural information. Poor matches are rejected and the types of remained ones are identified. The output of the detection algorithm is a set of identified road signs whose silhouette in image plane is represented by and ellipse, a quadrilateral or a triangle. The 3D reconstruction process is based on a hypothesis generation and verification. Hypotheses are generated by a stereo matching approach taking into account epipolar geometry and also the similarity of the categories. The hypotheses that are plausibly correspond to the same 3D road sign are identified and grouped during this process. Finally, all the hypotheses of the same group are merged to generate a unique 3D road sign by a multi-view algorithm integrating a priori knowledges about 3D shape of road signs as constraints. The algorithm is assessed on real and synthetic images and reached and average accuracy of 3.5cm for position and 4.5° for orientation.

Restoration of Motion-Blurred Image Based on Border Deformation Detection: A Traffic Sign Restoration Model

PubMed Central

Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Wang, Qi; Gao, Jing

2015-01-01

Due to the rapid development of motor vehicle Driver Assistance Systems (DAS), the safety problems associated with automatic driving have become a hot issue in Intelligent Transportation. The traffic sign is one of the most important tools used to reinforce traffic rules. However, traffic sign image degradation based on computer vision is unavoidable during the vehicle movement process. In order to quickly and accurately recognize traffic signs in motion-blurred images in DAS, a new image restoration algorithm based on border deformation detection in the spatial domain is proposed in this paper. The border of a traffic sign is extracted using color information, and then the width of the border is measured in all directions. According to the width measured and the corresponding direction, both the motion direction and scale of the image can be confirmed, and this information can be used to restore the motion-blurred image. Finally, a gray mean grads (GMG) ratio is presented to evaluate the image restoration quality. Compared to the traditional restoration approach which is based on the blind deconvolution method and Lucy-Richardson method, our method can greatly restore motion blurred images and improve the correct recognition rate. Our experiments show that the proposed method is able to restore traffic sign information accurately and efficiently. PMID:25849350

Restoration of motion-blurred image based on border deformation detection: a traffic sign restoration model.

PubMed

Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Wang, Qi; Gao, Jing

2015-01-01

Due to the rapid development of motor vehicle Driver Assistance Systems (DAS), the safety problems associated with automatic driving have become a hot issue in Intelligent Transportation. The traffic sign is one of the most important tools used to reinforce traffic rules. However, traffic sign image degradation based on computer vision is unavoidable during the vehicle movement process. In order to quickly and accurately recognize traffic signs in motion-blurred images in DAS, a new image restoration algorithm based on border deformation detection in the spatial domain is proposed in this paper. The border of a traffic sign is extracted using color information, and then the width of the border is measured in all directions. According to the width measured and the corresponding direction, both the motion direction and scale of the image can be confirmed, and this information can be used to restore the motion-blurred image. Finally, a gray mean grads (GMG) ratio is presented to evaluate the image restoration quality. Compared to the traditional restoration approach which is based on the blind deconvolution method and Lucy-Richardson method, our method can greatly restore motion blurred images and improve the correct recognition rate. Our experiments show that the proposed method is able to restore traffic sign information accurately and efficiently.

Generic Vehicle Speed Models Based On Traffic Simulation: Development and Application (Revision #1)

DOT National Transportation Integrated Search

1994-12-15

The findings of a research project to develop new methods of estimating speeds for inclusion in the Highway Performance Monitoring System (HPMS) Analytical Process are summarized. The paper focuses on the effects of traffic conditions excluding incid...

Neural networks for continuous online learning and control.

PubMed

Choy, Min Chee; Srinivasan, Dipti; Cheu, Ruey Long

2006-11-01

This paper proposes a new hybrid neural network (NN) model that employs a multistage online learning process to solve the distributed control problem with an infinite horizon. Various techniques such as reinforcement learning and evolutionary algorithm are used to design the multistage online learning process. For this paper, the infinite horizon distributed control problem is implemented in the form of real-time distributed traffic signal control for intersections in a large-scale traffic network. The hybrid neural network model is used to design each of the local traffic signal controllers at the respective intersections. As the state of the traffic network changes due to random fluctuation of traffic volumes, the NN-based local controllers will need to adapt to the changing dynamics in order to provide effective traffic signal control and to prevent the traffic network from becoming overcongested. Such a problem is especially challenging if the local controllers are used for an infinite horizon problem where online learning has to take place continuously once the controllers are implemented into the traffic network. A comprehensive simulation model of a section of the Central Business District (CBD) of Singapore has been developed using PARAMICS microscopic simulation program. As the complexity of the simulation increases, results show that the hybrid NN model provides significant improvement in traffic conditions when evaluated against an existing traffic signal control algorithm as well as a new, continuously updated simultaneous perturbation stochastic approximation-based neural network (SPSA-NN). Using the hybrid NN model, the total mean delay of each vehicle has been reduced by 78% and the total mean stoppage time of each vehicle has been reduced by 84% compared to the existing traffic signal control algorithm. This shows the efficacy of the hybrid NN model in solving large-scale traffic signal control problem in a distributed manner. Also, it indicates the possibility of using the hybrid NN model for other applications that are similar in nature as the infinite horizon distributed control problem.

Control of Networked Traffic Flow Distribution - A Stochastic Distribution System Perspective

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

Wang, Hong; Aziz, H M Abdul; Young, Stan

Networked traffic flow is a common scenario for urban transportation, where the distribution of vehicle queues either at controlled intersections or highway segments reflect the smoothness of the traffic flow in the network. At signalized intersections, the traffic queues are controlled by traffic signal control settings and effective traffic lights control would realize both smooth traffic flow and minimize fuel consumption. Funded by the Energy Efficient Mobility Systems (EEMS) program of the Vehicle Technologies Office of the US Department of Energy, we performed a preliminary investigation on the modelling and control framework in context of urban network of signalized intersections.more » In specific, we developed a recursive input-output traffic queueing models. The queue formation can be modeled as a stochastic process where the number of vehicles entering each intersection is a random number. Further, we proposed a preliminary B-Spline stochastic model for a one-way single-lane corridor traffic system based on theory of stochastic distribution control.. It has been shown that the developed stochastic model would provide the optimal probability density function (PDF) of the traffic queueing length as a dynamic function of the traffic signal setting parameters. Based upon such a stochastic distribution model, we have proposed a preliminary closed loop framework on stochastic distribution control for the traffic queueing system to make the traffic queueing length PDF follow a target PDF that potentially realizes the smooth traffic flow distribution in a concerned corridor.« less

Natural fertility and heavy metals in the soil in border areas of Atlantic Forest located in an urban area

NASA Astrophysics Data System (ADS)

Longo, R. M.; Ribeiro, A. I.

2017-12-01

Regina Márcia Longo2, Deborah Regina Mendes2, Admilson Irio Ribeiro31 Part of the project funded by the Foundation of the State of São Paulo Research - Brazil (FAPESP - process 2012 / 14423-8)2 Pontifícal Catholic University of Campinas - Brazil; email: regina.longo@puc-campinas.edu.br 3 Paulista State University (UNESP-Sorocaba - Brazil)Due to the disorderly growth of cities, especially in tropical areas, it is observed that the destruction or fragmentation of natural ecosystems has presented itself as one of the great problems of the present time. The forest fragments, although important for the maintenance of microclimate, genetic variety and species diversity, are increasingly impacted due to the activities that are developed in their environment. The present work had as main objective to quantify the level of natural fertility and the presence of heavy metals in the soil in border areas of a forest remnant located in an urban area in the city of Campinas / SP - Brazil in order to verify possible interferences of the anthropic actions carried out in adjacent areas. Soil composite samples were collected at 40 points equidistant at 200 m along the edge. In the samples were determined the contents of: pH (CaCl2); organic matter (OM); phosphorus (P), potassium (K), calcium (Ca) and magnesium (Mg), Cation Exchange Capacity (CEC), base sum (SB) and percentage saturation of bases in addition to heavy metals lead (Pb), chromium (Cr) and nickel (Ni). The results indicated that the nutritional quality of the soil was adequate for the tropical regions. In relation to micronutrients, high levels of copper, zinc and manganese were observed. Regarding the metals, it was observed that iron was the one that accused the most irregularities along the edge, while the lead had higher indices for all the edges evaluated. In general, the presented results indicated that the forest remnant presents its border areas under external pressures, presenting several factors of degradation as real estate occupation, presence of access roads and traffic of vehicles and people, of the production of sugar cane, fire and deposition of solid waste, or other degradation factor that directly interfere in the areas of the edges of this important remnant of Atlantic Forest. Key words: forest remnants, tropical soils, edge effect

Two-lane traffic-flow model with an exact steady-state solution.

PubMed

Kanai, Masahiro

2010-12-01

We propose a stochastic cellular-automaton model for two-lane traffic flow based on the misanthrope process in one dimension. The misanthrope process is a stochastic process allowing for an exact steady-state solution; hence, we have an exact flow-density diagram for two-lane traffic. In addition, we introduce two parameters that indicate, respectively, driver's driving-lane preference and passing-lane priority. Due to the additional parameters, the model shows a deviation of the density ratio for driving-lane use and a biased lane efficiency in flow. Then, a mean-field approach explicitly describes the asymmetric flow by the hop rates, the driving-lane preference, and the passing-lane priority. Meanwhile, the simulation results are in good agreement with an observational data, and we thus estimate these parameters. We conclude that the proposed model successfully produces two-lane traffic flow particularly with the driving-lane preference and the passing-lane priority.

Self-control of traffic lights and vehicle flows in urban road networks

NASA Astrophysics Data System (ADS)

Lämmer, Stefan; Helbing, Dirk

2008-04-01

Based on fluid-dynamic and many-particle (car-following) simulations of traffic flows in (urban) networks, we study the problem of coordinating incompatible traffic flows at intersections. Inspired by the observation of self-organized oscillations of pedestrian flows at bottlenecks, we propose a self-organization approach to traffic light control. The problem can be treated as a multi-agent problem with interactions between vehicles and traffic lights. Specifically, our approach assumes a priority-based control of traffic lights by the vehicle flows themselves, taking into account short-sighted anticipation of vehicle flows and platoons. The considered local interactions lead to emergent coordination patterns such as 'green waves' and achieve an efficient, decentralized traffic light control. While the proposed self-control adapts flexibly to local flow conditions and often leads to non-cyclical switching patterns with changing service sequences of different traffic flows, an almost periodic service may evolve under certain conditions and suggests the existence of a spontaneous synchronization of traffic lights despite the varying delays due to variable vehicle queues and travel times. The self-organized traffic light control is based on an optimization and a stabilization rule, each of which performs poorly at high utilizations of the road network, while their proper combination reaches a superior performance. The result is a considerable reduction not only in the average travel times, but also of their variation. Similar control approaches could be applied to the coordination of logistic and production processes.

Traffic Sign Recognition with Invariance to Lighting in Dual-Focal Active Camera System

NASA Astrophysics Data System (ADS)

Gu, Yanlei; Panahpour Tehrani, Mehrdad; Yendo, Tomohiro; Fujii, Toshiaki; Tanimoto, Masayuki

In this paper, we present an automatic vision-based traffic sign recognition system, which can detect and classify traffic signs at long distance under different lighting conditions. To realize this purpose, the traffic sign recognition is developed in an originally proposed dual-focal active camera system. In this system, a telephoto camera is equipped as an assistant of a wide angle camera. The telephoto camera can capture a high accuracy image for an object of interest in the view field of the wide angle camera. The image from the telephoto camera provides enough information for recognition when the accuracy of traffic sign is low from the wide angle camera. In the proposed system, the traffic sign detection and classification are processed separately for different images from the wide angle camera and telephoto camera. Besides, in order to detect traffic sign from complex background in different lighting conditions, we propose a type of color transformation which is invariant to light changing. This color transformation is conducted to highlight the pattern of traffic signs by reducing the complexity of background. Based on the color transformation, a multi-resolution detector with cascade mode is trained and used to locate traffic signs at low resolution in the image from the wide angle camera. After detection, the system actively captures a high accuracy image of each detected traffic sign by controlling the direction and exposure time of the telephoto camera based on the information from the wide angle camera. Moreover, in classification, a hierarchical classifier is constructed and used to recognize the detected traffic signs in the high accuracy image from the telephoto camera. Finally, based on the proposed system, a set of experiments in the domain of traffic sign recognition is presented. The experimental results demonstrate that the proposed system can effectively recognize traffic signs at low resolution in different lighting conditions.

Integrated optimisation technique based on computer-aided capacity and safety evaluation for managing downstream lane-drop merging area of signalised junctions

NASA Astrophysics Data System (ADS)

Chen, CHAI; Yiik Diew, WONG

2017-02-01

This study provides an integrated strategy, encompassing microscopic simulation, safety assessment, and multi-attribute decision-making, to optimize traffic performance at downstream merging area of signalized intersections. A Fuzzy Cellular Automata (FCA) model is developed to replicate microscopic movement and merging behavior. Based on simulation experiment, the proposed FCA approach is able to provide capacity and safety evaluation of different traffic scenarios. The results are then evaluated through data envelopment analysis (DEA) and analytic hierarchy process (AHP). Optimized geometric layout and control strategies are then suggested for various traffic conditions. An optimal lane-drop distance that is dependent on traffic volume and speed limit can thus be established at the downstream merging area.

Research and design of intelligent distributed traffic signal light control system based on CAN bus

NASA Astrophysics Data System (ADS)

Chen, Yu

2007-12-01

Intelligent distributed traffic signal light control system was designed based on technologies of infrared, CAN bus, single chip microprocessor (SCM), etc. The traffic flow signal is processed with the core of SCM AT89C51. At the same time, the SCM controls the CAN bus controller SJA1000/transceiver PCA82C250 to build a CAN bus communication system to transmit data. Moreover, up PC realizes to connect and communicate with SCM through USBCAN chip PDIUSBD12. The distributed traffic signal light control system with three control styles of Vehicle flux, remote and PC is designed. This paper introduces the system composition method and parts of hardware/software design in detail.

Using Inspiration from Synaptic Plasticity Rules to Optimize Traffic Flow in Distributed Engineered Networks.

PubMed

Suen, Jonathan Y; Navlakha, Saket

2017-05-01

Controlling the flow and routing of data is a fundamental problem in many distributed networks, including transportation systems, integrated circuits, and the Internet. In the brain, synaptic plasticity rules have been discovered that regulate network activity in response to environmental inputs, which enable circuits to be stable yet flexible. Here, we develop a new neuro-inspired model for network flow control that depends only on modifying edge weights in an activity-dependent manner. We show how two fundamental plasticity rules, long-term potentiation and long-term depression, can be cast as a distributed gradient descent algorithm for regulating traffic flow in engineered networks. We then characterize, both by simulation and analytically, how different forms of edge-weight-update rules affect network routing efficiency and robustness. We find a close correspondence between certain classes of synaptic weight update rules derived experimentally in the brain and rules commonly used in engineering, suggesting common principles to both.

Edge-filter technique and dominant frequency analysis for high-speed railway monitoring with fiber Bragg gratings

NASA Astrophysics Data System (ADS)

Kouroussis, Georges; Kinet, Damien; Mendoza, Edgar; Dupuy, Julien; Moeyaert, Véronique; Caucheteur, Christophe

2016-07-01

Structural health and operation monitoring are of growing interest in the development of railway networks. Conventional systems of infrastructure monitoring already exist (e.g. axle counters, track circuits) but present some drawbacks. Alternative solutions are therefore studied and developed. In this field, optical fiber sensors, and more particularly fiber Bragg grating (FBG) sensors, are particularly relevant due to their immunity to electromagnetic fields and simple wavelength-division-multiplexing capability. Field trials conducted up to now have demonstrated that FBG sensors provide useful information about train composition, positioning, speed, acceleration and weigh-in-motion estimations. Nevertheless, for practical deployment, cost-effectiveness should be ensured, specifically at the interrogator side that has also to be fast (>1 kHz repetition rate), accurate (∼1 pm wavelength shift) and reliable. To reach this objective, we propose in this paper to associate a low cost and high-speed interrogator coupled with an adequate signal-processing algorithm to dynamically monitor cascaded wavelength-multiplexed FBGs and to accurately capture the parameters of interest for railway traffic monitoring. This method has been field-tested with a Redondo Optics Inc. interrogator based on the well-known edge-filter demodulation technique. To determine the train speed from the raw data, a dominant frequency analysis has been implemented. Using this original method, we show that we can retrieve the speed of the trains, even when the time history strain signature is strongly affected by the measurement noise. The results are assessed by complimentary data obtained from a spectrometer-based FBG interrogator.

Price of anarchy on heterogeneous traffic-flow networks

NASA Astrophysics Data System (ADS)

Rose, A.; O'Dea, R.; Hopcraft, K. I.

2016-09-01

The efficiency of routing traffic through a network, comprising nodes connected by links whose cost of traversal is either fixed or varies in proportion to volume of usage, can be measured by the "price of anarchy." This is the ratio of the cost incurred by agents who act to minimize their individual expenditure to the optimal cost borne by the entire system. As the total traffic load and the network variability—parameterized by the proportion of variable-cost links in the network—changes, the behaviors that the system presents can be understood with the introduction of a network of simpler structure. This is constructed from classes of nonoverlapping paths connecting source to destination nodes that are characterized by the number of variable-cost edges they contain. It is shown that localized peaks in the price of anarchy occur at critical traffic volumes at which it becomes beneficial to exploit ostensibly more expensive paths as the network becomes more congested. Simulation results verifying these findings are presented for the variation of the price of anarchy with the network's size, aspect ratio, variability, and traffic load.

Price of anarchy on heterogeneous traffic-flow networks.

PubMed

Rose, A; O'Dea, R; Hopcraft, K I

2016-09-01

The efficiency of routing traffic through a network, comprising nodes connected by links whose cost of traversal is either fixed or varies in proportion to volume of usage, can be measured by the "price of anarchy." This is the ratio of the cost incurred by agents who act to minimize their individual expenditure to the optimal cost borne by the entire system. As the total traffic load and the network variability-parameterized by the proportion of variable-cost links in the network-changes, the behaviors that the system presents can be understood with the introduction of a network of simpler structure. This is constructed from classes of nonoverlapping paths connecting source to destination nodes that are characterized by the number of variable-cost edges they contain. It is shown that localized peaks in the price of anarchy occur at critical traffic volumes at which it becomes beneficial to exploit ostensibly more expensive paths as the network becomes more congested. Simulation results verifying these findings are presented for the variation of the price of anarchy with the network's size, aspect ratio, variability, and traffic load.

Cognitive process modelling of controllers in en route air traffic control.

PubMed

Inoue, Satoru; Furuta, Kazuo; Nakata, Keiichi; Kanno, Taro; Aoyama, Hisae; Brown, Mark

2012-01-01

In recent years, various efforts have been made in air traffic control (ATC) to maintain traffic safety and efficiency in the face of increasing air traffic demands. ATC is a complex process that depends to a large degree on human capabilities, and so understanding how controllers carry out their tasks is an important issue in the design and development of ATC systems. In particular, the human factor is considered to be a serious problem in ATC safety and has been identified as a causal factor in both major and minor incidents. There is, therefore, a need to analyse the mechanisms by which errors occur due to complex factors and to develop systems that can deal with these errors. From the cognitive process perspective, it is essential that system developers have an understanding of the more complex working processes that involve the cooperative work of multiple controllers. Distributed cognition is a methodological framework for analysing cognitive processes that span multiple actors mediated by technology. In this research, we attempt to analyse and model interactions that take place in en route ATC systems based on distributed cognition. We examine the functional problems in an ATC system from a human factors perspective, and conclude by identifying certain measures by which to address these problems. This research focuses on the analysis of air traffic controllers' tasks for en route ATC and modelling controllers' cognitive processes. This research focuses on an experimental study to gain a better understanding of controllers' cognitive processes in air traffic control. We conducted ethnographic observations and then analysed the data to develop a model of controllers' cognitive process. This analysis revealed that strategic routines are applicable to decision making.

A Cyber-ITS Framework for Massive Traffic Data Analysis Using Cyber Infrastructure

PubMed Central

Fontaine, Michael D.

2013-01-01

Traffic data is commonly collected from widely deployed sensors in urban areas. This brings up a new research topic, data-driven intelligent transportation systems (ITSs), which means to integrate heterogeneous traffic data from different kinds of sensors and apply it for ITS applications. This research, taking into consideration the significant increase in the amount of traffic data and the complexity of data analysis, focuses mainly on the challenge of solving data-intensive and computation-intensive problems. As a solution to the problems, this paper proposes a Cyber-ITS framework to perform data analysis on Cyber Infrastructure (CI), by nature parallel-computing hardware and software systems, in the context of ITS. The techniques of the framework include data representation, domain decomposition, resource allocation, and parallel processing. All these techniques are based on data-driven and application-oriented models and are organized as a component-and-workflow-based model in order to achieve technical interoperability and data reusability. A case study of the Cyber-ITS framework is presented later based on a traffic state estimation application that uses the fusion of massive Sydney Coordinated Adaptive Traffic System (SCATS) data and GPS data. The results prove that the Cyber-ITS-based implementation can achieve a high accuracy rate of traffic state estimation and provide a significant computational speedup for the data fusion by parallel computing. PMID:23766690

A Cyber-ITS framework for massive traffic data analysis using cyber infrastructure.

PubMed

Xia, Yingjie; Hu, Jia; Fontaine, Michael D

2013-01-01

Traffic data is commonly collected from widely deployed sensors in urban areas. This brings up a new research topic, data-driven intelligent transportation systems (ITSs), which means to integrate heterogeneous traffic data from different kinds of sensors and apply it for ITS applications. This research, taking into consideration the significant increase in the amount of traffic data and the complexity of data analysis, focuses mainly on the challenge of solving data-intensive and computation-intensive problems. As a solution to the problems, this paper proposes a Cyber-ITS framework to perform data analysis on Cyber Infrastructure (CI), by nature parallel-computing hardware and software systems, in the context of ITS. The techniques of the framework include data representation, domain decomposition, resource allocation, and parallel processing. All these techniques are based on data-driven and application-oriented models and are organized as a component-and-workflow-based model in order to achieve technical interoperability and data reusability. A case study of the Cyber-ITS framework is presented later based on a traffic state estimation application that uses the fusion of massive Sydney Coordinated Adaptive Traffic System (SCATS) data and GPS data. The results prove that the Cyber-ITS-based implementation can achieve a high accuracy rate of traffic state estimation and provide a significant computational speedup for the data fusion by parallel computing.

In-flight edge response measurements for high-spatial-resolution remote sensing systems

NASA Astrophysics Data System (ADS)

Blonski, Slawomir; Pagnutti, Mary A.; Ryan, Robert; Zanoni, Vickie

2002-09-01

In-flight measurements of spatial resolution were conducted as part of the NASA Scientific Data Purchase Verification and Validation process. Characterization included remote sensing image products with ground sample distance of 1 meter or less, such as those acquired with the panchromatic imager onboard the IKONOS satellite and the airborne ADAR System 5500 multispectral instrument. Final image products were used to evaluate the effects of both the image acquisition system and image post-processing. Spatial resolution was characterized by full width at half maximum of an edge-response-derived line spread function. The edge responses were analyzed using the tilted-edge technique that overcomes the spatial sampling limitations of the digital imaging systems. As an enhancement to existing algorithms, the slope of the edge response and the orientation of the edge target were determined by a single computational process. Adjacent black and white square panels, either painted on a flat surface or deployed as tarps, formed the ground-based edge targets used in the tests. Orientation of the deployable tarps was optimized beforehand, based on simulations of the imaging system. The effects of such factors as acquisition geometry, temporal variability, Modulation Transfer Function compensation, and ground sample distance on spatial resolution were investigated.

A demonstration of expert systems applications in transportation engineering : volume II, TRANZ, a prototype expert system for traffic control in highway work zones.

DOT National Transportation Integrated Search

1988-01-01

The development of a prototype knowledge-based expert system (KBES) for selecting appropriate traffic control strategies and management techniques around highway work zones was initiated. This process was encompassed by the steps that formulate the p...

Research on reducing the edge effect in magnetorheological finishing.

PubMed

Hu, Hao; Dai, Yifan; Peng, Xiaoqiang; Wang, Jianmin

2011-03-20

The edge effect could not be avoided in most optical manufacturing methods based on the theory of computer controlled optical surfacing. The difference between the removal function at the workpiece edge and that inside it is also the primary cause for edge effect in magnetorheological finishing (MRF). The change of physical dimension and removal ratio of the removal function is investigated through experiments. The results demonstrate that the situation is different when MRF "spot" is at the leading edge or at the trailing edge. Two methods for reducing the edge effect are put into practice after analysis of the processing results. One is adopting a small removal function for dealing with the workpiece edge, and the other is utilizing the removal function compensation. The actual processing results show that these two ways are both effective on reducing the edge effect in MRF.

Vehicle tracking using fuzzy-based vehicle detection window with adaptive parameters

NASA Astrophysics Data System (ADS)

Chitsobhuk, Orachat; Kasemsiri, Watjanapong; Glomglome, Sorayut; Lapamonpinyo, Pipatphon

2018-04-01

In this paper, fuzzy-based vehicle tracking system is proposed. The proposed system consists of two main processes: vehicle detection and vehicle tracking. In the first process, the Gradient-based Adaptive Threshold Estimation (GATE) algorithm is adopted to provide the suitable threshold value for the sobel edge detection. The estimated threshold can be adapted to the changes of diverse illumination conditions throughout the day. This leads to greater vehicle detection performance compared to a fixed user's defined threshold. In the second process, this paper proposes the novel vehicle tracking algorithms namely Fuzzy-based Vehicle Analysis (FBA) in order to reduce the false estimation of the vehicle tracking caused by uneven edges of the large vehicles and vehicle changing lanes. The proposed FBA algorithm employs the average edge density and the Horizontal Moving Edge Detection (HMED) algorithm to alleviate those problems by adopting fuzzy rule-based algorithms to rectify the vehicle tracking. The experimental results demonstrate that the proposed system provides the high accuracy of vehicle detection about 98.22%. In addition, it also offers the low false detection rates about 3.92%.

Development and application of traffic flow information collecting and analysis system based on multi-type video

NASA Astrophysics Data System (ADS)

Lu, Mujie; Shang, Wenjie; Ji, Xinkai; Hua, Mingzhuang; Cheng, Kuo

2015-12-01

Nowadays, intelligent transportation system (ITS) has already become the new direction of transportation development. Traffic data, as a fundamental part of intelligent transportation system, is having a more and more crucial status. In recent years, video observation technology has been widely used in the field of traffic information collecting. Traffic flow information contained in video data has many advantages which is comprehensive and can be stored for a long time, but there are still many problems, such as low precision and high cost in the process of collecting information. This paper aiming at these problems, proposes a kind of traffic target detection method with broad applicability. Based on three different ways of getting video data, such as aerial photography, fixed camera and handheld camera, we develop a kind of intelligent analysis software which can be used to extract the macroscopic, microscopic traffic flow information in the video, and the information can be used for traffic analysis and transportation planning. For road intersections, the system uses frame difference method to extract traffic information, for freeway sections, the system uses optical flow method to track the vehicles. The system was applied in Nanjing, Jiangsu province, and the application shows that the system for extracting different types of traffic flow information has a high accuracy, it can meet the needs of traffic engineering observations and has a good application prospect.

Verification of rut depth collected with the INO laser rut measurement system : executive summary report.

DOT National Transportation Integrated Search

2011-10-28

Since 1985, ODOT has been manually collecting rut : depth data using a straight edge and dial gauge (S&G). This : method is slow and dangerous to pavement condition raters : when traffic control is not available. According to the : Pavement Condition...

A computing method for spatial accessibility based on grid partition

NASA Astrophysics Data System (ADS)

Ma, Linbing; Zhang, Xinchang

2007-06-01

An accessibility computing method and process based on grid partition was put forward in the paper. As two important factors impacting on traffic, density of road network and relative spatial resistance for difference land use was integrated into computing traffic cost in each grid. A* algorithms was inducted to searching optimum traffic cost of grids path, a detailed searching process and definition of heuristic evaluation function was described in the paper. Therefore, the method can be implemented more simply and its data source is obtained more easily. Moreover, by changing heuristic searching information, more reasonable computing result can be obtained. For confirming our research, a software package was developed with C# language under ArcEngine9 environment. Applying the computing method, a case study on accessibility of business districts in Guangzhou city was carried out.

New Scheduling Algorithms for Agile All-Photonic Networks

NASA Astrophysics Data System (ADS)

Mehri, Mohammad Saleh; Ghaffarpour Rahbar, Akbar

2017-12-01

An optical overlaid star network is a class of agile all-photonic networks that consists of one or more core node(s) at the center of the star network and a number of edge nodes around the core node. In this architecture, a core node may use a scheduling algorithm for transmission of traffic through the network. A core node is responsible for scheduling optical packets that arrive from edge nodes and switching them toward their destinations. Nowadays, most edge nodes use virtual output queue (VOQ) architecture for buffering client packets to achieve high throughput. This paper presents two efficient scheduling algorithms called discretionary iterative matching (DIM) and adaptive DIM. These schedulers find maximum matching in a small number of iterations and provide high throughput and incur low delay. The number of arbiters in these schedulers and the number of messages exchanged between inputs and outputs of a core node are reduced. We show that DIM and adaptive DIM can provide better performance in comparison with iterative round-robin matching with SLIP (iSLIP). SLIP means the act of sliding for a short distance to select one of the requested connections based on the scheduling algorithm.

Intensity dependent spread theory

NASA Technical Reports Server (NTRS)

Holben, Richard

1990-01-01

The Intensity Dependent Spread (IDS) procedure is an image-processing technique based on a model of the processing which occurs in the human visual system. IDS processing is relevant to many aspects of machine vision and image processing. For quantum limited images, it produces an ideal trade-off between spatial resolution and noise averaging, performs edge enhancement thus requiring only mean-crossing detection for the subsequent extraction of scene edges, and yields edge responses whose amplitudes are independent of scene illumination, depending only upon the ratio of the reflectance on the two sides of the edge. These properties suggest that the IDS process may provide significant bandwidth reduction while losing only minimal scene information when used as a preprocessor at or near the image plane.

A quantum mechanics-based approach to model incident-induced dynamic driver behavior

NASA Astrophysics Data System (ADS)

Sheu, Jiuh-Biing

2008-08-01

A better understanding of the psychological factors influencing drivers, and the resulting driving behavior responding to incident-induced lane traffic phenomena while passing by an incident site is vital to the improvement of road safety. This paper presents a microscopic driver behavior model to explain the dynamics of the instantaneous driver decision process under lane-blocking incidents on adjacent lanes. The proposed conceptual framework decomposes the corresponding driver decision process into three sequential phases: (1) initial stimulus, (2) glancing-around car-following, and (3) incident-induced driving behavior. The theorem of quantum mechanics in optical flows is applied in the first phase to explain the motion-related perceptual phenomena while vehicles approach the incident site in adjacent lanes, followed by the incorporation of the effect of quantum optical flows in modeling the induced glancing-around car-following behavior in the second phase. Then, an incident-induced driving behavior model is formulated to reproduce the dynamics of driver behavior conducted in the process of passing by an incident site in the adjacent lanes. Numerical results of model tests using video-based incident data indicate the validity of the proposed traffic behavior model in analyzing the incident-induced lane traffic phenomena. It is also expected that such a proposed quantum-mechanics based methodology can throw more light if applied to driver psychology and response in anomalous traffic environments in order to improve road safety.

Future benefits and applications of intelligent on-board processing to VSAT services

NASA Technical Reports Server (NTRS)

Price, Kent M.; Kwan, Robert K.; Edward, Ron; Faris, F.; Inukai, Tom

1992-01-01

The trends and roles of VSAT services in the year 2010 time frame are examined based on an overall network and service model for that period. An estimate of the VSAT traffic is then made and the service and general network requirements are identified. In order to accommodate these traffic needs, four satellite VSAT architectures based on the use of fixed or scanning multibeam antennas in conjunction with IF switching or onboard regeneration and baseband processing are suggested. The performance of each of these architectures is assessed and the key enabling technologies are identified.

Verification of rut depth collected with the INO laser rut measurement system (LRMS) : executive summary report.

DOT National Transportation Integrated Search

2011-11-01

Since 1985, ODOT has been manually collecting rut : depth data using a straight edge and dial gauge (S&G). This : method is slow and dangerous to pavement condition raters : when traffic control is not available. According to the : Pavement Condition...

NASA and general aviation

NASA Technical Reports Server (NTRS)

Ethell, J. L.

1986-01-01

General aviation remains the single most misunderstood sector of aeronautics in the United States. A detailed look at how general aviation functions and how NASA helps keep it on the cutting edge of technology in airfoils, airframes, commuter travel, environmental concerns, engines, propellers, air traffic control, agricultural development, electronics, and safety is given.

Spatial Analysis of Traffic and Routing Path Methods for Tsunami Evacuation

NASA Astrophysics Data System (ADS)

Fakhrurrozi, A.; Sari, A. M.

2018-02-01

Tsunami disaster occurred relatively very fast. Thus, it has a very large-scale impact on both non-material and material aspects. Community evacuation caused mass panic, crowds, and traffic congestion. A further research in spatial based modelling, traffic engineering and splitting zone evacuation simulation is very crucial as an effort to reduce higher losses. This topic covers some information from the previous research. Complex parameters include route selection, destination selection, the spontaneous timing of both the departure of the source and the arrival time to destination and other aspects of the result parameter in various methods. The simulation process and its results, traffic modelling, and routing analysis emphasized discussion which is the closest to real conditions in the tsunami evacuation process. The method that we should highlight is Clearance Time Estimate based on Location Priority in which the computation result is superior to others despite many drawbacks. The study is expected to have input to improve and invent a new method that will be a part of decision support systems for disaster risk reduction of tsunamis disaster.

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.

Traffic Congestion Detection System through Connected Vehicles and Big Data

PubMed Central

Cárdenas-Benítez, Néstor; Aquino-Santos, Raúl; Magaña-Espinoza, Pedro; Aguilar-Velazco, José; Edwards-Block, Arthur; Medina Cass, Aldo

2016-01-01

This article discusses the simulation and evaluation of a traffic congestion detection system which combines inter-vehicular communications, fixed roadside infrastructure and infrastructure-to-infrastructure connectivity and big data. The system discussed in this article permits drivers to identify traffic congestion and change their routes accordingly, thus reducing the total emissions of CO2 and decreasing travel time. This system monitors, processes and stores large amounts of data, which can detect traffic congestion in a precise way by means of a series of algorithms that reduces localized vehicular emission by rerouting vehicles. To simulate and evaluate the proposed system, a big data cluster was developed based on Cassandra, which was used in tandem with the OMNeT++ discreet event network simulator, coupled with the SUMO (Simulation of Urban MObility) traffic simulator and the Veins vehicular network framework. The results validate the efficiency of the traffic detection system and its positive impact in detecting, reporting and rerouting traffic when traffic events occur. PMID:27136548

Traffic Congestion Detection System through Connected Vehicles and Big Data.

PubMed

Cárdenas-Benítez, Néstor; Aquino-Santos, Raúl; Magaña-Espinoza, Pedro; Aguilar-Velazco, José; Edwards-Block, Arthur; Medina Cass, Aldo

2016-04-28

This article discusses the simulation and evaluation of a traffic congestion detection system which combines inter-vehicular communications, fixed roadside infrastructure and infrastructure-to-infrastructure connectivity and big data. The system discussed in this article permits drivers to identify traffic congestion and change their routes accordingly, thus reducing the total emissions of CO₂ and decreasing travel time. This system monitors, processes and stores large amounts of data, which can detect traffic congestion in a precise way by means of a series of algorithms that reduces localized vehicular emission by rerouting vehicles. To simulate and evaluate the proposed system, a big data cluster was developed based on Cassandra, which was used in tandem with the OMNeT++ discreet event network simulator, coupled with the SUMO (Simulation of Urban MObility) traffic simulator and the Veins vehicular network framework. The results validate the efficiency of the traffic detection system and its positive impact in detecting, reporting and rerouting traffic when traffic events occur.

Traffic flow collection wireless sensor network node for intersection light control

NASA Astrophysics Data System (ADS)

Li, Xu; Li, Xue

2011-10-01

Wireless sensor network (WSN) is expected to be deployed in intersection to monitor the traffic flow continuously, and the monitoring datum can be used as the foundation of traffic light control. In this paper, a WSN based on ZigBee protocol for monitoring traffic flow is proposed. Structure, hardware and work flow of WSN nodes are designed. CC2431 from Texas Instrument is chosen as the main computational and transmission unit, and CC2591 as the amplification unit. The stability experiment and the actual environment experiment are carried out in the last of the paper. The results of experiments show that WSN has the ability to collect traffic flow information quickly and transmit the datum to the processing center in real time.

Prevalence and regional correlates of road traffic injury among Chinese urban residents: A 21-city population-based study.

PubMed

Rockett, Ian R H; Jiang, Shuhan; Yang, Qian; Yang, Tingzhong; Yang, Xiaozhao Y; Peng, Sihui; Yu, Lingwei

2017-08-18

This study estimated the prevalence of road traffic injury among Chinese urban residents and examined individual and regional-level correlates. A cross-sectional multistage process was used to sample residents from 21 selected cities in China. Survey respondents reported their history of road traffic injury in the past 12 months through a community survey. Multilevel, multivariable logistic regression analysis was used to identify injury correlates. Based on a retrospective 12-month reporting window, road traffic injury prevalence among urban residents was 13.2%. Prevalence of road traffic injury, by type, was 8.7, 8.7, 8.5, and 7.7% in the automobile, bicycle, motorcycle, and pedestrian categories, respectively. Multilevel analysis showed that prevalence of road traffic injury was positively associated with minority status, income, and mental health disorder score at the individual level. Regionally, road traffic injury was associated with geographic location of residence and prevalence of mental health disorders. Both individual and regional-level variables were associated with road traffic injury among Chinese urban residents, a finding whose implications transcend wholesale imported generic solutions. This descriptive research demonstrates an urgent need for longitudinal studies across China on risk and protective factors, in order to inform injury etiology, surveillance, prevention, treatment, and evaluation.

Constraint-based stereo matching

NASA Technical Reports Server (NTRS)

Kuan, D. T.

1987-01-01

The major difficulty in stereo vision is the correspondence problem that requires matching features in two stereo images. Researchers describe a constraint-based stereo matching technique using local geometric constraints among edge segments to limit the search space and to resolve matching ambiguity. Edge segments are used as image features for stereo matching. Epipolar constraint and individual edge properties are used to determine possible initial matches between edge segments in a stereo image pair. Local edge geometric attributes such as continuity, junction structure, and edge neighborhood relations are used as constraints to guide the stereo matching process. The result is a locally consistent set of edge segment correspondences between stereo images. These locally consistent matches are used to generate higher-level hypotheses on extended edge segments and junctions to form more global contexts to achieve global consistency.

A new region-edge based level set model with applications to image segmentation

NASA Astrophysics Data System (ADS)

Zhi, Xuhao; Shen, Hong-Bin

2018-04-01

Level set model has advantages in handling complex shapes and topological changes, and is widely used in image processing tasks. The image segmentation oriented level set models can be grouped into region-based models and edge-based models, both of which have merits and drawbacks. Region-based level set model relies on fitting to color intensity of separated regions, but is not sensitive to edge information. Edge-based level set model evolves by fitting to local gradient information, but can get easily affected by noise. We propose a region-edge based level set model, which considers saliency information into energy function and fuses color intensity with local gradient information. The evolution of the proposed model is implemented by a hierarchical two-stage protocol, and the experimental results show flexible initialization, robust evolution and precise segmentation.

Preliminary Investigation of Workload on Intrastate Bus Traffic Controllers

NASA Astrophysics Data System (ADS)

Yen Bin, Teo; Azlis-Sani, Jalil; Nur Annuar Mohd Yunos, Muhammad; Ismail, S. M. Sabri S. M.; Tajedi, Noor Aqilah Ahmad

2016-11-01

The daily routine of bus traffic controller which involves high mental processes would have a direct impact on the level of workload. To date, the level of workload on the bus traffic controllers in Malaysia is relatively unknown. Excessive workload on bus traffic controllers would affect the control and efficiency of the system. This paper served to study the workload on bus traffic controllers and justify the needs to conduct further detailed research on this field. The objectives of this research are to identify the level of workload on the intrastate bus traffic controllers. Based on the results, recommendations will be proposed for improvements and future studies. The level of workload for the bus traffic controllers is quantified using questionnaire adapted from NASA TLX. Interview sessions were conducted for validation of workload. Sixteen respondents were involved and it was found that the average level of workload based on NASA TLX was 6.91. It was found that workload is not affected by gender and marital status. This study also showed that the level of workload and working experience of bus traffic controllers has a strong positive linear relationship. This study would serve as a guidance and reference related to this field. Since this study is a preliminary investigation, further detailed studies could be conducted to obtain a better comprehension regarding the bus traffic controllers.

Profile negotiation - A concept for integrating airborne and ground-based automation for managing arrival traffic

NASA Technical Reports Server (NTRS)

Green, Steven M.; Den Braven, Wim; Williams, David H.

1991-01-01

The profile negotiation process (PNP) concept as applied to the management of arrival traffic within the extended terminal area is presented, focusing on functional issues from the ground-based perspective. The PNP is an interactive process between an aircraft and air traffic control (ATC) which combines airborne and ground-based automation capabilities to determine conflict-free trajectories that are as close to an aircraft's preference as possible. Preliminary results from a real-time simulation study show that the controller teams are able to consistently and effectively negotiate conflict-free vertical profiles with 4D-equipped aircraft. The ability of the airborne 4D flight management system to adapt to ATC specified 4D trajectory constraints is found to be a requirement for successful execution of the PNP. It is recommended that the conventional method of cost index iteration for obtaining the minimum fuel 4D trajectory be supplemented by a method which constrains the profile speeds to those desired by ATC.

Discussion of Planning and Operating of Chongming Qianwei Village's Nongjiale tourism site

NASA Astrophysics Data System (ADS)

Guo, Qingqing; Liu, Min

According to the sufficient market research the paper put forward the Construction and operation of Chongming Qianwei village Nongjiale tour website completed the Building program of this Business Website. Through needs analysis and feasibility analysis, this paper proposed business model for the target system, transaction mode, revenue model and competitive edge. Opening of the bridge which contact Shanghai and Chongming, coming of the shanghai expo; will bring the growth of passenger traffic of chongming's tourism industry. This article is based on this background, discussing the exploitation and plan of tour website of ChongMing, Enhancing the Popularity and Competitiveness of Chongming's Tourism.

A Collection of Technical Papers

NASA Technical Reports Server (NTRS)

1995-01-01

Papers presented at the 6th Space Logistics Symposium covered such areas as: The International Space Station; The Hubble Space Telescope; Launch site computer simulation; Integrated logistics support; The Baikonur Cosmodrome; Probabalistic tools for high confidence repair; A simple space station rescue vehicle; Integrated Traffic Model for the International Space Station; Packaging the maintenance shop; Leading edge software support; Storage information management system; Consolidated maintenance inventory logistics planning; Operation concepts for a single stage to orbit vehicle; Mission architecture for human lunar exploration; Logistics of a lunar based solar power satellite scenario; Just in time in space; NASA acquisitions/logistics; Effective transition management; Shuttle logistics; and Revitalized space operations through total quality control management.

Application of Finite Element Method in Traffic Injury and Its Prospect in Forensic Science.

PubMed

Liu, C G; Lu, Y J; Gao, J; Liu, Q

2016-06-01

The finite element method （FEM） is a numerical computation method based on computer technology, and has been gradually applied in the fields of medicine and biomechanics. The finite element analysis can be used to explore the loading process and injury mechanism of human body in traffic injury. FEM is also helpful for the forensic investigation in traffic injury. This paper reviews the development of the finite element models and analysis of brain, cervical spine, chest and abdomen, pelvis, limbs at home and aboard in traffic injury in recent years. Copyright© by the Editorial Department of Journal of Forensic Medicine.

Impact of Operating Context on the Use of Structure in Air Traffic Controller Cognitive Processes

NASA Technical Reports Server (NTRS)

Davison, Hayley J.; Histon, Jonathan M.; Ragnarsdottir, Margret Dora; Major, Laura M.; Hansman, R. John

2004-01-01

This paper investigates the influence of structure on air traffic controllers cognitive processes in the TRACON, En Route, and Oceanic environments. Radar data and voice command analyses were conducted to support hypotheses generated through observations and interviews conducted at the various facilities. Three general types of structure-based abstractions (standard flows, groupings, and critical points) have been identified as being used in each context, though the details of their application varied in accordance with the constraints of the particular operational environment. Projection emerged as a key cognitive process aided by the structure-based abstractions, and there appears to be a significant difference between how time-based versus spatial-based projection is performed by controllers. It is recommended that consideration be given to the value provided by the structure-based abstractions to the controller as well as to maintain consistency between the type (time or spatial) of information support provided to the controller.

Multi-edge X-ray absorption spectroscopy study of road dust samples from a traffic area of Venice using stoichiometric and environmental references.

PubMed

Valotto, Gabrio; Cattaruzza, Elti; Bardelli, Fabrizio

2017-02-15

The appropriate selection of representative pure compounds to be used as reference is a crucial step for successful analysis of X-ray absorption near edge spectroscopy (XANES) data, and it is often not a trivial task. This is particularly true when complex environmental matrices are investigated, being their elemental speciation a priori unknown. In this paper, an investigation on the speciation of Cu, Zn, and Sb based on the use of conventional (stoichiometric compounds) and non-conventional (environmental samples or relevant certified materials) references is explored. This method can be useful in when the effectiveness of XANES analysis is limited because of the difficulty in obtaining a set of references sufficiently representative of the investigated samples. Road dust samples collected along the bridge connecting Venice to the mainland were used to show the potentialities and the limits of this approach. Copyright © 2016 Elsevier B.V. All rights reserved.

Multispectral image sharpening using a shift-invariant wavelet transform and adaptive processing of multiresolution edges

USGS Publications Warehouse

Lemeshewsky, G.P.; Rahman, Z.-U.; Schowengerdt, R.A.; Reichenbach, S.E.

2002-01-01

Enhanced false color images from mid-IR, near-IR (NIR), and visible bands of the Landsat thematic mapper (TM) are commonly used for visually interpreting land cover type. Described here is a technique for sharpening or fusion of NIR with higher resolution panchromatic (Pan) that uses a shift-invariant implementation of the discrete wavelet transform (SIDWT) and a reported pixel-based selection rule to combine coefficients. There can be contrast reversals (e.g., at soil-vegetation boundaries between NIR and visible band images) and consequently degraded sharpening and edge artifacts. To improve performance for these conditions, I used a local area-based correlation technique originally reported for comparing image-pyramid-derived edges for the adaptive processing of wavelet-derived edge data. Also, using the redundant data of the SIDWT improves edge data generation. There is additional improvement because sharpened subband imagery is used with the edge-correlation process. A reported technique for sharpening three-band spectral imagery used forward and inverse intensity, hue, and saturation transforms and wavelet-based sharpening of intensity. This technique had limitations with opposite contrast data, and in this study sharpening was applied to single-band multispectral-Pan image pairs. Sharpening used simulated 30-m NIR imagery produced by degrading the spatial resolution of a higher resolution reference. Performance, evaluated by comparison between sharpened and reference image, was improved when sharpened subband data were used with the edge correlation.

On-board processing for future satellite communications systems: Satellite-Routed FDMA

NASA Astrophysics Data System (ADS)

Berk, G.; Christopher, P. F.; Hoffman, M.; Jean, P. N.; Rotholz, E.; White, B. E.

1981-05-01

A frequency division multiple access (FDMA) 30/20 GHz satellite communications architecture without on-board baseband processing is investigated. Conceptual system designs are suggested for domestic traffic models totaling 4 Gb/s of customer premises service (CPS) traffic and 6 Gb/s of trunking traffic. Emphasis is given to the CPS portion of the system which includes thousands of earth terminals with digital traffic ranging from a single 64 kb/s voice channel to hundreds of channels of voice, data, and video with an aggregate data rate of 33 Mb/s. A unique regional design concept that effectively smooths the non-uniform traffic distribution and greatly simplifies the satellite design is employed. The satellite antenna system forms thirty-two 0.33 deg beam on both the uplinks and the downlinks in one design. In another design matched to a traffic model with more dispersed users, there are twenty-four 0.33 deg beams and twenty-one 0.7 deg beams. Detailed system design techniques show that a single satellite producing approximately 5 kW of dc power is capable of handling at least 75% of the postulated traffic. A detailed cost model of the ground segment and estimated system costs based on current information from manufacturers are presented.

On-board processing for future satellite communications systems: Satellite-Routed FDMA

NASA Technical Reports Server (NTRS)

Berk, G.; Christopher, P. F.; Hoffman, M.; Jean, P. N.; Rotholz, E.; White, B. E.

1981-01-01

A frequency division multiple access (FDMA) 30/20 GHz satellite communications architecture without on-board baseband processing is investigated. Conceptual system designs are suggested for domestic traffic models totaling 4 Gb/s of customer premises service (CPS) traffic and 6 Gb/s of trunking traffic. Emphasis is given to the CPS portion of the system which includes thousands of earth terminals with digital traffic ranging from a single 64 kb/s voice channel to hundreds of channels of voice, data, and video with an aggregate data rate of 33 Mb/s. A unique regional design concept that effectively smooths the non-uniform traffic distribution and greatly simplifies the satellite design is employed. The satellite antenna system forms thirty-two 0.33 deg beam on both the uplinks and the downlinks in one design. In another design matched to a traffic model with more dispersed users, there are twenty-four 0.33 deg beams and twenty-one 0.7 deg beams. Detailed system design techniques show that a single satellite producing approximately 5 kW of dc power is capable of handling at least 75% of the postulated traffic. A detailed cost model of the ground segment and estimated system costs based on current information from manufacturers are presented.

Mobile Traffic Alert and Tourist Route Guidance System Design Using Geospatial Data

NASA Astrophysics Data System (ADS)

Bhattacharya, D.; Painho, M.; Mishra, S.; Gupta, A.

2017-09-01

The present study describes an integrated system for traffic data collection and alert warning. Geographical information based decision making related to traffic destinations and routes is proposed through the design. The system includes a geospatial database having profile relating to a user of a mobile device. The processing and understanding of scanned maps, other digital data input leads to route guidance. The system includes a server configured to receive traffic information relating to a route and location information relating to the mobile device. Server is configured to send a traffic alert to the mobile device when the traffic information and the location information indicate that the mobile device is traveling toward traffic congestion. Proposed system has geospatial and mobile data sets pertaining to Bangalore city in India. It is envisaged to be helpful for touristic purposes as a route guidance and alert relaying information system to tourists for proximity to sites worth seeing in a city they have entered into. The system is modular in architecture and the novelty lies in integration of different modules carrying different technologies for a complete traffic information system. Generic information processing and delivery system has been tested to be functional and speedy under test geospatial domains. In a restricted prototype model with geo-referenced route data required information has been delivered correctly over sustained trials to designated cell numbers, with average time frame of 27.5 seconds, maximum 50 and minimum 5 seconds. Traffic geo-data set trials testing is underway.

Environmental assessment of polycyclic aromatic hydrocarbons (PAHs) in surface sediments of the Santander Bay, Northern Spain.

PubMed

Viguri, J; Verde, J; Irabien, A

2002-07-01

Samples of intertidal surface sediments (0-2 cm) were collected in 17 stations of the Santander Bay, Cantabric Sea, Northern Spain. The concentrations of polycyclic aromatic hydrocarbons (PAHs), 16, were analysed by HPLC and MS detection. Surface sediments show a good linear correlation among the parameters of the experimental organic matter evaluation, where total carbon (TC) and loss on ignition (LOI) are approximately 2.5 and 5 times total organic carbon (TOC). A wide range of TOC from 0.08% to 4.1%, and a broad distribution of the sum of sigma16PAHs, from 0.02 to 344.6 microg/g d.w., which can be correlated by an exponential equation to the TOC, has been identified. A qualitative relationship may be established between the industrial input along the rivers and the concentration of sigma6PAHs in the sediments of the estuaries: Boo estuary (8404-4631 microg/g OC), Solia-San Salvador estuaries (305-113 microg/g OC) and Cubas estuary (31-32 microg/g OC). This work shows a dramatic change in the spatial distribution in the concentration of PAHs of intertidal surface sediments. The left edge of the Bay has the main traffic around the city and the major source of PAHs is from combustion processes and estuarine inputs, leading to medium values of PAHs in the sediments; the right edge of the Bay has much lesser anthropogenic activities leading to lower values of PAHs in sediments. The distribution of individual PAHs in sediments varies widely depending on their structure and molecular weight; the 4-6 ring aromatics predominate in polluted sediments due to their higher persistence. The isomer ratio does not allow any clear identification of the PAHs origin. Environmental evaluation according to Dutch guidelines and consensus sediment quality guidelines based on ecotoxicological data leads to the same conclusion, sediments in the Santander Bay show a very different environmental quality depending on the spatial position from heavily polluted/medium effects to non-polluted/below threshold effects. These results indicate that local sources of PAHs, especially estuary discharges, lead to very different qualities of sediments in coastal zones, where traffic and industrial activities take place.

Economic analysis of fuel ethanol production from hulled barley by the EDGE (Enhanced Dry Grind Enzymatic) process

USDA-ARS?s Scientific Manuscript database

A cost model was developed for fuel ethanol production from barley based on the EDGE (Enhanced Dry Grind Enzymatic) process (Nghiem, et al., 2008). In this process, in addition to beta-glucanases, which is added to reduce the viscosity of the barley mash for efficient mixing, another enzyme, beta-...

Experimental pavement delineation treatments

NASA Astrophysics Data System (ADS)

Bryden, J. E.; Lorini, R. A.

1981-06-01

Visibility and durability of materials used to delineate shoulders and medians adjacent to asphalt pavements were evaluated. Materials evaluated were polysulfide and coal tar epoxies, one and two component polyesters, portland cement, acrylic paints, modified-alkyd traffic paint, preformed plastic tape, and thermoplastic markings. Neat applications, sand mortars, and surface treatments were installed in several geometric patterns including cross hatches, solid median treatments, and various widths of edge lines. Thermoplastic pavement markings generally performed very well, providing good visibility under adverse viewing conditions for at least 4 years. Thermoplastic 4 in. wide edge lines appear to provide adequate visibility for most conditions.

Fast digital zooming system using directionally adaptive image interpolation and restoration.

PubMed

Kang, Wonseok; Jeon, Jaehwan; Yu, Soohwan; Paik, Joonki

2014-01-01

This paper presents a fast digital zooming system for mobile consumer cameras using directionally adaptive image interpolation and restoration methods. The proposed interpolation algorithm performs edge refinement along the initially estimated edge orientation using directionally steerable filters. Either the directionally weighted linear or adaptive cubic-spline interpolation filter is then selectively used according to the refined edge orientation for removing jagged artifacts in the slanted edge region. A novel image restoration algorithm is also presented for removing blurring artifacts caused by the linear or cubic-spline interpolation using the directionally adaptive truncated constrained least squares (TCLS) filter. Both proposed steerable filter-based interpolation and the TCLS-based restoration filters have a finite impulse response (FIR) structure for real time processing in an image signal processing (ISP) chain. Experimental results show that the proposed digital zooming system provides high-quality magnified images with FIR filter-based fast computational structure.

Querying and Extracting Timeline Information from Road Traffic Sensor Data

PubMed Central

Imawan, Ardi; Indikawati, Fitri Indra; Kwon, Joonho; Rao, Praveen

2016-01-01

The escalation of traffic congestion in urban cities has urged many countries to use intelligent transportation system (ITS) centers to collect historical traffic sensor data from multiple heterogeneous sources. By analyzing historical traffic data, we can obtain valuable insights into traffic behavior. Many existing applications have been proposed with limited analysis results because of the inability to cope with several types of analytical queries. In this paper, we propose the QET (querying and extracting timeline information) system—a novel analytical query processing method based on a timeline model for road traffic sensor data. To address query performance, we build a TQ-index (timeline query-index) that exploits spatio-temporal features of timeline modeling. We also propose an intuitive timeline visualization method to display congestion events obtained from specified query parameters. In addition, we demonstrate the benefit of our system through a performance evaluation using a Busan ITS dataset and a Seattle freeway dataset. PMID:27563900

32 CFR 935.136 - General operating rules.

Code of Federal Regulations, 2010 CFR

2010-07-01

... unposted area, except adjacent to the right-hand curb or edge of the road; (k) Park a motor vehicle in a... compacted surface; (n) Operate any motor vehicle contrary to a posted traffic sign; (o) Operate a motor... vehicle off of established roads, or in a cross-country manner, except when necessary in conducting...

32 CFR 935.136 - General operating rules.

Code of Federal Regulations, 2011 CFR

2011-07-01

... unposted area, except adjacent to the right-hand curb or edge of the road; (k) Park a motor vehicle in a... compacted surface; (n) Operate any motor vehicle contrary to a posted traffic sign; (o) Operate a motor... vehicle off of established roads, or in a cross-country manner, except when necessary in conducting...

32 CFR 935.136 - General operating rules.

Code of Federal Regulations, 2012 CFR

2012-07-01

... unposted area, except adjacent to the right-hand curb or edge of the road; (k) Park a motor vehicle in a... compacted surface; (n) Operate any motor vehicle contrary to a posted traffic sign; (o) Operate a motor... vehicle off of established roads, or in a cross-country manner, except when necessary in conducting...

32 CFR 935.136 - General operating rules.

Code of Federal Regulations, 2014 CFR

2014-07-01

... unposted area, except adjacent to the right-hand curb or edge of the road; (k) Park a motor vehicle in a... compacted surface; (n) Operate any motor vehicle contrary to a posted traffic sign; (o) Operate a motor... vehicle off of established roads, or in a cross-country manner, except when necessary in conducting...

32 CFR 935.136 - General operating rules.

Code of Federal Regulations, 2013 CFR

2013-07-01

... unposted area, except adjacent to the right-hand curb or edge of the road; (k) Park a motor vehicle in a... compacted surface; (n) Operate any motor vehicle contrary to a posted traffic sign; (o) Operate a motor... vehicle off of established roads, or in a cross-country manner, except when necessary in conducting...

Cooperation and information replication in wireless networks.

PubMed

Poularakis, Konstantinos; Tassiulas, Leandros

2016-03-06

A significant portion of today's network traffic is due to recurring downloads of a few popular contents. It has been observed that replicating the latter in caches installed at network edges-close to users-can drastically reduce network bandwidth usage and improve content access delay. Such caching architectures are gaining increasing interest in recent years as a way of dealing with the explosive traffic growth, fuelled further by the downward slope in storage space price. In this work, we provide an overview of caching with a particular emphasis on emerging network architectures that enable caching at the radio access network. In this context, novel challenges arise due to the broadcast nature of the wireless medium, which allows simultaneously serving multiple users tuned into a multicast stream, and the mobility of the users who may be frequently handed off from one cell tower to another. Existing results indicate that caching at the wireless edge has a great potential in removing bottlenecks on the wired backbone networks. Taking into consideration the schedule of multicast service and mobility profiles is crucial to extract maximum benefit in network performance. © 2016 The Author(s).

3D Markov Process for Traffic Flow Prediction in Real-Time.

PubMed

Ko, Eunjeong; Ahn, Jinyoung; Kim, Eun Yi

2016-01-25

Recently, the correct estimation of traffic flow has begun to be considered an essential component in intelligent transportation systems. In this paper, a new statistical method to predict traffic flows using time series analyses and geometric correlations is proposed. The novelty of the proposed method is two-fold: (1) a 3D heat map is designed to describe the traffic conditions between roads, which can effectively represent the correlations between spatially- and temporally-adjacent traffic states; and (2) the relationship between the adjacent roads on the spatiotemporal domain is represented by cliques in MRF and the clique parameters are obtained by example-based learning. In order to assess the validity of the proposed method, it is tested using data from expressway traffic that are provided by the Korean Expressway Corporation, and the performance of the proposed method is compared with existing approaches. The results demonstrate that the proposed method can predict traffic conditions with an accuracy of 85%, and this accuracy can be improved further.

3D Markov Process for Traffic Flow Prediction in Real-Time

PubMed Central

Ko, Eunjeong; Ahn, Jinyoung; Kim, Eun Yi

2016-01-01

Recently, the correct estimation of traffic flow has begun to be considered an essential component in intelligent transportation systems. In this paper, a new statistical method to predict traffic flows using time series analyses and geometric correlations is proposed. The novelty of the proposed method is two-fold: (1) a 3D heat map is designed to describe the traffic conditions between roads, which can effectively represent the correlations between spatially- and temporally-adjacent traffic states; and (2) the relationship between the adjacent roads on the spatiotemporal domain is represented by cliques in MRF and the clique parameters are obtained by example-based learning. In order to assess the validity of the proposed method, it is tested using data from expressway traffic that are provided by the Korean Expressway Corporation, and the performance of the proposed method is compared with existing approaches. The results demonstrate that the proposed method can predict traffic conditions with an accuracy of 85%, and this accuracy can be improved further. PMID:26821025

Improvement in the Accuracy of Matching by Different Feature Subspaces in Traffic Sign Recognition

NASA Astrophysics Data System (ADS)

Ihara, Arihito; Fujiyoshi, Hironobu; Takaki, Masanari; Kumon, Hiroaki; Tamatsu, Yukimasa

A technique for recognizing traffic signs from an image taken with an in-vehicle camera has already been proposed as driver's drive assist. SIFT feature is used for traffic sign recognition, because it is robust to changes in scaling and rotating of the traffic sign. However, it is difficult to process in real-time because the computation cost of the SIFT feature extraction and matching is expensive. This paper presents a method of traffic sign recognition based on keypoint classifier by AdaBoost using PCA-SIFT features in different feature subspaces. Each subspace is constructed from gradients of traffic sign images and general images respectively. A detected keypoint is projected to both subspaces, and then the AdaBoost employs to classy into whether the keypoint is on the traffic sign or not. Experimental results show that the computation cost for keypoint matching can be reduced to about 1/2 compared with the conventional method.

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.

An improved car-following model with two preceding cars' average speed

NASA Astrophysics Data System (ADS)

Yu, Shao-Wei; Shi, Zhong-Ke

2015-01-01

To better describe cooperative car-following behaviors under intelligent transportation circumstances and increase roadway traffic mobility, the data of three successive following cars at a signalized intersection of Jinan in China were obtained and employed to explore the linkage between two preceding cars' average speed and car-following behaviors. The results indicate that two preceding cars' average velocity has significant effects on the following car's motion. Then an improved car-following model considering two preceding cars' average velocity was proposed and calibrated based on full velocity difference model and some numerical simulations were carried out to study how two preceding cars' average speed affected the starting process and the traffic flow evolution process with an initial small disturbance, the results indicate that the improved car-following model can qualitatively describe the impacts of two preceding cars' average velocity on traffic flow and that taking two preceding cars' average velocity into account in designing the control strategy for the cooperative adaptive cruise control system can improve the stability of traffic flow, suppress the appearance of traffic jams and increase the capacity of signalized intersections.

A wireless sensor network for urban traffic characterization and trend monitoring.

PubMed

Fernández-Lozano, J J; Martín-Guzmán, Miguel; Martín-Ávila, Juan; García-Cerezo, A

2015-10-15

Sustainable mobility requires a better management of the available infrastructure resources. To achieve this goal, it is necessary to obtain accurate data about road usage, in particular in urban areas. Although a variety of sensor alternates for urban traffic exist, they usually require extensive investments in the form of construction works for installation, processing means, etc. Wireless Sensor Networks (WSN) are an alternative to acquire urban traffic data, allowing for flexible, easy deployment. Together with the use of the appropriate sensors, like Bluetooth identification, and associate processing, WSN can provide the means to obtain in real time data like the origin-destination matrix, a key tool for trend monitoring which previously required weeks or months to be completed. This paper presents a system based on WSN designed to characterize urban traffic, particularly traffic trend monitoring through the calculation of the origin-destination matrix in real time by using Bluetooth identification. Additional sensors are also available integrated in different types of nodes. Experiments in real conditions have been performed, both for separate sensors (Bluetooth, ultrasound and laser), and for the whole system, showing the feasibility of this approach.

Advanced Models and Algorithms for Self-Similar IP Network Traffic Simulation and Performance Analysis

NASA Astrophysics Data System (ADS)

Radev, Dimitar; Lokshina, Izabella

2010-11-01

The paper examines self-similar (or fractal) properties of real communication network traffic data over a wide range of time scales. These self-similar properties are very different from the properties of traditional models based on Poisson and Markov-modulated Poisson processes. Advanced fractal models of sequentional generators and fixed-length sequence generators, and efficient algorithms that are used to simulate self-similar behavior of IP network traffic data are developed and applied. Numerical examples are provided; and simulation results are obtained and analyzed.

Modelling and optimization of rotary parking system

NASA Astrophysics Data System (ADS)

Skrzyniowski, A.

2016-09-01

The increasing number of vehicles in cities is a cause of traffic congestion which interrupts the smooth traffic flow. The established EU policy underlines the importance of restoring spaces for pedestrian traffic and public communication. The overall vehicle parking process in some parts of a city takes so much time that it has a negative impact on the environment. This article presents different kinds of solution with special focus on the rotary parking system (PO). This article is based on a project realized at the Faculty of Mechanical Engineering of Cracow University of Technology.

Technical and economic feasibility of integrated video service by satellite

NASA Technical Reports Server (NTRS)

Price, Kent M.; Garlow, R. K.; Henderson, T. R.; Kwan, Robert K.; White, L. W.

1992-01-01

The trends and roles of satellite based video services in the year 2010 time frame are examined based on an overall network and service model for that period. Emphasis is placed on point to point and multipoint service, but broadcast could also be accommodated. An estimate of the video traffic is made and the service and general network requirements are identified. User charges are then estimated based on several usage scenarios. In order to accommodate these traffic needs, a 28 spot beam satellite architecture with on-board processing and signal mixing is suggested.

Analysis of in-trail following dynamics of CDTI-equipped aircraft. [Cockpit Displays of Traffic Information

NASA Technical Reports Server (NTRS)

Sorensen, J. A.; Goka, T.

1982-01-01

In connection with the necessity to provide greater terminal area capacity, attention is given to approaches in which the required increase in capacity will be obtained by making use of more automation and by involving the pilot to a larger degree in the air traffic control (ATC) process. It was recommended that NASA should make extensive use of its research aircraft and cockpit simulators to assist the FAA in examining the capabilities and limitations of cockpit displays of traffic information (CDTI). A program was organized which utilizes FAA ATC (ground-based) simulators and NASA aircraft and associated cockpit simulators in a research project which explores applications of the CDTI system. The present investigation is concerned with several questions related to the CDTI-based terminal area traffic tactical control concepts. Attention is given to longitudinal separation criteria, a longitudinal following model, longitudinal capture, combined longitudinal/vertical control, and lateral control.

Optimization technique for rolled edge control process based on the acentric tool influence functions.

PubMed

Du, Hang; Song, Ci; Li, Shengyi; Xu, Mingjin; Peng, Xiaoqiang

2017-05-20

In the process of computer controlled optical surfacing (CCOS), the uncontrollable rolled edge restricts further improvements of the machining accuracy and efficiency. Two reasons are responsible for the rolled edge problem during small tool polishing. One is that the edge areas cannot be processed because of the orbit movement. The other is that changing the tool influence function (TIF) is difficult to compensate for in algorithms, since pressure step appears in the local pressure distribution at the surface edge. In this paper, an acentric tool influence function (A-TIF) is designed to remove the rolled edge after CCOS polishing. The model of A-TIF is analyzed theoretically, and a control point translation dwell time algorithm is used to verify that the full aperture of the workpiece can be covered by the peak removal point of the tool influence functions. Thus, surface residual error in the full aperture can be effectively corrected. Finally, the experiments are carried out. Two fused silica glass samples of 100  mm×100  mm are polished by traditional CCOS and the A-TIF method, respectively. The rolled edge was clearly produced in the sample polished by the traditional CCOS, while residual errors do not show this problem the sample polished by the A-TIF method. Therefore, the rolled edge caused by the traditional CCOS process is successfully suppressed during the A-TIF process. The ability to suppress the rolled edge of the designed A-TIF has been confirmed.

Determination system for solar cell layout in traffic light network using dominating set

NASA Astrophysics Data System (ADS)

Eka Yulia Retnani, Windi; Fambudi, Brelyanes Z.; Slamin

2018-04-01

Graph Theory is one of the fields in Mathematics that solves discrete problems. In daily life, the applications of Graph Theory are used to solve various problems. One of the topics in the Graph Theory that is used to solve the problem is the dominating set. The concept of dominating set is used, for example, to locate some objects systematically. In this study, the dominating set are used to determine the dominating points for solar panels, where the vertex represents the traffic light point and the edge represents the connection between the points of the traffic light. To search the dominating points for solar panels using the greedy algorithm. This algorithm is used to determine the location of solar panel. This research produced applications that can determine the location of solar panels with optimal results, that is, the minimum dominating points.

A new method of edge detection for object recognition

USGS Publications Warehouse

Maddox, Brian G.; Rhew, Benjamin

2004-01-01

Traditional edge detection systems function by returning every edge in an input image. This can result in a large amount of clutter and make certain vectorization algorithms less accurate. Accuracy problems can then have a large impact on automated object recognition systems that depend on edge information. A new method of directed edge detection can be used to limit the number of edges returned based on a particular feature. This results in a cleaner image that is easier for vectorization. Vectorized edges from this process could then feed an object recognition system where the edge data would also contain information as to what type of feature it bordered.

Robust foreground detection: a fusion of masked grey world, probabilistic gradient information and extended conditional random field approach.

PubMed

Zulkifley, Mohd Asyraf; Moran, Bill; Rawlinson, David

2012-01-01

Foreground detection has been used extensively in many applications such as people counting, traffic monitoring and face recognition. However, most of the existing detectors can only work under limited conditions. This happens because of the inability of the detector to distinguish foreground and background pixels, especially in complex situations. Our aim is to improve the robustness of foreground detection under sudden and gradual illumination change, colour similarity issue, moving background and shadow noise. Since it is hard to achieve robustness using a single model, we have combined several methods into an integrated system. The masked grey world algorithm is introduced to handle sudden illumination change. Colour co-occurrence modelling is then fused with the probabilistic edge-based background modelling. Colour co-occurrence modelling is good in filtering moving background and robust to gradual illumination change, while an edge-based modelling is used for solving a colour similarity problem. Finally, an extended conditional random field approach is used to filter out shadow and afterimage noise. Simulation results show that our algorithm performs better compared to the existing methods, which makes it suitable for higher-level applications.

Understanding the topological characteristics and flow complexity of urban traffic congestion

NASA Astrophysics Data System (ADS)

Wen, Tzai-Hung; Chin, Wei-Chien-Benny; Lai, Pei-Chun

2017-05-01

For a growing number of developing cities, the capacities of streets cannot meet the rapidly growing demand of cars, causing traffic congestion. Understanding the spatial-temporal process of traffic flow and detecting traffic congestion are important issues associated with developing sustainable urban policies to resolve congestion. Therefore, the objective of this study is to propose a flow-based ranking algorithm for investigating traffic demands in terms of the attractiveness of street segments and flow complexity of the street network based on turning probability. Our results show that, by analyzing the topological characteristics of streets and volume data for a small fraction of street segments in Taipei City, the most congested segments of the city were identified successfully. The identified congested segments are significantly close to the potential congestion zones, including the officially announced most congested streets, the segments with slow moving speeds at rush hours, and the areas near significant landmarks. The identified congested segments also captured congestion-prone areas concentrated in the business districts and industrial areas of the city. Identifying the topological characteristics and flow complexity of traffic congestion provides network topological insights for sustainable urban planning, and these characteristics can be used to further understand congestion propagation.

Big-data-based edge biomarkers: study on dynamical drug sensitivity and resistance in individuals.

PubMed

Zeng, Tao; Zhang, Wanwei; Yu, Xiangtian; Liu, Xiaoping; Li, Meiyi; Chen, Luonan

2016-07-01

Big-data-based edge biomarker is a new concept to characterize disease features based on biomedical big data in a dynamical and network manner, which also provides alternative strategies to indicate disease status in single samples. This article gives a comprehensive review on big-data-based edge biomarkers for complex diseases in an individual patient, which are defined as biomarkers based on network information and high-dimensional data. Specifically, we firstly introduce the sources and structures of biomedical big data accessible in public for edge biomarker and disease study. We show that biomedical big data are typically 'small-sample size in high-dimension space', i.e. small samples but with high dimensions on features (e.g. omics data) for each individual, in contrast to traditional big data in many other fields characterized as 'large-sample size in low-dimension space', i.e. big samples but with low dimensions on features. Then, we demonstrate the concept, model and algorithm for edge biomarkers and further big-data-based edge biomarkers. Dissimilar to conventional biomarkers, edge biomarkers, e.g. module biomarkers in module network rewiring-analysis, are able to predict the disease state by learning differential associations between molecules rather than differential expressions of molecules during disease progression or treatment in individual patients. In particular, in contrast to using the information of the common molecules or edges (i.e.molecule-pairs) across a population in traditional biomarkers including network and edge biomarkers, big-data-based edge biomarkers are specific for each individual and thus can accurately evaluate the disease state by considering the individual heterogeneity. Therefore, the measurement of big data in a high-dimensional space is required not only in the learning process but also in the diagnosing or predicting process of the tested individual. Finally, we provide a case study on analyzing the temporal expression data from a malaria vaccine trial by big-data-based edge biomarkers from module network rewiring-analysis. The illustrative results show that the identified module biomarkers can accurately distinguish vaccines with or without protection and outperformed previous reported gene signatures in terms of effectiveness and efficiency. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Node-based measures of connectivity in genetic networks.

PubMed

Koen, Erin L; Bowman, Jeff; Wilson, Paul J

2016-01-01

At-site environmental conditions can have strong influences on genetic connectivity, and in particular on the immigration and settlement phases of dispersal. However, at-site processes are rarely explored in landscape genetic analyses. Networks can facilitate the study of at-site processes, where network nodes are used to model site-level effects. We used simulated genetic networks to compare and contrast the performance of 7 node-based (as opposed to edge-based) genetic connectivity metrics. We simulated increasing node connectivity by varying migration in two ways: we increased the number of migrants moving between a focal node and a set number of recipient nodes, and we increased the number of recipient nodes receiving a set number of migrants. We found that two metrics in particular, the average edge weight and the average inverse edge weight, varied linearly with simulated connectivity. Conversely, node degree was not a good measure of connectivity. We demonstrated the use of average inverse edge weight to describe the influence of at-site habitat characteristics on genetic connectivity of 653 American martens (Martes americana) in Ontario, Canada. We found that highly connected nodes had high habitat quality for marten (deep snow and high proportions of coniferous and mature forest) and were farther from the range edge. We recommend the use of node-based genetic connectivity metrics, in particular, average edge weight or average inverse edge weight, to model the influences of at-site habitat conditions on the immigration and settlement phases of dispersal. © 2015 John Wiley & Sons Ltd.

Enhanced TCAS 2/CDTI traffic Sensor digital simulation model and program description

NASA Technical Reports Server (NTRS)

Goka, T.

1984-01-01

Digital simulation models of enhanced TCAS 2/CDTI traffic sensors are developed, based on actual or projected operational and performance characteristics. Two enhanced Traffic (or Threat) Alert and Collision Avoidance Systems are considered. A digital simulation program is developed in FORTRAN. The program contains an executive with a semireal time batch processing capability. The simulation program can be interfaced with other modules with a minimum requirement. Both the traffic sensor and CAS logic modules are validated by means of extensive simulation runs. Selected validation cases are discussed in detail, and capabilities and limitations of the actual and simulated systems are noted. The TCAS systems are not specifically intended for Cockpit Display of Traffic Information (CDTI) applications. These systems are sufficiently general to allow implementation of CDTI functions within the real systems' constraints.

Directional filtering for block recovery using wavelet features

NASA Astrophysics Data System (ADS)

Hyun, Seung H.; Eom, Il K.; Kim, Yoo S.

2005-07-01

When images compressed with block-based compression techniques are transmitted over a noisy channel, unexpected block losses occur. Conventional methods that do not consider edge directions can cause blocked blurring artifacts. In this paper, we present a post-processing-based block recovery scheme using Haar wavelet features. The adaptive selection of neighboring blocks is performed based on the energy of wavelet subbands (EWS) and difference between DC values (DDC). The lost blocks are recovered by linear interpolation in the spatial domain using selected blocks. The method using only EWS performs well for horizontal and vertical edges, but not as well for diagonal edges. Conversely, only using DDC performs well for diagonal edges with the exception of line- or roof-type edge profiles. Therefore, we combine EWS and DDC for better results. The proposed directional recovery method is effective for the strong edge because exploit the varying neighboring blocks adaptively according to the edges and the directional information in the image. The proposed method outperforms the previous methods that used only fixed blocks.

A novel cloning template designing method by using an artificial bee colony algorithm for edge detection of CNN based imaging sensors.

PubMed

Parmaksızoğlu, Selami; Alçı, Mustafa

2011-01-01

Cellular Neural Networks (CNNs) have been widely used recently in applications such as edge detection, noise reduction and object detection, which are among the main computer imaging processes. They can also be realized as hardware based imaging sensors. The fact that hardware CNN models produce robust and effective results has attracted the attention of researchers using these structures within image sensors. Realization of desired CNN behavior such as edge detection can be achieved by correctly setting a cloning template without changing the structure of the CNN. To achieve different behaviors effectively, designing a cloning template is one of the most important research topics in this field. In this study, the edge detecting process that is used as a preliminary process for segmentation, identification and coding applications is conducted by using CNN structures. In order to design the cloning template of goal-oriented CNN architecture, an Artificial Bee Colony (ABC) algorithm which is inspired from the foraging behavior of honeybees is used and the performance analysis of ABC for this application is examined with multiple runs. The CNN template generated by the ABC algorithm is tested by using artificial and real test images. The results are subjectively and quantitatively compared with well-known classical edge detection methods, and other CNN based edge detector cloning templates available in the imaging literature. The results show that the proposed method is more successful than other methods.

A Novel Cloning Template Designing Method by Using an Artificial Bee Colony Algorithm for Edge Detection of CNN Based Imaging Sensors

PubMed Central

Parmaksızoğlu, Selami; Alçı, Mustafa

2011-01-01

Cellular Neural Networks (CNNs) have been widely used recently in applications such as edge detection, noise reduction and object detection, which are among the main computer imaging processes. They can also be realized as hardware based imaging sensors. The fact that hardware CNN models produce robust and effective results has attracted the attention of researchers using these structures within image sensors. Realization of desired CNN behavior such as edge detection can be achieved by correctly setting a cloning template without changing the structure of the CNN. To achieve different behaviors effectively, designing a cloning template is one of the most important research topics in this field. In this study, the edge detecting process that is used as a preliminary process for segmentation, identification and coding applications is conducted by using CNN structures. In order to design the cloning template of goal-oriented CNN architecture, an Artificial Bee Colony (ABC) algorithm which is inspired from the foraging behavior of honeybees is used and the performance analysis of ABC for this application is examined with multiple runs. The CNN template generated by the ABC algorithm is tested by using artificial and real test images. The results are subjectively and quantitatively compared with well-known classical edge detection methods, and other CNN based edge detector cloning templates available in the imaging literature. The results show that the proposed method is more successful than other methods. PMID:22163903

Ultrasonic Vibration Assisted Grinding of Bio-ceramic Materials: Modeling, Simulation, and Experimental Investigations on Edge Chipping

NASA Astrophysics Data System (ADS)

Tesfay, Hayelom D.

Bio-ceramics are those engineered materials that find their applications in the field of biomedical engineering or medicine. They have been widely used in dental restorations, repairing bones, joint replacements, pacemakers, kidney dialysis machines, and respirators. etc. due to their physico-chemical properties, such as excellent corrosion resistance, good biocompatibility, high strength and high wear resistance. Because of their inherent brittleness and hardness nature they are difficult to machine to exact sizes and dimensions. Abrasive machining processes such as grinding is one of the most widely used manufacturing processes for bioceramics. However, the principal technical challenge resulted from these machining is edge chipping. Edge chipping is a common edge failure commonly observed during the machining of bio-ceramic materials. The presence of edge chipping on bio-ceramic products affects dimensional accuracy, increases manufacturing cost, hider their industrial applications and causes potential failure during service. To overcome these technological challenges, a new ultrasonic vibration-assisted grinding (UVAG) manufacturing method has been developed and employed in this research. The ultimate aim of this study is to develop a new cost-effective manufacturing process relevant to eliminate edge chippings in grinding of bio-ceramic materials. In this dissertation, comprehensive investigations will be carried out using experimental, theoretical, and numerical approaches to evaluate the effect of ultrasonic vibrations on edge chipping of bioceramics. Moreover, effects of nine input variables (static load, vibration frequency, grinding depth, spindle speed, grinding distance, tool speed, grain size, grain number, and vibration amplitude) on edge chipping will be studied based on the developed models. Following a description of previous research and existing approaches, a series of experimental tests on three bio-ceramic materials (Lava, partially fired Lava, and Alumina) were conducted. Based on the experimental results, analytical models for UVAG and CG (conventional grinding without ultrasonic vibration) processes were developed. As for the numerical study, an extended finite element method (XFEM) based on Virtual Crack Closure Technique (VCCT) in ABAQUS was used to model the formation of edge chippings both for UVAG and CG processes. The experimental results are compared against the numerical FEA and the analytical models. The experimental, theoretical, and computational simulation results revealed that the edge chipping size of bioceramics can be significantly reduced with the assistance of ultrasonic vibration. The investigation procedures and the results obtained in this dissertation would be used as a reference and practical guidance for choosing reasonable process variables as well as designing mathematical (analytical and numerical) models in manufacturing industries and academic institutions when the edge chippings of brittle materials are expected to be controlled.

Nonlinear relative-proportion-based route adjustment process for day-to-day traffic dynamics: modeling, equilibrium and stability analysis

NASA Astrophysics Data System (ADS)

Zhu, Wenlong; Ma, Shoufeng; Tian, Junfang; Li, Geng

2016-11-01

Travelers' route adjustment behaviors in a congested road traffic network are acknowledged as a dynamic game process between them. Existing Proportional-Switch Adjustment Process (PSAP) models have been extensively investigated to characterize travelers' route choice behaviors; PSAP has concise structure and intuitive behavior rule. Unfortunately most of which have some limitations, i.e., the flow over adjustment problem for the discrete PSAP model, the absolute cost differences route adjustment problem, etc. This paper proposes a relative-Proportion-based Route Adjustment Process (rePRAP) maintains the advantages of PSAP and overcomes these limitations. The rePRAP describes the situation that travelers on higher cost route switch to those with lower cost at the rate that is unilaterally depended on the relative cost differences between higher cost route and its alternatives. It is verified to be consistent with the principle of the rational behavior adjustment process. The equivalence among user equilibrium, stationary path flow pattern and stationary link flow pattern is established, which can be applied to judge whether a given network traffic flow has reached UE or not by detecting the stationary or non-stationary state of link flow pattern. The stability theorem is proved by the Lyapunov function approach. A simple example is tested to demonstrate the effectiveness of the rePRAP model.

Network Exploration and Vulnerability Assessment Using a Combined Blackbox and Whitebox Analysis Approach

DTIC Science & Technology

2010-03-01

Employ NetFlow on Edge Router ......................................... 45 E. IMPLEMENT AN INTEGRATED VULNERABILITY ASSESSMENT. 48 1. Conduct...45 Figure 18. Netflow Information on Unauthorized Connections ............................ 46 Figure 19. Algorithm for Detecting...indicating that an attack has being initiated from this port. Figure 17. Information on Traffic Generated by Suspicious Host 3. Employ NetFlow

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

PubMed

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

2018-04-17

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

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

PubMed Central

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

2018-01-01

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

Air Traffic Controller Working Memory: Considerations in Air Traffic Control Tactical Operations

DTIC Science & Technology

1993-09-01

INFORMATION PROCESSING SYSTEM 3 2. AIR TRAFFIC CONTROLLER MEMORY 5 2.1 MEMORY CODES 6 21.1 Visual Codes 7 2.1.2 Phonetic Codes 7 2.1.3 Semantic Codes 8...raise an awareness of the memory re- quirements of ATC tactical operations by presenting information on working memory processes that are relevant to...working v memory permeates every aspect of the controller’s ability to process air traffic information and control live traffic. The

Endocytosis-dependent coordination of multiple actin regulators is required for wound healing

PubMed Central

Matsubayashi, Yutaka; Coulson-Gilmer, Camilla

2015-01-01

The ability to heal wounds efficiently is essential for life. After wounding of an epithelium, the cells bordering the wound form dynamic actin protrusions and/or a contractile actomyosin cable, and these actin structures drive wound closure. Despite their importance in wound healing, the molecular mechanisms that regulate the assembly of these actin structures at wound edges are not well understood. In this paper, using Drosophila melanogaster embryos, we demonstrate that Diaphanous, SCAR, and WASp play distinct but overlapping roles in regulating actin assembly during wound healing. Moreover, we show that endocytosis is essential for wound edge actin assembly and wound closure. We identify adherens junctions (AJs) as a key target of endocytosis during wound healing and propose that endocytic remodeling of AJs is required to form “signaling centers” along the wound edge that control actin assembly. We conclude that coordination of actin assembly, AJ remodeling, and membrane traffic is required for the construction of a motile leading edge during wound healing. PMID:26216900

Information theoretic analysis of linear shift-invariant edge-detection operators

NASA Astrophysics Data System (ADS)

Jiang, Bo; Rahman, Zia-ur

2012-06-01

Generally, the designs of digital image processing algorithms and image gathering devices remain separate. Consequently, the performance of digital image processing algorithms is evaluated without taking into account the influences by the image gathering process. However, experiments show that the image gathering process has a profound impact on the performance of digital image processing and the quality of the resulting images. Huck et al. proposed one definitive theoretic analysis of visual communication channels, where the different parts, such as image gathering, processing, and display, are assessed in an integrated manner using Shannon's information theory. We perform an end-to-end information theory based system analysis to assess linear shift-invariant edge-detection algorithms. We evaluate the performance of the different algorithms as a function of the characteristics of the scene and the parameters, such as sampling, additive noise etc., that define the image gathering system. The edge-detection algorithm is regarded as having high performance only if the information rate from the scene to the edge image approaches its maximum possible. This goal can be achieved only by jointly optimizing all processes. Our information-theoretic assessment provides a new tool that allows us to compare different linear shift-invariant edge detectors in a common environment.

Performance Testing of GPU-Based Approximate Matching Algorithm on Network Traffic

DTIC Science & Technology

2015-03-01

Defense Department’s use. vi THIS PAGE INTENTIONALLY LEFT BLANK vii TABLE OF CONTENTS I.  INTRODUCTION...22  D.  GENERATING DIGESTS ............................................................................23  1.  Reference...the-shelf GPU Graphical Processing Unit GPGPU General -Purpose Graphic Processing Unit HBSS Host-Based Security System HIPS Host Intrusion

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.

Two-Dimensional Edge Detection by Guided Mode Resonant Metasurface

NASA Astrophysics Data System (ADS)

Saba, Amirhossein; Tavakol, Mohammad Reza; Karimi-Khoozani, Parisa; Khavasi, Amin

2018-05-01

In this letter, a new approach to perform edge detection is presented using an all-dielectric CMOS-compatible metasurface. The design is based on guided-mode resonance which provides a high quality factor resonance to make the edge detection experimentally realizable. The proposed structure that is easy to fabricate, can be exploited for detection of edges in two dimensions due to its symmetry. Also, the trade-off between gain and resolution of edge detection is discussed which can be adjusted by appropriate design parameters. The proposed edge detector has also the potential to be used in ultrafast analog computing and image processing.

Ultrasound image edge detection based on a novel multiplicative gradient and Canny operator.

PubMed

Zheng, Yinfei; Zhou, Yali; Zhou, Hao; Gong, Xiaohong

2015-07-01

To achieve the fast and accurate segmentation of ultrasound image, a novel edge detection method for speckle noised ultrasound images was proposed, which was based on the traditional Canny and a novel multiplicative gradient operator. The proposed technique combines a new multiplicative gradient operator of non-Newtonian type with the traditional Canny operator to generate the initial edge map, which is subsequently optimized by the following edge tracing step. To verify the proposed method, we compared it with several other edge detection methods that had good robustness to noise, with experiments on the simulated and in vivo medical ultrasound image. Experimental results showed that the proposed algorithm has higher speed for real-time processing, and the edge detection accuracy could be 75% or more. Thus, the proposed method is very suitable for fast and accurate edge detection of medical ultrasound images. © The Author(s) 2014.

Understanding the T2 traffic in CMS during Run-1

NASA Astrophysics Data System (ADS)

T, Wildish

2015-12-01

In the run-up to Run-1 CMS was operating its facilities according to the MONARC model, where data-transfers were strictly hierarchical in nature. Direct transfers between Tier-2 nodes was excluded, being perceived as operationally intensive and risky in an era where the network was expected to be a major source of errors. By the end of Run-1 wide-area networks were more capable and stable than originally anticipated. The original data-placement model was relaxed, and traffic was allowed between Tier-2 nodes. Tier-2 to Tier-2 traffic in 2012 already exceeded the amount of Tier-2 to Tier-1 traffic, so it clearly has the potential to become important in the future. Moreover, while Tier-2 to Tier-1 traffic is mostly upload of Monte Carlo data, the Tier-2 to Tier-2 traffic represents data moved in direct response to requests from the physics analysis community. As such, problems or delays there are more likely to have a direct impact on the user community. Tier-2 to Tier-2 traffic may also traverse parts of the WAN that are at the 'edge' of our network, with limited network capacity or reliability compared to, say, the Tier-0 to Tier-1 traffic which goes the over LHCOPN network. CMS is looking to exploit technologies that allow us to interact with the network fabric so that it can manage our traffic better for us, this we hope to achieve before the end of Run-2. Tier-2 to Tier-2 traffic would be the most interesting use-case for such traffic management, precisely because it is close to the users' analysis and far from the 'core' network infrastructure. As such, a better understanding of our Tier-2 to Tier-2 traffic is important. Knowing the characteristics of our data-flows can help us place our data more intelligently. Knowing how widely the data moves can help us anticipate the requirements for network capacity, and inform the dynamic data placement algorithms we expect to have in place for Run-2. This paper presents an analysis of the CMS Tier-2 traffic during Run 1.

Evaluation of a Traffic Sign Detector by Synthetic Image Data for Advanced Driver Assistance Systems

NASA Astrophysics Data System (ADS)

Hanel, A.; Kreuzpaintner, D.; Stilla, U.

2018-05-01

Recently, several synthetic image datasets of street scenes have been published. These datasets contain various traffic signs and can therefore be used to train and test machine learning-based traffic sign detectors. In this contribution, selected datasets are compared regarding ther applicability for traffic sign detection. The comparison covers the process to produce the synthetic images and addresses the virtual worlds, needed to produce the synthetic images, and their environmental conditions. The comparison covers variations in the appearance of traffic signs and the labeling strategies used for the datasets, as well. A deep learning traffic sign detector is trained with multiple training datasets with different ratios between synthetic and real training samples to evaluate the synthetic SYNTHIA dataset. A test of the detector on real samples only has shown that an overall accuracy and ROC AUC of more than 95 % can be achieved for both a small rate of synthetic samples and a large rate of synthetic samples in the training dataset.

Finite Element Analysis of the Implantation Process of Overlapping Stents

PubMed Central

Xu, Jiang; Yang, Jie; Sohrabi, Salman; Zhou, Yihua; Liu, Yaling

2017-01-01

Overlapping stents are widely used in vascular stent surgeries. However, the rate of stent fractures (SF) and in-stent restenosis (ISR) after using overlapping stents is higher than that of single stent implantations. Published studies investigating the nature of overlapping stents rely primarily on medical images, which can only reveal the effect of the surgery without providing insights into how stent overlap influences the implantation process. In this paper, a finite element analysis of the overlapping stent implantation process was performed to study the interaction between overlapping stents. Four different cases, based on three typical stent overlap modes and two classical balloons, were investigated. The results showed that overlapping contact patterns among struts were edge-to-edge, edge-to-surface, and noncontact. These were mainly induced by the nonuniform deformation of the stent in the radial direction and stent tubular structures. Meanwhile, the results also revealed that the contact pressure was concentrated in the edge of overlapping struts. During the stent overlap process, the contact pattern was primarily edge-to-edge contact at the beginning and edge-to-surface contact as the contact pressure increased. The interactions between overlapping stents suggest that the failure of overlapping stents frequently occurs along stent edges, which agrees with the previous experimental research regarding the safety of overlapping stents. This paper also provides a fundamental understanding of the mechanical properties of overlapping stents. PMID:28690712

2Loud?: Community mapping of exposure to traffic noise with mobile phones.

PubMed

Leao, Simone; Ong, Kok-Leong; Krezel, Adam

2014-10-01

Despite ample medical evidence of the adverse impacts of traffic noise on health, most policies for traffic noise management are arbitrary or incomplete, resulting in serious social and economic impacts. Surprisingly, there is limited information about citizen's exposure to traffic noise worldwide. This paper presents the 2Loud? mobile phone application, developed and tested as a methodology to monitor, assess and map the level of exposure to traffic noise of citizens with focus on the night period and indoor locations, since sleep disturbance is one of the major triggers for ill health related to traffic noise. Based on a community participation experiment using the 2Loud? mobile phone application in a region close to freeways in Australia, the results of this research indicates a good level of accuracy for the noise monitoring by mobile phones and also demonstrates significant levels of indoor night exposure to traffic noise in the study area. The proposed methodology, through the data produced and the participatory process involved, can potentially assist in planning and management towards healthier urban environments.

High-performance Chinese multiclass traffic sign detection via coarse-to-fine cascade and parallel support vector machine detectors

NASA Astrophysics Data System (ADS)

Chang, Faliang; Liu, Chunsheng

2017-09-01

The high variability of sign colors and shapes in uncontrolled environments has made the detection of traffic signs a challenging problem in computer vision. We propose a traffic sign detection (TSD) method based on coarse-to-fine cascade and parallel support vector machine (SVM) detectors to detect Chinese warning and danger traffic signs. First, a region of interest (ROI) extraction method is proposed to extract ROIs using color contrast features in local regions. The ROI extraction can reduce scanning regions and save detection time. For multiclass TSD, we propose a structure that combines a coarse-to-fine cascaded tree with a parallel structure of histogram of oriented gradients (HOG) + SVM detectors. The cascaded tree is designed to detect different types of traffic signs in a coarse-to-fine process. The parallel HOG + SVM detectors are designed to do fine detection of different types of traffic signs. The experiments demonstrate the proposed TSD method can rapidly detect multiclass traffic signs with different colors and shapes in high accuracy.

A vision-based approach for tramway rail extraction

NASA Astrophysics Data System (ADS)

Zwemer, Matthijs H.; van de Wouw, Dennis W. J. M.; Jaspers, Egbert; Zinger, Sveta; de With, Peter H. N.

2015-03-01

The growing traffic density in cities fuels the desire for collision assessment systems on public transportation. For this application, video analysis is broadly accepted as a cornerstone. For trams, the localization of tramway tracks is an essential ingredient of such a system, in order to estimate a safety margin for crossing traffic participants. Tramway-track detection is a challenging task due to the urban environment with clutter, sharp curves and occlusions of the track. In this paper, we present a novel and generic system to detect the tramway track in advance of the tram position. The system incorporates an inverse perspective mapping and a-priori geometry knowledge of the rails to find possible track segments. The contribution of this paper involves the creation of a new track reconstruction algorithm which is based on graph theory. To this end, we define track segments as vertices in a graph, in which edges represent feasible connections. This graph is then converted to a max-cost arborescence graph, and the best path is selected according to its location and additional temporal information based on a maximum a-posteriori estimate. The proposed system clearly outperforms a railway-track detector. Furthermore, the system performance is validated on 3,600 manually annotated frames. The obtained results are promising, where straight tracks are found in more than 90% of the images and complete curves are still detected in 35% of the cases.

A Wireless Sensor Network for Urban Traffic Characterization and Trend Monitoring

PubMed Central

Fernández-Lozano, J.J.; Martín-Guzmán, Miguel; Martín-Ávila, Juan; García-Cerezo, A.

2015-01-01

Sustainable mobility requires a better management of the available infrastructure resources. To achieve this goal, it is necessary to obtain accurate data about road usage, in particular in urban areas. Although a variety of sensor alternates for urban traffic exist, they usually require extensive investments in the form of construction works for installation, processing means, etc. Wireless Sensor Networks (WSN) are an alternative to acquire urban traffic data, allowing for flexible, easy deployment. Together with the use of the appropriate sensors, like Bluetooth identification, and associate processing, WSN can provide the means to obtain in real time data like the origin-destination matrix, a key tool for trend monitoring which previously required weeks or months to be completed. This paper presents a system based on WSN designed to characterize urban traffic, particularly traffic trend monitoring through the calculation of the origin-destination matrix in real time by using Bluetooth identification. Additional sensors are also available integrated in different types of nodes. Experiments in real conditions have been performed, both for separate sensors (Bluetooth, ultrasound and laser), and for the whole system, showing the feasibility of this approach. PMID:26501278

Bicycle-vehicle interactions at mid-sections of mixed traffic streets: Examining passing distance and bicycle comfort perception.

PubMed

Apasnore, Peter; Ismail, Karim; Kassim, Ali

2017-09-01

This paper studies the relevant factors in mixed urban traffic that may impact the lateral spacing between bicycles and vehicles (passing distance, PD), and their resulting effect on a bicyclists' comfort based on a study of six sites in Ottawa, Canada. The observations are: [i] the average position of bicycles from the curb is 0.57m, and lesser (i.e. 0.35m) in the presence of parking; [ii] 90% of passes exceed 1.23m; [iii] PD is positively correlated with motor vehicle speed, lane width, and bicycle position from adjacent curb edge line, whiles inversely correlated to ambient traffic density and bicycle speed; [iv] motor vehicle speed has the highest prediction of PD variability; [v] PD and ambient traffic density (ATD) are found to be the most important factors to a bicyclists' comfort perception (BCP). Two linear regression models for PD and BCP were developed and significant variables are identified as: motor vehicle speed, bicycle speed, ATD, number of lanes, and lane width. The presence or absence of a grade slope is found to be significant to the PD model and not to BCP. The models both exhibit limited predictive ability, however residual plots and significance of included variables are indicative of correct assumptions for the models. It is recommended that speed calming, sharrows, road signs instructing road sharing, and educating road users against "dooring" crashes be considered in improving road sharing, especially for narrow lanes (i.e. less than 3.6m) and lanes wider than 4.5m. It is also prudent for designers to avoid installing parking zones on narrow shared roads. Copyright © 2017 Elsevier Ltd. All rights reserved.

Extraction of edge-based and region-based features for object recognition

NASA Astrophysics Data System (ADS)

Coutts, Benjamin; Ravi, Srinivas; Hu, Gongzhu; Shrikhande, Neelima

1993-08-01

One of the central problems of computer vision is object recognition. A catalogue of model objects is described as a set of features such as edges and surfaces. The same features are extracted from the scene and matched against the models for object recognition. Edges and surfaces extracted from the scenes are often noisy and imperfect. In this paper algorithms are described for improving low level edge and surface features. Existing edge extraction algorithms are applied to the intensity image to obtain edge features. Initial edges are traced by following directions of the current contour. These are improved by using corresponding depth and intensity information for decision making at branch points. Surface fitting routines are applied to the range image to obtain planar surface patches. An algorithm of region growing is developed that starts with a coarse segmentation and uses quadric surface fitting to iteratively merge adjacent regions into quadric surfaces based on approximate orthogonal distance regression. Surface information obtained is returned to the edge extraction routine to detect and remove fake edges. This process repeats until no more merging or edge improvement can take place. Both synthetic (with Gaussian noise) and real images containing multiple object scenes have been tested using the merging criteria. Results appeared quite encouraging.

Edge detection for optical synthetic aperture based on deep neural network

NASA Astrophysics Data System (ADS)

Tan, Wenjie; Hui, Mei; Liu, Ming; Kong, Lingqin; Dong, Liquan; Zhao, Yuejin

2017-09-01

Synthetic aperture optics systems can meet the demands of the next-generation space telescopes being lighter, larger and foldable. However, the boundaries of segmented aperture systems are much more complex than that of the whole aperture. More edge regions mean more imaging edge pixels, which are often mixed and discretized. In order to achieve high-resolution imaging, it is necessary to identify the gaps between the sub-apertures and the edges of the projected fringes. In this work, we introduced the algorithm of Deep Neural Network into the edge detection of optical synthetic aperture imaging. According to the detection needs, we constructed image sets by experiments and simulations. Based on MatConvNet, a toolbox of MATLAB, we ran the neural network, trained it on training image set and tested its performance on validation set. The training was stopped when the test error on validation set stopped declining. As an input image is given, each intra-neighbor area around the pixel is taken into the network, and scanned pixel by pixel with the trained multi-hidden layers. The network outputs make a judgment on whether the center of the input block is on edge of fringes. We experimented with various pre-processing and post-processing techniques to reveal their influence on edge detection performance. Compared with the traditional algorithms or their improvements, our method makes decision on a much larger intra-neighbor, and is more global and comprehensive. Experiments on more than 2,000 images are also given to prove that our method outperforms classical algorithms in optical images-based edge detection.

Image flows and one-liner graphical image representation.

PubMed

Makhervaks, Vadim; Barequet, Gill; Bruckstein, Alfred

2002-10-01

This paper introduces a novel graphical image representation consisting of a single curve-the one-liner. The first step of the algorithm involves the detection and ranking of image edges. A new edge exploration technique is used to perform both tasks simultaneously. This process is based on image flows. It uses a gradient vector field and a new operator to explore image edges. Estimation of the derivatives of the image is performed by using local Taylor expansions in conjunction with a weighted least-squares method. This process finds all the possible image edges without any pruning, and collects information that allows the edges found to be prioritized. This enables the most important edges to be selected to form a skeleton of the representation sought. The next step connects the selected edges into one continuous curve-the one-liner. It orders the selected edges and determines the curves connecting them. These two problems are solved separately. Since the abstract graph setting of the first problem is NP-complete, we reduce it to a variant of the traveling salesman problem and compute an approximate solution to it. We solve the second problem by using Dijkstra's shortest-path algorithm. The full software implementation for the entire one-liner determination process is available.

Information theoretic analysis of edge detection in visual communication

NASA Astrophysics Data System (ADS)

Jiang, Bo; Rahman, Zia-ur

2010-08-01

Generally, the designs of digital image processing algorithms and image gathering devices remain separate. Consequently, the performance of digital image processing algorithms is evaluated without taking into account the artifacts introduced into the process by the image gathering process. However, experiments show that the image gathering process profoundly impacts the performance of digital image processing and the quality of the resulting images. Huck et al. proposed one definitive theoretic analysis of visual communication channels, where the different parts, such as image gathering, processing, and display, are assessed in an integrated manner using Shannon's information theory. In this paper, we perform an end-to-end information theory based system analysis to assess edge detection methods. We evaluate the performance of the different algorithms as a function of the characteristics of the scene, and the parameters, such as sampling, additive noise etc., that define the image gathering system. The edge detection algorithm is regarded to have high performance only if the information rate from the scene to the edge approaches the maximum possible. This goal can be achieved only by jointly optimizing all processes. People generally use subjective judgment to compare different edge detection methods. There is not a common tool that can be used to evaluate the performance of the different algorithms, and to give people a guide for selecting the best algorithm for a given system or scene. Our information-theoretic assessment becomes this new tool to which allows us to compare the different edge detection operators in a common environment.

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

Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform.

PubMed

Cao, Jianfang; Chen, Lichao; Wang, Min; Tian, Yun

2018-01-01

The Canny operator is widely used to detect edges in images. However, as the size of the image dataset increases, the edge detection performance of the Canny operator decreases and its runtime becomes excessive. To improve the runtime and edge detection performance of the Canny operator, in this paper, we propose a parallel design and implementation for an Otsu-optimized Canny operator using a MapReduce parallel programming model that runs on the Hadoop platform. The Otsu algorithm is used to optimize the Canny operator's dual threshold and improve the edge detection performance, while the MapReduce parallel programming model facilitates parallel processing for the Canny operator to solve the processing speed and communication cost problems that occur when the Canny edge detection algorithm is applied to big data. For the experiments, we constructed datasets of different scales from the Pascal VOC2012 image database. The proposed parallel Otsu-Canny edge detection algorithm performs better than other traditional edge detection algorithms. The parallel approach reduced the running time by approximately 67.2% on a Hadoop cluster architecture consisting of 5 nodes with a dataset of 60,000 images. Overall, our approach system speeds up the system by approximately 3.4 times when processing large-scale datasets, which demonstrates the obvious superiority of our method. The proposed algorithm in this study demonstrates both better edge detection performance and improved time performance.

Application of machine learning methods for traffic signs recognition

NASA Astrophysics Data System (ADS)

Filatov, D. V.; Ignatev, K. V.; Deviatkin, A. V.; Serykh, E. V.

2018-02-01

This paper focuses on solving a relevant and pressing safety issue on intercity roads. Two approaches were considered for solving the problem of traffic signs recognition; the approaches involved neural networks to analyze images obtained from a camera in the real-time mode. The first approach is based on a sequential image processing. At the initial stage, with the help of color filters and morphological operations (dilatation and erosion), the area containing the traffic sign is located on the image, then the selected and scaled fragment of the image is analyzed using a feedforward neural network to determine the meaning of the found traffic sign. Learning of the neural network in this approach is carried out using a backpropagation method. The second approach involves convolution neural networks at both stages, i.e. when searching and selecting the area of the image containing the traffic sign, and when determining its meaning. Learning of the neural network in the second approach is carried out using the intersection over union function and a loss function. For neural networks to learn and the proposed algorithms to be tested, a series of videos from a dash cam were used that were shot under various weather and illumination conditions. As a result, the proposed approaches for traffic signs recognition were analyzed and compared by key indicators such as recognition rate percentage and the complexity of neural networks’ learning process.

Designing Two-Layer Optical Networks with Statistical Multiplexing

NASA Astrophysics Data System (ADS)

Addis, B.; Capone, A.; Carello, G.; Malucelli, F.; Fumagalli, M.; Pedrin Elli, E.

The possibility of adding multi-protocol label switching (MPLS) support to transport networks is considered an important opportunity by telecom carriers that want to add packet services and applications to their networks. However, the question that arises is whether it is suitable to have MPLS nodes just at the edge of the network to collect packet traffic from users, or also to introduce MPLS facilities on a subset of the core nodes in order to exploit packet switching flexibility and multiplexing, thus providing induction of a better bandwidth allocation. In this article, we address this complex decisional problem with the support of a mathematical programming approach. We consider two-layer networks where MPLS is overlaid on top of transport networks-synchronous digital hierarchy (SDH) or wavelength division multiplexing (WDM)-depending on the required link speed. The discussions' decisions take into account the trade-off between the cost of adding MPLS support in the core nodes and the savings in the link bandwidth allocation due to the statistical multiplexing and the traffic grooming effects induced by MPLS nodes. The traffic matrix specifies for each point-to-point request a pair of values: a mean traffic value and an additional one. Using this traffic model, the effect of statistical multiplexing on a link allows the allocation of a capacity equal to the sum of all the mean values of the traffic demands routed on the link and only the highest additional one. The proposed approach is suitable to solve real instances in reasonable time.

An optimal routing strategy on scale-free networks

NASA Astrophysics Data System (ADS)

Yang, Yibo; Zhao, Honglin; Ma, Jinlong; Qi, Zhaohui; Zhao, Yongbin

Traffic is one of the most fundamental dynamical processes in networked systems. With the traditional shortest path routing (SPR) protocol, traffic congestion is likely to occur on the hub nodes on scale-free networks. In this paper, we propose an improved optimal routing (IOR) strategy which is based on the betweenness centrality and the degree centrality of nodes in the scale-free networks. With the proposed strategy, the routing paths can accurately bypass hub nodes in the network to enhance the transport efficiency. Simulation results show that the traffic capacity as well as some other indexes reflecting transportation efficiency are further improved with the IOR strategy. Owing to the significantly improved traffic performance, this study is helpful to design more efficient routing strategies in communication or transportation systems.

Toward edge minability for role mining in bipartite networks

NASA Astrophysics Data System (ADS)

Dong, Lijun; Wang, Yi; Liu, Ran; Pi, Benjie; Wu, Liuyi

2016-11-01

Bipartite network models have been extensively used in information security to automatically generate role-based access control (RBAC) from dataset. This process is called role mining. However, not all the topologies of bipartite networks are suitable for role mining; some edges may even reduce the quality of role mining. This causes unnecessary time consumption as role mining is NP-hard. Therefore, to promote the quality of role mining results, the capability that an edge composes roles with other edges, called the minability of edge, needs to be identified. We tackle the problem from an angle of edge importance in complex networks; that is an edge easily covered by roles is considered to be more important. Based on this idea, the k-shell decomposition of complex networks is extended to reveal the different minability of edges. By this way, a bipartite network can be quickly purified by excluding the low-minability edges from role mining, and thus the quality of role mining can be effectively improved. Extensive experiments via the real-world datasets are conducted to confirm the above claims.

Damage Response in Fluid Flow Networks

NASA Astrophysics Data System (ADS)

Gavrilchenko, Tatyana; Katifori, Eleni

The networks found in biological fluid flow systems such as leaf venation and animal vasculature are characterized by hierarchically nested loops. This structure allows the system to be resilient against fluctuations in the flow of fluid and to be robust against damage. We analytically and computationally investigate how this loopy hierarchy determines the extent of disruption in fluid flow in the vicinity of a damage site. Perturbing the network with the removal of a single edge results in the differential flow as a function of distance from the perturbation decaying as a power law. The power law exponent is generally around -2 in 2D, but we find that it varies due to edge effects, initial edge conductivity, and local topology. We expect that these network flow findings, directly applicable to plant and animal veins, will have analogues in electrical grids, traffic flow and other transport networks.

Spatial-Spectral Approaches to Edge Detection in Hyperspectral Remote Sensing

NASA Astrophysics Data System (ADS)

Cox, Cary M.

This dissertation advances geoinformation science at the intersection of hyperspectral remote sensing and edge detection methods. A relatively new phenomenology among its remote sensing peers, hyperspectral imagery (HSI) comprises only about 7% of all remote sensing research - there are five times as many radar-focused peer reviewed journal articles than hyperspectral-focused peer reviewed journal articles. Similarly, edge detection studies comprise only about 8% of image processing research, most of which is dedicated to image processing techniques most closely associated with end results, such as image classification and feature extraction. Given the centrality of edge detection to mapping, that most important of geographic functions, improving the collective understanding of hyperspectral imagery edge detection methods constitutes a research objective aligned to the heart of geoinformation sciences. Consequently, this dissertation endeavors to narrow the HSI edge detection research gap by advancing three HSI edge detection methods designed to leverage HSI's unique chemical identification capabilities in pursuit of generating accurate, high-quality edge planes. The Di Zenzo-based gradient edge detection algorithm, an innovative version of the Resmini HySPADE edge detection algorithm and a level set-based edge detection algorithm are tested against 15 traditional and non-traditional HSI datasets spanning a range of HSI data configurations, spectral resolutions, spatial resolutions, bandpasses and applications. This study empirically measures algorithm performance against Dr. John Canny's six criteria for a good edge operator: false positives, false negatives, localization, single-point response, robustness to noise and unbroken edges. The end state is a suite of spatial-spectral edge detection algorithms that produce satisfactory edge results against a range of hyperspectral data types applicable to a diverse set of earth remote sensing applications. This work also explores the concept of an edge within hyperspectral space, the relative importance of spatial and spectral resolutions as they pertain to HSI edge detection and how effectively compressed HSI data improves edge detection results. The HSI edge detection experiments yielded valuable insights into the algorithms' strengths, weaknesses and optimal alignment to remote sensing applications. The gradient-based edge operator produced strong edge planes across a range of evaluation measures and applications, particularly with respect to false negatives, unbroken edges, urban mapping, vegetation mapping and oil spill mapping applications. False positives and uncompressed HSI data presented occasional challenges to the algorithm. The HySPADE edge operator produced satisfactory results with respect to localization, single-point response, oil spill mapping and trace chemical detection, and was challenged by false positives, declining spectral resolution and vegetation mapping applications. The level set edge detector produced high-quality edge planes for most tests and demonstrated strong performance with respect to false positives, single-point response, oil spill mapping and mineral mapping. False negatives were a regular challenge for the level set edge detection algorithm. Finally, HSI data optimized for spectral information compression and noise was shown to improve edge detection performance across all three algorithms, while the gradient-based algorithm and HySPADE demonstrated significant robustness to declining spectral and spatial resolutions.

Highway traffic noise prediction based on GIS

NASA Astrophysics Data System (ADS)

Zhao, Jianghua; Qin, Qiming

2014-05-01

Before building a new road, we need to predict the traffic noise generated by vehicles. Traditional traffic noise prediction methods are based on certain locations and they are not only time-consuming, high cost, but also cannot be visualized. Geographical Information System (GIS) can not only solve the problem of manual data processing, but also can get noise values at any point. The paper selected a road segment from Wenxi to Heyang. According to the geographical overview of the study area and the comparison between several models, we combine the JTG B03-2006 model and the HJ2.4-2009 model to predict the traffic noise depending on the circumstances. Finally, we interpolate the noise values at each prediction point and then generate contours of noise. By overlaying the village data on the noise contour layer, we can get the thematic maps. The use of GIS for road traffic noise prediction greatly facilitates the decision-makers because of GIS spatial analysis function and visualization capabilities. We can clearly see the districts where noise are excessive, and thus it becomes convenient to optimize the road line and take noise reduction measures such as installing sound barriers and relocating villages and so on.

Fast packet switching algorithms for dynamic resource control over ATM networks

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

Tsang, R.P.; Keattihananant, P.; Chang, T.

1996-12-01

Real-time continuous media traffic, such as digital video and audio, is expected to comprise a large percentage of the network load on future high speed packet switch networks such as ATM. A major feature which distinguishes high speed networks from traditional slower speed networks is the large amount of data the network must process very quickly. For efficient network usage, traffic control mechanisms are essential. Currently, most mechanisms for traffic control (such as flow control) have centered on the support of Available Bit Rate (ABR), i.e., non real-time, traffic. With regard to ATM, for ABR traffic, two major types ofmore » schemes which have been proposed are rate- control and credit-control schemes. Neither of these schemes are directly applicable to Real-time Variable Bit Rate (VBR) traffic such as continuous media traffic. Traffic control for continuous media traffic is an inherently difficult problem due to the time- sensitive nature of the traffic and its unpredictable burstiness. In this study, we present a scheme which controls traffic by dynamically allocating/de- allocating resources among competing VCs based upon their real-time requirements. This scheme incorporates a form of rate- control, real-time burst-level scheduling and link-link flow control. We show analytically potential performance improvements of our rate- control scheme and present a scheme for buffer dimensioning. We also present simulation results of our schemes and discuss the tradeoffs inherent in maintaining high network utilization and statistically guaranteeing many users` Quality of Service.« less

Pedestrians' intention to jaywalk: Automatic or planned? A study based on a dual-process model in China.

PubMed

Xu, Yaoshan; Li, Yongjuan; Zhang, Feng

2013-01-01

The present study investigates the determining factors of Chinese pedestrians' intention to violate traffic laws using a dual-process model. This model divides the cognitive processes of intention formation into controlled analytical processes and automatic associative processes. Specifically, the process explained by the augmented theory of planned behavior (TPB) is controlled, whereas the process based on past behavior is automatic. The results of a survey conducted on 323 adult pedestrian respondents showed that the two added TPB variables had different effects on the intention to violate, i.e., personal norms were significantly related to traffic violation intention, whereas descriptive norms were non-significant predictors. Past behavior significantly but uniquely predicted the intention to violate: the results of the relative weight analysis indicated that the largest percentage of variance in pedestrians' intention to violate was explained by past behavior (42%). According to the dual-process model, therefore, pedestrians' intention formation relies more on habit than on cognitive TPB components and social norms. The implications of these findings for the development of intervention programs are discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.

Tuning the band structure of graphene nanoribbons through defect-interaction-driven edge patterning

NASA Astrophysics Data System (ADS)

Du, Lin; Nguyen, Tam N.; Gilman, Ari; Muniz, André R.; Maroudas, Dimitrios

2017-12-01

We report a systematic analysis of pore-edge interactions in graphene nanoribbons (GNRs) and their outcomes based on first-principles calculations and classical molecular-dynamics simulations. We find a strong attractive interaction between nanopores and GNR edges that drives the pores to migrate toward and coalesce with the GNR edges, which can be exploited to form GNR edge patterns that impact the GNR electronic band structure and tune the GNR band gap. Our analysis introduces a viable physical processing strategy for modifying GNR properties by combining defect engineering and thermal annealing.

Traffic analysis and control using image processing

NASA Astrophysics Data System (ADS)

Senthilkumar, K.; Ellappan, Vijayan; Arun, A. R.

2017-11-01

This paper shows the work on traffic analysis and control till date. It shows an approach to regulate traffic the use of image processing and MATLAB systems. This concept uses computational images that are to be compared with original images of the street taken in order to determine the traffic level percentage and set the timing for the traffic signal accordingly which are used to reduce the traffic stoppage on traffic lights. They concept proposes to solve real life scenarios in the streets, thus enriching the traffic lights by adding image receivers like HD cameras and image processors. The input is then imported into MATLAB to be used. as a method for calculating the traffic on roads. Their results would be computed in order to adjust the traffic light timings on a particular street, and also with respect to other similar proposals but with the added value of solving a real, big instance.

Models for discrete-time self-similar vector processes with application to network traffic

NASA Astrophysics Data System (ADS)

Lee, Seungsin; Rao, Raghuveer M.; Narasimha, Rajesh

2003-07-01

The paper defines self-similarity for vector processes by employing the discrete-time continuous-dilation operation which has successfully been used previously by the authors to define 1-D discrete-time stochastic self-similar processes. To define self-similarity of vector processes, it is required to consider the cross-correlation functions between different 1-D processes as well as the autocorrelation function of each constituent 1-D process in it. System models to synthesize self-similar vector processes are constructed based on the definition. With these systems, it is possible to generate self-similar vector processes from white noise inputs. An important aspect of the proposed models is that they can be used to synthesize various types of self-similar vector processes by choosing proper parameters. Additionally, the paper presents evidence of vector self-similarity in two-channel wireless LAN data and applies the aforementioned systems to simulate the corresponding network traffic traces.

A Sarsa(λ)-based control model for real-time traffic light coordination.

PubMed

Zhou, Xiaoke; Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei

2014-01-01

Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control.

State traffic volume systems council estimation process.

DOT National Transportation Integrated Search

2004-10-01

The Kentucky Transportation Cabinet has an immense traffic data collection program that is an essential source for many other programs. The Division of Planning processes traffic volume counts annually. These counts are maintained in the Counts Datab...

Edge detection and localization with edge pattern analysis and inflection characterization

NASA Astrophysics Data System (ADS)

Jiang, Bo

2012-05-01

In general edges are considered to be abrupt changes or discontinuities in two dimensional image signal intensity distributions. The accuracy of front-end edge detection methods in image processing impacts the eventual success of higher level pattern analysis downstream. To generalize edge detectors designed from a simple ideal step function model to real distortions in natural images, research on one dimensional edge pattern analysis to improve the accuracy of edge detection and localization proposes an edge detection algorithm, which is composed by three basic edge patterns, such as ramp, impulse, and step. After mathematical analysis, general rules for edge representation based upon the classification of edge types into three categories-ramp, impulse, and step (RIS) are developed to reduce detection and localization errors, especially reducing "double edge" effect that is one important drawback to the derivative method. But, when applying one dimensional edge pattern in two dimensional image processing, a new issue is naturally raised that the edge detector should correct marking inflections or junctions of edges. Research on human visual perception of objects and information theory pointed out that a pattern lexicon of "inflection micro-patterns" has larger information than a straight line. Also, research on scene perception gave an idea that contours have larger information are more important factor to determine the success of scene categorization. Therefore, inflections or junctions are extremely useful features, whose accurate description and reconstruction are significant in solving correspondence problems in computer vision. Therefore, aside from adoption of edge pattern analysis, inflection or junction characterization is also utilized to extend traditional derivative edge detection algorithm. Experiments were conducted to test my propositions about edge detection and localization accuracy improvements. The results support the idea that these edge detection method improvements are effective in enhancing the accuracy of edge detection and localization.

A new edge detection algorithm based on Canny idea

NASA Astrophysics Data System (ADS)

Feng, Yingke; Zhang, Jinmin; Wang, Siming

2017-10-01

The traditional Canny algorithm has poor self-adaptability threshold, and it is more sensitive to noise. In order to overcome these drawbacks, this paper proposed a new edge detection method based on Canny algorithm. Firstly, the media filtering and filtering based on the method of Euclidean distance are adopted to process it; secondly using the Frei-chen algorithm to calculate gradient amplitude; finally, using the Otsu algorithm to calculate partial gradient amplitude operation to get images of thresholds value, then find the average of all thresholds that had been calculated, half of the average is high threshold value, and the half of the high threshold value is low threshold value. Experiment results show that this new method can effectively suppress noise disturbance, keep the edge information, and also improve the edge detection accuracy.

A Study of Driver's Route Choice Behavior Based on Evolutionary Game Theory

PubMed Central

Jiang, Xiaowei; Ji, Yanjie; Deng, Wei

2014-01-01

This paper proposes a route choice analytic method that embeds cumulative prospect theory in evolutionary game theory to analyze how the drivers adjust their route choice behaviors under the influence of the traffic information. A simulated network with two alternative routes and one variable message sign is built to illustrate the analytic method. We assume that the drivers in the transportation system are bounded rational, and the traffic information they receive is incomplete. An evolutionary game model is constructed to describe the evolutionary process of the drivers' route choice decision-making behaviors. Here we conclude that the traffic information plays an important role in the route choice behavior. The driver's route decision-making process develops towards different evolutionary stable states in accordance with different transportation situations. The analysis results also demonstrate that employing cumulative prospect theory and evolutionary game theory to study the driver's route choice behavior is effective. This analytic method provides an academic support and suggestion for the traffic guidance system, and may optimize the travel efficiency to a certain extent. PMID:25610455

A study of driver's route choice behavior based on evolutionary game theory.

PubMed

Jiang, Xiaowei; Ji, Yanjie; Du, Muqing; Deng, Wei

2014-01-01

This paper proposes a route choice analytic method that embeds cumulative prospect theory in evolutionary game theory to analyze how the drivers adjust their route choice behaviors under the influence of the traffic information. A simulated network with two alternative routes and one variable message sign is built to illustrate the analytic method. We assume that the drivers in the transportation system are bounded rational, and the traffic information they receive is incomplete. An evolutionary game model is constructed to describe the evolutionary process of the drivers' route choice decision-making behaviors. Here we conclude that the traffic information plays an important role in the route choice behavior. The driver's route decision-making process develops towards different evolutionary stable states in accordance with different transportation situations. The analysis results also demonstrate that employing cumulative prospect theory and evolutionary game theory to study the driver's route choice behavior is effective. This analytic method provides an academic support and suggestion for the traffic guidance system, and may optimize the travel efficiency to a certain extent.

Using fuzzy fractal features of digital images for the material surface analisys

NASA Astrophysics Data System (ADS)

Privezentsev, D. G.; Zhiznyakov, A. L.; Astafiev, A. V.; Pugin, E. V.

2018-01-01

Edge detection is an important task in image processing. There are a lot of approaches in this area: Sobel, Canny operators and others. One of the perspective techniques in image processing is the use of fuzzy logic and fuzzy sets theory. They allow us to increase processing quality by representing information in its fuzzy form. Most of the existing fuzzy image processing methods switch to fuzzy sets on very late stages, so this leads to some useful information loss. In this paper, a novel method of edge detection based on fuzzy image representation and fuzzy pixels is proposed. With this approach, we convert the image to fuzzy form on the first step. Different approaches to this conversion are described. Several membership functions for fuzzy pixel description and requirements for their form and view are given. A novel approach to edge detection based on Sobel operator and fuzzy image representation is proposed. Experimental testing of developed method was performed on remote sensing images.

Traffic sign detection in MLS acquired point clouds for geometric and image-based semantic inventory

NASA Astrophysics Data System (ADS)

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

2016-04-01

Nowadays, mobile laser scanning has become a valid technology for infrastructure inspection. This technology permits collecting accurate 3D point clouds of urban and road environments and the geometric and semantic analysis of data became an active research topic in the last years. This paper focuses on the detection of vertical traffic signs in 3D point clouds acquired by a LYNX Mobile Mapper system, comprised of laser scanning and RGB cameras. Each traffic sign is automatically detected in the LiDAR point cloud, and its main geometric parameters can be automatically extracted, therefore aiding the inventory process. Furthermore, the 3D position of traffic signs are reprojected on the 2D images, which are spatially and temporally synced with the point cloud. Image analysis allows for recognizing the traffic sign semantics using machine learning approaches. The presented method was tested in road and urban scenarios in Galicia (Spain). The recall results for traffic sign detection are close to 98%, and existing false positives can be easily filtered after point cloud projection. Finally, the lack of a large, publicly available Spanish traffic sign database is pointed out.

Superpixel edges for boundary detection

DOEpatents

Moya, Mary M.; Koch, Mark W.

2016-07-12

Various embodiments presented herein relate to identifying one or more edges in a synthetic aperture radar (SAR) image comprising a plurality of superpixels. Superpixels sharing an edge (or boundary) can be identified and one or more properties of the shared superpixels can be compared to determine whether the superpixels form the same or two different features. Where the superpixels form the same feature the edge is identified as an internal edge. Where the superpixels form two different features, the edge is identified as an external edge. Based upon classification of the superpixels, the external edge can be further determined to form part of a roof, wall, etc. The superpixels can be formed from a speckle-reduced SAR image product formed from a registered stack of SAR images, which is further segmented into a plurality of superpixels. The edge identification process is applied to the SAR image comprising the superpixels and edges.

Developing a stochastic traffic volume prediction model for public-private partnership projects

NASA Astrophysics Data System (ADS)

Phong, Nguyen Thanh; Likhitruangsilp, Veerasak; Onishi, Masamitsu

2017-11-01

Transportation projects require an enormous amount of capital investment resulting from their tremendous size, complexity, and risk. Due to the limitation of public finances, the private sector is invited to participate in transportation project development. The private sector can entirely or partially invest in transportation projects in the form of Public-Private Partnership (PPP) scheme, which has been an attractive option for several developing countries, including Vietnam. There are many factors affecting the success of PPP projects. The accurate prediction of traffic volume is considered one of the key success factors of PPP transportation projects. However, only few research works investigated how to predict traffic volume over a long period of time. Moreover, conventional traffic volume forecasting methods are usually based on deterministic models which predict a single value of traffic volume but do not consider risk and uncertainty. This knowledge gap makes it difficult for concessionaires to estimate PPP transportation project revenues accurately. The objective of this paper is to develop a probabilistic traffic volume prediction model. First, traffic volumes were estimated following the Geometric Brownian Motion (GBM) process. Monte Carlo technique is then applied to simulate different scenarios. The results show that this stochastic approach can systematically analyze variations in the traffic volume and yield more reliable estimates for PPP projects.

Self-organization of bacterial biofilms is facilitated by extracellular DNA

PubMed Central

Gloag, Erin S.; Turnbull, Lynne; Huang, Alan; Vallotton, Pascal; Wang, Huabin; Nolan, Laura M.; Mililli, Lisa; Hunt, Cameron; Lu, Jing; Osvath, Sarah R.; Monahan, Leigh G.; Cavaliere, Rosalia; Charles, Ian G.; Wand, Matt P.; Gee, Michelle L.; Prabhakar, Ranganathan; Whitchurch, Cynthia B.

2013-01-01

Twitching motility-mediated biofilm expansion is a complex, multicellular behavior that enables the active colonization of surfaces by many species of bacteria. In this study we have explored the emergence of intricate network patterns of interconnected trails that form in actively expanding biofilms of Pseudomonas aeruginosa. We have used high-resolution, phase-contrast time-lapse microscopy and developed sophisticated computer vision algorithms to track and analyze individual cell movements during expansion of P. aeruginosa biofilms. We have also used atomic force microscopy to examine the topography of the substrate underneath the expanding biofilm. Our analyses reveal that at the leading edge of the biofilm, highly coherent groups of bacteria migrate across the surface of the semisolid media and in doing so create furrows along which following cells preferentially migrate. This leads to the emergence of a network of trails that guide mass transit toward the leading edges of the biofilm. We have also determined that extracellular DNA (eDNA) facilitates efficient traffic flow throughout the furrow network by maintaining coherent cell alignments, thereby avoiding traffic jams and ensuring an efficient supply of cells to the migrating front. Our analyses reveal that eDNA also coordinates the movements of cells in the leading edge vanguard rafts and is required for the assembly of cells into the “bulldozer” aggregates that forge the interconnecting furrows. Our observations have revealed that large-scale self-organization of cells in actively expanding biofilms of P. aeruginosa occurs through construction of an intricate network of furrows that is facilitated by eDNA. PMID:23798445

A GPS-based Real-time Road Traffic Monitoring System

NASA Astrophysics Data System (ADS)

Tanti, Kamal Kumar

In recent years, monitoring systems are astonishingly inclined towards ever more automatic; reliably interconnected, distributed and autonomous operation. Specifically, the measurement, logging, data processing and interpretation activities may be carried out by separate units at different locations in near real-time. The recent evolution of mobile communication devices and communication technologies has fostered a growing interest in the GIS & GPS-based location-aware systems and services. This paper describes a real-time road traffic monitoring system based on integrated mobile field devices (GPS/GSM/IOs) working in tandem with advanced GIS-based application software providing on-the-fly authentications for real-time monitoring and security enhancement. The described system is developed as a fully automated, continuous, real-time monitoring system that employs GPS sensors and Ethernet and/or serial port communication techniques are used to transfer data between GPS receivers at target points and a central processing computer. The data can be processed locally or remotely based on the requirements of client’s satisfaction. Due to the modular architecture of the system, other sensor types may be supported with minimal effort. Data on the distributed network & measurements are transmitted via cellular SIM cards to a Control Unit, which provides for post-processing and network management. The Control Unit may be remotely accessed via an Internet connection. The new system will not only provide more consistent data about the road traffic conditions but also will provide methods for integrating with other Intelligent Transportation Systems (ITS). For communication between the mobile device and central monitoring service GSM technology is used. The resulting system is characterized by autonomy, reliability and a high degree of automation.

Passenger Flow Forecasting Research for Airport Terminal Based on SARIMA Time Series Model

NASA Astrophysics Data System (ADS)

Li, Ziyu; Bi, Jun; Li, Zhiyin

2017-12-01

Based on the data of practical operating of Kunming Changshui International Airport during2016, this paper proposes Seasonal Autoregressive Integrated Moving Average (SARIMA) model to predict the passenger flow. This article not only considers the non-stationary and autocorrelation of the sequence, but also considers the daily periodicity of the sequence. The prediction results can accurately describe the change trend of airport passenger flow and provide scientific decision support for the optimal allocation of airport resources and optimization of departure process. The result shows that this model is applicable to the short-term prediction of airport terminal departure passenger traffic and the average error ranges from 1% to 3%. The difference between the predicted and the true values of passenger traffic flow is quite small, which indicates that the model has fairly good passenger traffic flow prediction ability.

Detection and enforcement of failure-to-yield in an emergency vehicle preemption system

NASA Technical Reports Server (NTRS)

Bachelder, Aaron (Inventor); Wickline, Richard (Inventor)

2007-01-01

An intersection controlled by an intersection controller receives trigger signals from on-coming emergency vehicles responding to an emergency call. The intersection controller initiates surveillance of the intersection via cameras installed at the intersection in response to a received trigger signal. The surveillance may begin immediately upon receipt of the trigger signal from an emergency vehicle, or may wait until the intersection controller determines that the signaling emergency vehicle is in the field of view of the cameras at the intersection. Portions of the captured images are tagged by the intersection controller based on tag signals transmitted by the vehicle or based on detected traffic patterns that indicate a potential traffic violation. The captured images are downloaded to a processing facility that analyzes the images and automatically issues citations for captured traffic violations.

Evaluation of Alternate Concepts for Synthetic Vision Flight Displays With Weather-Penetrating Sensor Image Inserts During Simulated Landing Approaches

NASA Technical Reports Server (NTRS)

Parrish, Russell V.; Busquets, Anthony M.; Williams, Steven P.; Nold, Dean E.

2003-01-01

A simulation study was conducted in 1994 at Langley Research Center that used 12 commercial airline pilots repeatedly flying complex Microwave Landing System (MLS)-type approaches to parallel runways under Category IIIc weather conditions. Two sensor insert concepts of 'Synthetic Vision Systems' (SVS) were used in the simulated flights, with a more conventional electro-optical display (similar to a Head-Up Display with raster capability for sensor imagery), flown under less restrictive visibility conditions, used as a control condition. The SVS concepts combined the sensor imagery with a computer-generated image (CGI) of an out-the-window scene based on an onboard airport database. Various scenarios involving runway traffic incursions (taxiing aircraft and parked fuel trucks) and navigational system position errors (both static and dynamic) were used to assess the pilots' ability to manage the approach task with the display concepts. The two SVS sensor insert concepts contrasted the simple overlay of sensor imagery on the CGI scene without additional image processing (the SV display) to the complex integration (the AV display) of the CGI scene with pilot-decision aiding using both object and edge detection techniques for detection of obstacle conflicts and runway alignment errors.

A Study towards Building An Optimal Graph Theory Based Model For The Design of Tourism Website

NASA Astrophysics Data System (ADS)

Panigrahi, Goutam; Das, Anirban; Basu, Kajla

2010-10-01

Effective tourism website is a key to attract tourists from different parts of the world. Here we identify the factors of improving the effectiveness of website by considering it as a graph, where web pages including homepage are the nodes and hyperlinks are the edges between the nodes. In this model, the design constraints for building a tourism website are taken into consideration. Our objectives are to build a framework of an effective tourism website providing adequate level of information, service and also to enable the users to reach to the desired page by spending minimal loading time. In this paper an information hierarchy specifying the upper limit of outgoing link of a page has also been proposed. Following the hierarchy, the web developer can prepare an effective tourism website. Here loading time depends on page size and network traffic. We have assumed network traffic as uniform and the loading time is directly proportional with page size. This approach is done by quantifying the link structure of a tourism website. In this approach we also propose a page size distribution pattern of a tourism website.

Inferring the background traffic arrival process in the Internet.

PubMed

Hága, Péter; Csabai, István; Vattay, Gábor

2009-12-01

Phase transition has been found in many complex interactivity systems. Complex networks are not exception either but there are quite few real systems where we can directly understand the emergence of this nontrivial behavior from the microscopic view. In this paper, we present the emergence of the phase transition between the congested and uncongested phases of a network link. We demonstrate a method to infer the background traffic arrival process, which is one of the key state parameters of the Internet traffic. The traffic arrival process in the Internet has been investigated in several studies, since the recognition of its self-similar nature. The statistical properties of the traffic arrival process are very important since they are fundamental in modeling the dynamical behavior. Here, we demonstrate how the widely used packet train technique can be used to determine the main properties of the traffic arrival process. We show that the packet train dispersion is sensitive to the congestion on the network path. We introduce the packet train stretch as an order parameter to describe the phase transition between the congested and uncongested phases of the bottleneck link in the path. We find that the distribution of the background traffic arrival process can be determined from the average packet train dispersion at the critical point of the system.

Segmentation of neuroanatomy in magnetic resonance images

NASA Astrophysics Data System (ADS)

Simmons, Andrew; Arridge, Simon R.; Barker, G. J.; Tofts, Paul S.

1992-06-01

Segmentation in neurological magnetic resonance imaging (MRI) is necessary for feature extraction, volume measurement and for the three-dimensional display of neuroanatomy. Automated and semi-automated methods offer considerable advantages over manual methods because of their lack of subjectivity, their data reduction capabilities, and the time savings they give. We have used dual echo multi-slice spin-echo data sets which take advantage of the intrinsically multispectral nature of MRI. As a pre-processing step, a rf non-uniformity correction is applied and if the data is noisy the images are smoothed using a non-isotropic blurring method. Edge-based processing is used to identify the skin (the major outer contour) and the eyes. Edge-focusing has been used to significantly simplify edge images and thus allow simple postprocessing to pick out the brain contour in each slice of the data set. Edge- focusing is a technique which locates significant edges using a high degree of smoothing at a coarse level and tracks these edges to a fine level where the edges can be determined with high positional accuracy. Both 2-D and 3-D edge-detection methods have been compared. Once isolated, the brain is further processed to identify CSF, and, depending upon the MR pulse sequence used, the brain itself may be sub-divided into gray matter and white matter using semi-automatic contrast enhancement and clustering methods.

Method of Preparation AZP4330 PR Pattern with Edge Slope 40°

NASA Astrophysics Data System (ADS)

Wu, Jie; Zhao, Hongyuan; Yu, Yuanwei; Zhu, Jian

2018-03-01

When the edge which is under the multi-film is more steep or angular, the stress in the multilayer film near the edge is concentrated, this situation will greatly reduce the reliability of electronic components. And sometimes, we need some special structure such as a slope with a specific angle in the MEMS, so that the metal line can take the signal to the output pad through the slope instead of deep step. To cover these problems, the lithography method of preparing the structure with edge slope is studied. In this paper, based on the Kirchhoff scalar diffraction theory we try to change the contact exposure gap and the post-baking time at the specific temperature to find out the effect about the edge angle of the photoresist. After test by SEM, the results were presented by using AZP4330 photoresist, we can get the PR Pattern with edge slope 40° of the process and the specific process parameters.

A Sarsa(λ)-Based Control Model for Real-Time Traffic Light Coordination

PubMed Central

Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei

2014-01-01

Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control. PMID:24592183

Vision-Based Traffic Data Collection Sensor for Automotive Applications

PubMed Central

Llorca, David F.; Sánchez, Sergio; Ocaña, Manuel; Sotelo, Miguel. A.

2010-01-01

This paper presents a complete vision sensor onboard a moving vehicle which collects the traffic data in its local area in daytime conditions. The sensor comprises a rear looking and a forward looking camera. Thus, a representative description of the traffic conditions in the local area of the host vehicle can be computed. The proposed sensor detects the number of vehicles (traffic load), their relative positions and their relative velocities in a four-stage process: lane detection, candidates selection, vehicles classification and tracking. Absolute velocities (average road speed) and global positioning are obtained after combining the outputs provided by the vision sensor with the data supplied by the CAN Bus and a GPS sensor. The presented experiments are promising in terms of detection performance and accuracy in order to be validated for applications in the context of the automotive industry. PMID:22315572

Vision-based traffic data collection sensor for automotive applications.

PubMed

Llorca, David F; Sánchez, Sergio; Ocaña, Manuel; Sotelo, Miguel A

2010-01-01

This paper presents a complete vision sensor onboard a moving vehicle which collects the traffic data in its local area in daytime conditions. The sensor comprises a rear looking and a forward looking camera. Thus, a representative description of the traffic conditions in the local area of the host vehicle can be computed. The proposed sensor detects the number of vehicles (traffic load), their relative positions and their relative velocities in a four-stage process: lane detection, candidates selection, vehicles classification and tracking. Absolute velocities (average road speed) and global positioning are obtained after combining the outputs provided by the vision sensor with the data supplied by the CAN Bus and a GPS sensor. The presented experiments are promising in terms of detection performance and accuracy in order to be validated for applications in the context of the automotive industry.

Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform

PubMed Central

Wang, Min; Tian, Yun

2018-01-01

The Canny operator is widely used to detect edges in images. However, as the size of the image dataset increases, the edge detection performance of the Canny operator decreases and its runtime becomes excessive. To improve the runtime and edge detection performance of the Canny operator, in this paper, we propose a parallel design and implementation for an Otsu-optimized Canny operator using a MapReduce parallel programming model that runs on the Hadoop platform. The Otsu algorithm is used to optimize the Canny operator's dual threshold and improve the edge detection performance, while the MapReduce parallel programming model facilitates parallel processing for the Canny operator to solve the processing speed and communication cost problems that occur when the Canny edge detection algorithm is applied to big data. For the experiments, we constructed datasets of different scales from the Pascal VOC2012 image database. The proposed parallel Otsu-Canny edge detection algorithm performs better than other traditional edge detection algorithms. The parallel approach reduced the running time by approximately 67.2% on a Hadoop cluster architecture consisting of 5 nodes with a dataset of 60,000 images. Overall, our approach system speeds up the system by approximately 3.4 times when processing large-scale datasets, which demonstrates the obvious superiority of our method. The proposed algorithm in this study demonstrates both better edge detection performance and improved time performance. PMID:29861711

AHP-based spatial analysis of water quality impact assessment due to change in vehicular traffic caused by highway broadening in Sikkim Himalaya

NASA Astrophysics Data System (ADS)

Banerjee, Polash; Ghose, Mrinal Kanti; Pradhan, Ratika

2018-05-01

Spatial analysis of water quality impact assessment of highway projects in mountainous areas remains largely unexplored. A methodology is presented here for Spatial Water Quality Impact Assessment (SWQIA) due to highway-broadening-induced vehicular traffic change in the East district of Sikkim. Pollution load of the highway runoff was estimated using an Average Annual Daily Traffic-Based Empirical model in combination with mass balance model to predict pollution in the rivers within the study area. Spatial interpolation and overlay analysis were used for impact mapping. Analytic Hierarchy Process-Based Water Quality Status Index was used to prepare a composite impact map. Model validation criteria, cross-validation criteria, and spatial explicit sensitivity analysis show that the SWQIA model is robust. The study shows that vehicular traffic is a significant contributor to water pollution in the study area. The model is catering specifically to impact analysis of the concerned project. It can be an aid for decision support system for the project stakeholders. The applicability of SWQIA model needs to be explored and validated in the context of a larger set of water quality parameters and project scenarios at a greater spatial scale.

Expanding the Use of Time-Based Metering: Multi-Center Traffic Management Advisor

NASA Technical Reports Server (NTRS)

Landry, Steven J.; Farley, Todd; Hoang, Ty

2005-01-01

Time-based metering is an efficient air traffic management alternative to the more common practice of distance-based metering (or "miles-in-trail spacing"). Despite having demonstrated significant operational benefit to airspace users and service providers, time-based metering is used in the United States for arrivals to just nine airports and is not used at all for non-arrival traffic flows. The Multi-Center Traffic Management Advisor promises to bring time-based metering into the mainstream of air traffic management techniques. Not constrained to operate solely on arrival traffic, Multi-Center Traffic Management Advisor is flexible enough to work in highly congested or heavily partitioned airspace for any and all traffic flows in a region. This broader and more general application of time-based metering is expected to bring the operational benefits of time-based metering to a much wider pool of beneficiaries than is possible with existing technology. It also promises to facilitate more collaborative traffic management on a regional basis. This paper focuses on the operational concept of the Multi-Center Traffic Management Advisor, touching also on its system architecture, field test results, and prospects for near-term deployment to the United States National Airspace System.

The Evaluation of Screening Process and Local Bureaucracy in Determining the Priority of Urban Roads Maintenance and Rehabilitation

NASA Astrophysics Data System (ADS)

Hendhratmoyo, Andri; Syafi'i; Pungky Pramesti, Florentina

2017-11-01

Due to the limited budget of urban roads maintenance and rehabilitation, its prioritizationis inevitable. Many models have been developed to solve these problems. That is the reason why the purpose of this study was to evaluate the screening process in the decision making of the urban roads maintenance and rehabilitation priority. The prioritization that have to be taken into account on the effect of important criteria are road condition, traffic volume, budget processing and land use. 30 stakeholders were asked to fill in the questionnaires. The object of this case study are 188 urban roads sections at Ponorogo in order to examine the priorities. The researchers collected the data from Surface Distress Index (SDI), traffic volume, budget processing and land use of these road sections. Based on analysis, the weights of the criteria were: road condition (W1) = 0,411; traffic volume (W2) = 0,122; budget processing (W3) = 0,363 and land use (W4) = 0,105. The result of this study by the comparison of the index values of the alternatives priorities, Nyi Ageng Serang Street, was revealed to have the highest priority over the other streets regarding of maintenance and rehabilitation activities.

Joint parameter and state estimation algorithms for real-time traffic monitoring.

DOT National Transportation Integrated Search

2013-12-01

A common approach to traffic monitoring is to combine a macroscopic traffic flow model with traffic sensor data in a process called state estimation, data fusion, or data assimilation. The main challenge of traffic state estimation is the integration...

An estimation of vehicle kilometer traveled and on-road emissions using the traffic volume and travel speed on road links in Incheon City.

PubMed

Jung, Sungwoon; Kim, Jounghwa; Kim, Jeongsoo; Hong, Dahee; Park, Dongjoo

2017-04-01

The objective of this study is to estimate the vehicle kilometer traveled (VKT) and on-road emissions using the traffic volume in urban. We estimated two VKT; one is based on registered vehicles and the other is based on traffic volumes. VKT for registered vehicles was 2.11 times greater than that of the applied traffic volumes because each VKT estimation method is different. Therefore, we had to define the inner VKT is moved VKT inner in urban to compare two values. Also, we focused on freight modes because these are discharged much air pollutant emissions. From analysis results, we found middle and large trucks registered in other regions traveled to target city in order to carry freight, target city has included many industrial and logistics areas. Freight is transferred through the harbors, large logistics centers, or via locations before being moved to the final destination. During this process, most freight is moved by middle and large trucks, and trailers rather than small trucks for freight import and export. Therefore, these trucks from other areas are inflow more than registered vehicles. Most emissions from diesel trucks had been overestimated in comparison to VKT from applied traffic volumes in target city. From these findings, VKT is essential based on traffic volume and travel speed on road links in order to estimate accurately the emissions of diesel trucks in target city. Our findings support the estimation of the effect of on-road emissions on urban air quality in Korea. Copyright © 2016. Published by Elsevier B.V.

An unsupervised video foreground co-localization and segmentation process by incorporating motion cues and frame features

NASA Astrophysics Data System (ADS)

Zhang, Chao; Zhang, Qian; Zheng, Chi; Qiu, Guoping

2018-04-01

Video foreground segmentation is one of the key problems in video processing. In this paper, we proposed a novel and fully unsupervised approach for foreground object co-localization and segmentation of unconstrained videos. We firstly compute both the actual edges and motion boundaries of the video frames, and then align them by their HOG feature maps. Then, by filling the occlusions generated by the aligned edges, we obtained more precise masks about the foreground object. Such motion-based masks could be derived as the motion-based likelihood. Moreover, the color-base likelihood is adopted for the segmentation process. Experimental Results show that our approach outperforms most of the State-of-the-art algorithms.

The big and intricate dreams of little organelles: Embracing complexity in the study of membrane traffic.

PubMed

Liu, Allen P; Botelho, Roberto J; Antonescu, Costin N

2017-09-01

Compartmentalization of eukaryotic cells into dynamic organelles that exchange material through regulated membrane traffic governs virtually every aspect of cellular physiology including signal transduction, metabolism and transcription. Much has been revealed about the molecular mechanisms that control organelle dynamics and membrane traffic and how these processes are regulated by metabolic, physical and chemical cues. From this emerges the understanding of the integration of specific organellar phenomena within complex, multiscale and nonlinear regulatory networks. In this review, we discuss systematic approaches that revealed remarkable insight into the complexity of these phenomena, including the use of proximity-based proteomics, high-throughput imaging, transcriptomics and computational modeling. We discuss how these methods offer insights to further understand molecular versatility and organelle heterogeneity, phenomena that allow a single organelle population to serve a range of physiological functions. We also detail on how transcriptional circuits drive organelle adaptation, such that organelles may shift their function to better serve distinct differentiation and stress conditions. Thus, organelle dynamics and membrane traffic are functionally heterogeneous and adaptable processes that coordinate with higher-order system behavior to optimize cell function under a range of contexts. Obtaining a comprehensive understanding of organellar phenomena will increasingly require combined use of reductionist and system-based approaches. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Traffic dynamics of carnival processions

NASA Astrophysics Data System (ADS)

Polichronidis, Petros; Wegerle, Dominik; Dieper, Alexander; Schreckenberg, Michael

2018-03-01

The traffic dynamics of processions are described in this study. GPS data from participating groups in the Cologne Rose Monday processions 2014–2017 are used to analyze the kinematic characteristics. The preparation of the measured data requires an adjustment by a specially adapted algorithm for the map matching method. A higher average velocity is observed for the last participant, the Carnival Prince, than for the leading participant of the parade. Based on the results of the data analysis, for the first time a model can be established for defilading parade groups as a modified Nagel-Schreckenberg model. This model can reproduce the observed characteristics in simulations. They can be explained partly by the constantly moving vehicle driving ahead of the parade leaving the pathway and partly due to a spatial contraction of the parade during the procession.

BP fusion model for the detection of oil spills on the sea by remote sensing

NASA Astrophysics Data System (ADS)

Chen, Weiwei; An, Jubai; Zhang, Hande; Lin, Bin

2003-06-01

Oil spills are very serious marine pollution in many countries. In order to detect and identify the oil-spilled on the sea by remote sensor, scientists have to conduct a research work on the remote sensing image. As to the detection of oil spills on the sea, edge detection is an important technology in image processing. There are many algorithms of edge detection developed for image processing. These edge detection algorithms always have their own advantages and disadvantages in the image processing. Based on the primary requirements of edge detection of the oil spills" image on the sea, computation time and detection accuracy, we developed a fusion model. The model employed a BP neural net to fuse the detection results of simple operators. The reason we selected BP neural net as the fusion technology is that the relation between simple operators" result of edge gray level and the image"s true edge gray level is nonlinear, while BP neural net is good at solving the nonlinear identification problem. Therefore in this paper we trained a BP neural net by some oil spill images, then applied the BP fusion model on the edge detection of other oil spill images and obtained a good result. In this paper the detection result of some gradient operators and Laplacian operator are also compared with the result of BP fusion model to analysis the fusion effect. At last the paper pointed out that the fusion model has higher accuracy and higher speed in the processing oil spill image"s edge detection.

Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management.

PubMed

Cruz-Piris, Luis; Rivera, Diego; Fernandez, Susel; Marsa-Maestre, Ivan

2018-02-02

One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO) traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS) Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network.

Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management

PubMed Central

2018-01-01

One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO) traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS) Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network. PMID:29393884

Comparison of Adjacency and Distance-Based Approaches for Spatial Analysis of Multimodal Traffic Crash Data

NASA Astrophysics Data System (ADS)

Gill, G.; Sakrani, T.; Cheng, W.; Zhou, J.

2017-09-01

Many studies have utilized the spatial correlations among traffic crash data to develop crash prediction models with the aim to investigate the influential factors or predict crash counts at different sites. The spatial correlation have been observed to account for heterogeneity in different forms of weight matrices which improves the estimation performance of models. But very rarely have the weight matrices been compared for the prediction accuracy for estimation of crash counts. This study was targeted at the comparison of two different approaches for modelling the spatial correlations among crash data at macro-level (County). Multivariate Full Bayesian crash prediction models were developed using Decay-50 (distance-based) and Queen-1 (adjacency-based) weight matrices for simultaneous estimation crash counts of four different modes: vehicle, motorcycle, bike, and pedestrian. The goodness-of-fit and different criteria for accuracy at prediction of crash count reveled the superiority of Decay-50 over Queen-1. Decay-50 was essentially different from Queen-1 with the selection of neighbors and more robust spatial weight structure which rendered the flexibility to accommodate the spatially correlated crash data. The consistently better performance of Decay-50 at prediction accuracy further bolstered its superiority. Although the data collection efforts to gather centroid distance among counties for Decay-50 may appear to be a downside, but the model has a significant edge to fit the crash data without losing the simplicity of computation of estimated crash count.

New scheme for image edge detection using the switching mechanism of nonlinear optical material

NASA Astrophysics Data System (ADS)

Pahari, Nirmalya; Mukhopadhyay, Sourangshu

2006-03-01

The limitations of electronics in conducting parallel arithmetic, algebraic, and logic processing are well known. Very high-speed (terahertz) performance cannot be expected in conventional electronic mechanisms. To achieve such performance we can introduce optics instead of electronics for information processing, computing, and data handling. Nonlinear optical material (NOM) is a successful candidate in this regard to play a major role in the domain of optically controlled switching systems. The character of some NOMs is such as to reflect the probe beam in the presence of two read beams (or pump beams) exciting the material from opposite directions, using the principle of four-wave mixing. In image processing, edge extraction from an image is an important and essential task. Several optical methods of digital image processing are used for properly evaluating the image edges. We propose here a new method of image edge detection, extraction, and enhancement by use of AND-based switching operations with NOM. In this process we have used the optically inverted image of a supplied image. This can be obtained by the EXOR switching operation of the NOM.

Augmented reality enabling intelligence exploitation at the edge

NASA Astrophysics Data System (ADS)

Kase, Sue E.; Roy, Heather; Bowman, Elizabeth K.; Patton, Debra

2015-05-01

Today's Warfighters need to make quick decisions while interacting in densely populated environments comprised of friendly, hostile, and neutral host nation locals. However, there is a gap in the real-time processing of big data streams for edge intelligence. We introduce a big data processing pipeline called ARTEA that ingests, monitors, and performs a variety of analytics including noise reduction, pattern identification, and trend and event detection in the context of an area of operations (AOR). Results of the analytics are presented to the Soldier via an augmented reality (AR) device Google Glass (Glass). Non-intrusive AR devices such as Glass can visually communicate contextually relevant alerts to the Soldier based on the current mission objectives, time, location, and observed or sensed activities. This real-time processing and AR presentation approach to knowledge discovery flattens the intelligence hierarchy enabling the edge Soldier to act as a vital and active participant in the analysis process. We report preliminary observations testing ARTEA and Glass in a document exploitation and person of interest scenario simulating edge Soldier participation in the intelligence process in disconnected deployment conditions.

EDGE(3): a web-based solution for management and analysis of Agilent two color microarray experiments.

PubMed

Vollrath, Aaron L; Smith, Adam A; Craven, Mark; Bradfield, Christopher A

2009-09-04

The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE(3) was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users. EDGE(3) has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE3 has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE(3) is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image. Here, we present EDGE(3), an open-source, web-based application that allows for the storage, analysis, and controlled sharing of transcription-based microarray data generated on the Agilent DNA platform. In addition, EDGE(3) provides a means for managing RNA samples and arrays during the hybridization process. EDGE(3) is freely available for download at http://edge.oncology.wisc.edu/.

Vehicle license plate recognition in dense fog based on improved atmospheric scattering model

NASA Astrophysics Data System (ADS)

Tang, Chunming; Lin, Jun; Chen, Chunkai; Dong, Yancheng

2018-04-01

An effective method based on improved atmospheric scattering model is proposed in this paper to handle the problem of the vehicle license plate location and recognition in dense fog. Dense fog detection is performed firstly by the top-hat transformation and the vertical edge detection, and the moving vehicle image is separated from the traffic video image. After the vehicle image is decomposed into two layers: structure and texture layers, the glow layer is separated from the structure layer to get the background layer. Followed by performing the mean-pooling and the bicubic interpolation algorithm, the atmospheric light map of the background layer can be predicted, meanwhile the transmission of the background layer is estimated through the grayed glow layer, whose gray value is altered by linear mapping. Then, according to the improved atmospheric scattering model, the final restored image can be obtained by fusing the restored background layer and the optimized texture layer. License plate location is performed secondly by a series of morphological operations, connected domain analysis and various validations. Characters extraction is achieved according to the projection. Finally, an offline trained pattern classifier of hybrid discriminative restricted boltzmann machines (HDRBM) is applied to recognize the characters. Experimental results on thorough data sets are reported to demonstrate that the proposed method can achieve high recognition accuracy and works robustly in the dense fog traffic environment during 24h or one day.

Wear Detection of Drill Bit by Image-based Technique

NASA Astrophysics Data System (ADS)

Sukeri, Maziyah; Zulhilmi Paiz Ismadi, Mohd; Rahim Othman, Abdul; Kamaruddin, Shahrul

2018-03-01

Image processing for computer vision function plays an essential aspect in the manufacturing industries for the tool condition monitoring. This study proposes a dependable direct measurement method to measure the tool wear using image-based analysis. Segmentation and thresholding technique were used as the means to filter and convert the colour image to binary datasets. Then, the edge detection method was applied to characterize the edge of the drill bit. By using cross-correlation method, the edges of original and worn drill bits were correlated to each other. Cross-correlation graphs were able to detect the difference of the worn edge despite small difference between the graphs. Future development will focus on quantifying the worn profile as well as enhancing the sensitivity of the technique.

A Survey on Data Storage and Information Discovery in the WSANs-Based Edge Computing Systems

PubMed Central

Liang, Junbin; Liu, Renping; Ni, Wei; Li, Yin; Li, Ran; Ma, Wenpeng; Qi, Chuanda

2018-01-01

In the post-Cloud era, the proliferation of Internet of Things (IoT) has pushed the horizon of Edge computing, which is a new computing paradigm with data processed at the edge of the network. As the important systems of Edge computing, wireless sensor and actuator networks (WSANs) play an important role in collecting and processing the sensing data from the surrounding environment as well as taking actions on the events happening in the environment. In WSANs, in-network data storage and information discovery schemes with high energy efficiency, high load balance and low latency are needed because of the limited resources of the sensor nodes and the real-time requirement of some specific applications, such as putting out a big fire in a forest. In this article, the existing schemes of WSANs on data storage and information discovery are surveyed with detailed analysis on their advancements and shortcomings, and possible solutions are proposed on how to achieve high efficiency, good load balance, and perfect real-time performances at the same time, hoping that it can provide a good reference for the future research of the WSANs-based Edge computing systems. PMID:29439442

A Survey on Data Storage and Information Discovery in the WSANs-Based Edge Computing Systems.

PubMed

Ma, Xingpo; Liang, Junbin; Liu, Renping; Ni, Wei; Li, Yin; Li, Ran; Ma, Wenpeng; Qi, Chuanda

2018-02-10

In the post-Cloud era, the proliferation of Internet of Things (IoT) has pushed the horizon of Edge computing, which is a new computing paradigm with data are processed at the edge of the network. As the important systems of Edge computing, wireless sensor and actuator networks (WSANs) play an important role in collecting and processing the sensing data from the surrounding environment as well as taking actions on the events happening in the environment. In WSANs, in-network data storage and information discovery schemes with high energy efficiency, high load balance and low latency are needed because of the limited resources of the sensor nodes and the real-time requirement of some specific applications, such as putting out a big fire in a forest. In this article, the existing schemes of WSANs on data storage and information discovery are surveyed with detailed analysis on their advancements and shortcomings, and possible solutions are proposed on how to achieve high efficiency, good load balance, and perfect real-time performances at the same time, hoping that it can provide a good reference for the future research of the WSANs-based Edge computing systems.

Investigation of the effectiveness of traffic sign training in terms of training methods and sign characteristics.

PubMed

Ng, Annie W Y; Chan, Alan H S

2011-06-01

This research investigated whether different training methods had any effect on the effectiveness of traffic sign training and whether there were any relationships between traffic sign characteristics and effectiveness of the training. Thirty-six participants were randomly assigned into 4 equal-sized groups (control, paired-associate learning, recall training, and recognition training) to study the learnability of Mainland China traffic signs. In paired-associate learning, participants studied each traffic sign along with a referent describing its meaning. In addition to being informed of the meaning of traffic signs, both recall training and recognition training provided participants with questions and feedback. For recall training, the questioning process was a recall task in which participants had to produce a meaning for a given traffic sign from memory. For recognition training, the questioning process was a recognition task that required participants to identify the most appropriate referent corresponding to a given sign. No traffic sign training was given to the control group. Each training method significantly improved comprehension of the meaning of traffic signs. Participants from recall training performed better in a posttraining test than those from paired-associate learning and recognition training, indicating that the recall training elicited a deeper level of learning. In addition, questioning and feedback had a positive influence on training effectiveness. Performance in the posttest was found to be better when the questioning process matched the test process. Regarding the traffic sign characteristics, semantic closeness had a long-lasting effect, in terms of the timescale of this experiment on traffic sign comprehension, and traffic signs were perceived as more meaningful after their intended meanings were studied. Recall training is more effective in enhancing comprehension of traffic signs than paired-associate learning and recognition training. The findings of this study provide a basis for useful recommendations for designing symbol-training programs to improve road safety for road users.

The effects of lane width, shoulder width, and road cross-sectional reallocation on drivers' behavioral adaptations.

PubMed

Mecheri, Sami; Rosey, Florence; Lobjois, Régis

2017-07-01

Previous research has shown that lane-width reduction makes drivers operate vehicles closer to the center of the road whereas hard-shoulder widening induces a position farther away from the road's center. The goal of the present driving-simulator study was twofold. First, it was aimed at further investigating the respective effects of lane and shoulder width on in-lane positioning strategies, by examining vehicle distance from the center of the lane. The second aim was to assess the impact on safety of three possible cross-sectional reallocations of the width of the road (i.e., three lane-width reductions with concomitant shoulder widening at a fixed cross-sectional width) as compared to a control road. The results confirmed that lane-width reduction made participants drive closer to the road's center. However, in-lane position was affected differently by lane narrowing, depending on the traffic situation. In the absence of oncoming traffic, lane narrowing gave rise to significant shifts in the car's distance from the lane's center toward the edge line, whereas this distance remained similar across lane widths during traffic periods. When the shoulders were at least 0.50m wide, participants drove farther away from both the road center and the lane center. Road reallocation operations resulted in vehicles positioned farther away from the edge of the road and less swerving behavior, without generating higher driving speeds. Finally, it is argued that road-space reallocation may serve as a good low-cost tool for providing a recovery area for steering errors, without impairing drivers' behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

Enabling the democratization of the genomics revolution with a fully integrated web-based bioinformatics platform, Version 1.5 and 1.x.

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

Chain, Patrick; Lo, Chien-Chi; Li, Po-E

EDGE bioinformatics was developed to help biologists process Next Generation Sequencing data (in the form of raw FASTQ files), even if they have little to no bioinformatics expertise. EDGE is a highly integrated and interactive web-based platform that is capable of running many of the standard analyses that biologists require for viral, bacterial/archaeal, and metagenomic samples. EDGE provides the following analytical workflows: quality trimming and host removal, assembly and annotation, comparisons against known references, taxonomy classification of reads and contigs, whole genome SNP-based phylogenetic analysis, and PCR analysis. EDGE provides an intuitive web-based interface for user input, allows users tomore » visualize and interact with selected results (e.g. JBrowse genome browser), and generates a final detailed PDF report. Results in the form of tables, text files, graphic files, and PDFs can be downloaded. A user management system allows tracking of an individual’s EDGE runs, along with the ability to share, post publicly, delete, or archive their results.« less

Processing circuitry for single channel radiation detector

NASA Technical Reports Server (NTRS)

Holland, Samuel D. (Inventor); Delaune, Paul B. (Inventor); Turner, Kathryn M. (Inventor)

2009-01-01

Processing circuitry is provided for a high voltage operated radiation detector. An event detector utilizes a comparator configured to produce an event signal based on a leading edge threshold value. A preferred event detector does not produce another event signal until a trailing edge threshold value is satisfied. The event signal can be utilized for counting the number of particle hits and also for controlling data collection operation for a peak detect circuit and timer. The leading edge threshold value is programmable such that it can be reprogrammed by a remote computer. A digital high voltage control is preferably operable to monitor and adjust high voltage for the detector.

Guide to long term pavement performance (LTPP) traffic data collection and processing

DOT National Transportation Integrated Search

2000-04-11

The goal of this report is to document the process and procedures used by LTPP to collect and store the traffic data used to estimate pavement loadings. This first section of this report provides introductory material on the traffic data collection p...

Post-processing techniques to enhance reliability of assignment algorithm based performance measures : [technical summary].

DOT National Transportation Integrated Search

2011-01-01

Travel demand modeling plays a key role in the transportation system planning and evaluation process. The four-step sequential travel demand model is the most widely used technique in practice. Traffic assignment is the key step in the conventional f...

At the Intersection of Networks and Highly Interactive Online Games

NASA Astrophysics Data System (ADS)

Armitage, Grenville

The game industry continues to evolves its techniques for extracting the most realistic 'immersion' experience for players given the vagaries on best-effort Internet service. A key challenge for service providers is understanding the characteristics of traffic imposed on networks by games, and their service quality requirements. Interactive online games are particularly susceptible to the side effects of other non-interactive (or delay- and loss-tolerant) traffic sharing next- generation access links. This creates challenges out toward the edges, where high-speed home LANs squeeze through broadband consumer access links to reach the Internet. In this chapter we identify a range of research work exploring many issues associated with the intersection of highly interactive games and the Internet, and hopefully stimulate some further thinking along these lines.

Single-scale center-surround Retinex based restoration of low-illumination images with edge enhancement

NASA Astrophysics Data System (ADS)

Kwok, Ngaiming; Shi, Haiyan; Peng, Yeping; Wu, Hongkun; Li, Ruowei; Liu, Shilong; Rahman, Md Arifur

2018-04-01

Restoring images captured under low-illuminations is an essential front-end process for most image based applications. The Center-Surround Retinex algorithm has been a popular approach employed to improve image brightness. However, this algorithm in its basic form, is known to produce color degradations. In order to mitigate this problem, here the Single-Scale Retinex algorithm is modifid as an edge extractor while illumination is recovered through a non-linear intensity mapping stage. The derived edges are then integrated with the mapped image to produce the enhanced output. Furthermore, in reducing color distortion, the process is conducted in the magnitude sorted domain instead of the conventional Red-Green-Blue (RGB) color channels. Experimental results had shown that improvements with regard to mean brightness, colorfulness, saturation, and information content can be obtained.

Electrochemistry at Edge of Single Graphene Layer in a Nanopore

PubMed Central

Banerjee, Shouvik; Shim, Jiwook; Rivera, Jose; Jin, Xiaozhong; Estrada, David; Solovyeva, Vita; You, Xiuque; Pak, James; Pop, Eric; Aluru, Narayana; Bashir, Rashid

2013-01-01

We study the electrochemistry of single layer graphene edges using a nanopore-based structure consisting of stacked graphene and Al2O3 dielectric layers. Nanopores, with diameters ranging from 5 to 20 nm, are formed by an electron beam sculpting process on the stacked layers. This leads to unique edge structure which, along with the atomically thin nature of the embedded graphene electrode, demonstrates electrochemical current densities as high as 1.2 × 104 A/cm2. The graphene edge embedded structure offers a unique capability to study the electrochemical exchange at an individual graphene edge, isolated from the basal plane electrochemical activity. We also report ionic current modulation in the nanopore by biasing the embedded graphene terminal with respect to the electrodes in the fluid. The high electrochemical specific current density for a graphene nanopore-based device can have many applications in sensitive chemical and biological sensing, and energy storage devices. PMID:23249127

Real-time model-based vision system for object acquisition and tracking

NASA Technical Reports Server (NTRS)

Wilcox, Brian; Gennery, Donald B.; Bon, Bruce; Litwin, Todd

1987-01-01

A machine vision system is described which is designed to acquire and track polyhedral objects moving and rotating in space by means of two or more cameras, programmable image-processing hardware, and a general-purpose computer for high-level functions. The image-processing hardware is capable of performing a large variety of operations on images and on image-like arrays of data. Acquisition utilizes image locations and velocities of the features extracted by the image-processing hardware to determine the three-dimensional position, orientation, velocity, and angular velocity of the object. Tracking correlates edges detected in the current image with edge locations predicted from an internal model of the object and its motion, continually updating velocity information to predict where edges should appear in future frames. With some 10 frames processed per second, real-time tracking is possible.

The Edge-Disjoint Path Problem on Random Graphs by Message-Passing.

PubMed

Altarelli, Fabrizio; Braunstein, Alfredo; Dall'Asta, Luca; De Bacco, Caterina; Franz, Silvio

2015-01-01

We present a message-passing algorithm to solve a series of edge-disjoint path problems on graphs based on the zero-temperature cavity equations. Edge-disjoint paths problems are important in the general context of routing, that can be defined by incorporating under a unique framework both traffic optimization and total path length minimization. The computation of the cavity equations can be performed efficiently by exploiting a mapping of a generalized edge-disjoint path problem on a star graph onto a weighted maximum matching problem. We perform extensive numerical simulations on random graphs of various types to test the performance both in terms of path length minimization and maximization of the number of accommodated paths. In addition, we test the performance on benchmark instances on various graphs by comparison with state-of-the-art algorithms and results found in the literature. Our message-passing algorithm always outperforms the others in terms of the number of accommodated paths when considering non trivial instances (otherwise it gives the same trivial results). Remarkably, the largest improvement in performance with respect to the other methods employed is found in the case of benchmarks with meshes, where the validity hypothesis behind message-passing is expected to worsen. In these cases, even though the exact message-passing equations do not converge, by introducing a reinforcement parameter to force convergence towards a sub optimal solution, we were able to always outperform the other algorithms with a peak of 27% performance improvement in terms of accommodated paths. On random graphs, we numerically observe two separated regimes: one in which all paths can be accommodated and one in which this is not possible. We also investigate the behavior of both the number of paths to be accommodated and their minimum total length.

The Edge-Disjoint Path Problem on Random Graphs by Message-Passing

PubMed Central

2015-01-01

We present a message-passing algorithm to solve a series of edge-disjoint path problems on graphs based on the zero-temperature cavity equations. Edge-disjoint paths problems are important in the general context of routing, that can be defined by incorporating under a unique framework both traffic optimization and total path length minimization. The computation of the cavity equations can be performed efficiently by exploiting a mapping of a generalized edge-disjoint path problem on a star graph onto a weighted maximum matching problem. We perform extensive numerical simulations on random graphs of various types to test the performance both in terms of path length minimization and maximization of the number of accommodated paths. In addition, we test the performance on benchmark instances on various graphs by comparison with state-of-the-art algorithms and results found in the literature. Our message-passing algorithm always outperforms the others in terms of the number of accommodated paths when considering non trivial instances (otherwise it gives the same trivial results). Remarkably, the largest improvement in performance with respect to the other methods employed is found in the case of benchmarks with meshes, where the validity hypothesis behind message-passing is expected to worsen. In these cases, even though the exact message-passing equations do not converge, by introducing a reinforcement parameter to force convergence towards a sub optimal solution, we were able to always outperform the other algorithms with a peak of 27% performance improvement in terms of accommodated paths. On random graphs, we numerically observe two separated regimes: one in which all paths can be accommodated and one in which this is not possible. We also investigate the behavior of both the number of paths to be accommodated and their minimum total length. PMID:26710102

Heterogeneity Index for the Assessment of Relationship Between Land Use Pattern and Road Traffic Congestion in Apapa-Oworoshoki Express way, Lagos Metropolis

NASA Astrophysics Data System (ADS)

Alaigba, D. B.; Soumah, M.; Banjo, M. O.

2017-05-01

The problem of urban mobility is complicated by traffic delay, resulting from poor planning, high population density and poor condition of roads within urban spaces. This study assessed traffic congestion resulting from differential contribution made by various land-uses along Apapa-Oworoshoki expressway in Lagos metropolis. The data for this study was from both primary and secondary sources; GPS point data was collected at selected points for traffic volume count; observation of the nature of vehicular traffic congestion, and land use types along the corridor. Existing data on traffic count along the corridor, connectivity map and land use map sourced from relevant authorities were acquired. Traffic congestion within the area was estimated using volume capacity ratio (V/C). Heterogeneity Index was developed and used to quantify the percentage contribution to traffic volume from various land-use categories. Analytical Hierarchical Processing (AHP) and knowledge-based weighting were used to rank the importance of different heterogeneity indices. Results showed significant relationship between the degree of heterogeneity of the land use pattern and road traffic congestion. Volume Capacity Ratio computed revealed that the route corridor exceeds its designed capacity in the southward direction between the hours of 8am and 12pm on working days. Five major nodes were analyzed along the corridor, and were all above the expected Passenger Car Unit (PCU), these are "Oshodi" 15 %, "Airport junction" 10 %, "Cele bus stop" 21 %, "Mile 2" 14 %, "Berger" 15 % and "Tincan bus stop" 33 % indicating heavy traffic congestion.

Citizen Science for Traffic Planning: A Practical Example

NASA Astrophysics Data System (ADS)

Rieke, Matthes; Stasch, Christoph; Autermann, Christian; de Wall, Arne; Remke, Albert; Wulffius, Herwig; Jirka, Simon

2017-04-01

Measures affecting traffic flows in urban areas, e.g. changing the configuration of traffic lights, are often causing emotional debates by citizens who are affected by these measures. Up to now, citizens are usually not involved in traffic planning and the evaluation of the decisions that were taken. The enviroCar project provides an open platform for collecting and analyzing car sensor data with GPS position data. On the hardware side, enviroCar relies on using Android smartphones and OBD-II Bluetooth adapters. A Web server component collects and aggregates the readings from the cars, anonymizes them and publishes the data as open data which scientists, public administrations or other third parties can utilize for further analysis. In this work, we provide a general overview on the enviroCar project and present a project in a mid-size city in Germany. The city's administration utilized the enviroCar platform with the help of a traffic system consultancy for including citizens in the evaluation process of different traffic light configurations along major traffic axes. Therefore, a public campaign was started including local workshops to engage the citizens. More than 150 citizens were actively collecting more about 9.500 tracks including about 2.5 million measurements. Dedicated evaluation results for the different traffic axes were computed based on the collected data set. Because the data is publicly available as open data, others may prove and reproduce the evaluation results contributing to an objective discussion of traffic planning measures. In summary, the project illustrates how Citizen Science methods and technologies improve traffic planning and related discussions.

Reduction of wafer-edge overlay errors using advanced correction models, optimized for minimal metrology requirements

NASA Astrophysics Data System (ADS)

Kim, Min-Suk; Won, Hwa-Yeon; Jeong, Jong-Mun; Böcker, Paul; Vergaij-Huizer, Lydia; Kupers, Michiel; Jovanović, Milenko; Sochal, Inez; Ryan, Kevin; Sun, Kyu-Tae; Lim, Young-Wan; Byun, Jin-Moo; Kim, Gwang-Gon; Suh, Jung-Joon

2016-03-01

In order to optimize yield in DRAM semiconductor manufacturing for 2x nodes and beyond, the (processing induced) overlay fingerprint towards the edge of the wafer needs to be reduced. Traditionally, this is achieved by acquiring denser overlay metrology at the edge of the wafer, to feed field-by-field corrections. Although field-by-field corrections can be effective in reducing localized overlay errors, the requirement for dense metrology to determine the corrections can become a limiting factor due to a significant increase of metrology time and cost. In this study, a more cost-effective solution has been found in extending the regular correction model with an edge-specific component. This new overlay correction model can be driven by an optimized, sparser sampling especially at the wafer edge area, and also allows for a reduction of noise propagation. Lithography correction potential has been maximized, with significantly less metrology needs. Evaluations have been performed, demonstrating the benefit of edge models in terms of on-product overlay performance, as well as cell based overlay performance based on metrology-to-cell matching improvements. Performance can be increased compared to POR modeling and sampling, which can contribute to (overlay based) yield improvement. Based on advanced modeling including edge components, metrology requirements have been optimized, enabling integrated metrology which drives down overall metrology fab footprint and lithography cycle time.

Mapping AIS coverage for trusted surveillance

NASA Astrophysics Data System (ADS)

Lapinski, Anna-Liesa S.; Isenor, Anthony W.

2010-10-01

Automatic Identification System (AIS) is an unattended vessel reporting system developed for collision avoidance. Shipboard AIS equipment automatically broadcasts vessel positional data at regular intervals. The real-time position and identity data from a vessel is received by other vessels in the area thereby assisting with local navigation. As well, AIS broadcasts are beneficial to those concerned with coastal and harbour security. Land-based AIS receiving stations can also collect the AIS broadcasts. However, reception at the land station is dependent upon the ship's position relative to the receiving station. For AIS to be used as a trusted surveillance system, the characteristics of the AIS coverage area in the vicinity of the station (or stations) should be understood. This paper presents some results of a method being investigated at DRDC Atlantic, Canada) to map the AIS coverage characteristics of a dynamic AIS reception network. The method is shown to clearly distinguish AIS reception edges from those edges caused by vessel traffic patterns. The method can also be used to identify temporal changes in the coverage area, an important characteristic for local maritime security surveillance activities. Future research using the coverage estimate technique is also proposed to support surveillance activities.

Complex Network Theory Applied to the Growth of Kuala Lumpur's Public Urban Rail Transit Network.

PubMed

Ding, Rui; Ujang, Norsidah; Hamid, Hussain Bin; Wu, Jianjun

2015-01-01

Recently, the number of studies involving complex network applications in transportation has increased steadily as scholars from various fields analyze traffic networks. Nonetheless, research on rail network growth is relatively rare. This research examines the evolution of the Public Urban Rail Transit Networks of Kuala Lumpur (PURTNoKL) based on complex network theory and covers both the topological structure of the rail system and future trends in network growth. In addition, network performance when facing different attack strategies is also assessed. Three topological network characteristics are considered: connections, clustering and centrality. In PURTNoKL, we found that the total number of nodes and edges exhibit a linear relationship and that the average degree stays within the interval [2.0488, 2.6774] with heavy-tailed distributions. The evolutionary process shows that the cumulative probability distribution (CPD) of degree and the average shortest path length show good fit with exponential distribution and normal distribution, respectively. Moreover, PURTNoKL exhibits clear cluster characteristics; most of the nodes have a 2-core value, and the CPDs of the centrality's closeness and betweenness follow a normal distribution function and an exponential distribution, respectively. Finally, we discuss four different types of network growth styles and the line extension process, which reveal that the rail network's growth is likely based on the nodes with the biggest lengths of the shortest path and that network protection should emphasize those nodes with the largest degrees and the highest betweenness values. This research may enhance the networkability of the rail system and better shape the future growth of public rail networks.

Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors.

PubMed

Villaverde, Monica; Perez, David; Moreno, Felix

2015-11-17

The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor's infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

Reflection symmetry detection using locally affine invariant edge correspondence.

PubMed

Wang, Zhaozhong; Tang, Zesheng; Zhang, Xiao

2015-04-01

Reflection symmetry detection receives increasing attentions in recent years. The state-of-the-art algorithms mainly use the matching of intensity-based features (such as the SIFT) within a single image to find symmetry axes. This paper proposes a novel approach by establishing the correspondence of locally affine invariant edge-based features, which are superior to the intensity based in the aspects that it is insensitive to illumination variations, and applicable to textureless objects. The locally affine invariance is achieved by simple linear algebra for efficient and robust computations, making the algorithm suitable for detections under object distortions like perspective projection. Commonly used edge detectors and a voting process are, respectively, used before and after the edge description and matching steps to form a complete reflection detection pipeline. Experiments are performed using synthetic and real-world images with both multiple and single reflection symmetry axis. The test results are compared with existing algorithms to validate the proposed method.

KSC-05PD-1461

NASA Technical Reports Server (NTRS)

2005-01-01

KENNEDY SPACE CENTER, FLA. At the Shuttle Landing Facility on NASAs Kennedy Space Center, KSC Director Jim Kennedy talks to attendees at the ribbon-cutting ceremony for the new NASA Air Traffic Control Tower. The dedication took place in the SLFs new media facilities, which were built for the Return to Flight mission STS-114 and the landing of Shuttle Discovery. The facilities are co-located with the new control tower. The dedication and ribbon cutting were held at the base of the tower and included Center Director Jim Kennedy, Space Gateway Support President William A. Sample, External Relations Director Lisa Malone, Center Operations Director Scott D. Kerr, and KSC Safety Aviation Officer Albert E. Taff. The structure rises 110 feet over the midpoint of the runway and offers air traffic controllers a magnificent 360-degree view of Kennedy Space Center, Cape Canaveral Air Force Station and north Brevard County. It replaces the small, portable tower installed at the edge of the runway in 1986. The new control tower will manage all landings and departures from the SLF, including air traffic within the Kennedy Space Center-Cape Canaveral restricted airspace. The facility provides a 24-hour weather-observing facility providing official hourly weather observations for the SLF and the Cape Canaveral vicinity, including special observations for all launches and landings. State-of-the-art, weather-observing equipment has been installed for Space Shuttle landings and for serving conventional aircraft landing at the SLF. At this location, weather observers will have a multi- directional view of the weather conditions at the runway and Launch Complex 39.

Transport phenomena in helical edge state interferometers: A Green's function approach

NASA Astrophysics Data System (ADS)

Rizzo, Bruno; Arrachea, Liliana; Moskalets, Michael

2013-10-01

We analyze the current and the shot noise of an electron interferometer made of the helical edge states of a two-dimensional topological insulator within the framework of nonequilibrium Green's functions formalism. We study, in detail, setups with a single and with two quantum point contacts inducing scattering between the different edge states. We consider processes preserving the spin as well as the effect of spin-flip scattering. In the case of a single quantum point contact, a simple test based on the shot-noise measurement is proposed to quantify the strength of the spin-flip scattering. In the case of two single point contacts with the additional ingredient of gate voltages applied within a finite-size region at the top and bottom edges of the sample, we identify two types of interference processes in the behavior of the currents and the noise. One such process is analogous to that taking place in a Fabry-Pérot interferometer, while the second one corresponds to a configuration similar to a Mach-Zehnder interferometer. In the helical interferometer, these two processes compete.

A Global System for Transportation Simulation and Visualization in Emergency Evacuation Scenarios

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

Lu, Wei; Liu, Cheng; Thomas, Neil

2015-01-01

Simulation-based studies are frequently used for evacuation planning and decision making processes. Given the transportation systems complexity and data availability, most evacuation simulation models focus on certain geographic areas. With routine improvement of OpenStreetMap road networks and LandScanTM global population distribution data, we present WWEE, a uniform system for world-wide emergency evacuation simulations. WWEE uses unified data structure for simulation inputs. It also integrates a super-node trip distribution model as the default simulation parameter to improve the system computational performance. Two levels of visualization tools are implemented for evacuation performance analysis, including link-based macroscopic visualization and vehicle-based microscopic visualization. Formore » left-hand and right-hand traffic patterns in different countries, the authors propose a mirror technique to experiment with both scenarios without significantly changing traffic simulation models. Ten cities in US, Europe, Middle East, and Asia are modeled for demonstration. With default traffic simulation models for fast and easy-to-use evacuation estimation and visualization, WWEE also retains the capability of interactive operation for users to adopt customized traffic simulation models. For the first time, WWEE provides a unified platform for global evacuation researchers to estimate and visualize their strategies performance of transportation systems under evacuation scenarios.« less

Haptic Edge Detection Through Shear

NASA Astrophysics Data System (ADS)

Platkiewicz, Jonathan; Lipson, Hod; Hayward, Vincent

2016-03-01

Most tactile sensors are based on the assumption that touch depends on measuring pressure. However, the pressure distribution at the surface of a tactile sensor cannot be acquired directly and must be inferred from the deformation field induced by the touched object in the sensor medium. Currently, there is no consensus as to which components of strain are most informative for tactile sensing. Here, we propose that shape-related tactile information is more suitably recovered from shear strain than normal strain. Based on a contact mechanics analysis, we demonstrate that the elastic behavior of a haptic probe provides a robust edge detection mechanism when shear strain is sensed. We used a jamming-based robot gripper as a tactile sensor to empirically validate that shear strain processing gives accurate edge information that is invariant to changes in pressure, as predicted by the contact mechanics study. This result has implications for the design of effective tactile sensors as well as for the understanding of the early somatosensory processing in mammals.

Haptic Edge Detection Through Shear

PubMed Central

Platkiewicz, Jonathan; Lipson, Hod; Hayward, Vincent

2016-01-01

Most tactile sensors are based on the assumption that touch depends on measuring pressure. However, the pressure distribution at the surface of a tactile sensor cannot be acquired directly and must be inferred from the deformation field induced by the touched object in the sensor medium. Currently, there is no consensus as to which components of strain are most informative for tactile sensing. Here, we propose that shape-related tactile information is more suitably recovered from shear strain than normal strain. Based on a contact mechanics analysis, we demonstrate that the elastic behavior of a haptic probe provides a robust edge detection mechanism when shear strain is sensed. We used a jamming-based robot gripper as a tactile sensor to empirically validate that shear strain processing gives accurate edge information that is invariant to changes in pressure, as predicted by the contact mechanics study. This result has implications for the design of effective tactile sensors as well as for the understanding of the early somatosensory processing in mammals. PMID:27009331

Haptic Edge Detection Through Shear.

PubMed

Platkiewicz, Jonathan; Lipson, Hod; Hayward, Vincent

2016-03-24

Most tactile sensors are based on the assumption that touch depends on measuring pressure. However, the pressure distribution at the surface of a tactile sensor cannot be acquired directly and must be inferred from the deformation field induced by the touched object in the sensor medium. Currently, there is no consensus as to which components of strain are most informative for tactile sensing. Here, we propose that shape-related tactile information is more suitably recovered from shear strain than normal strain. Based on a contact mechanics analysis, we demonstrate that the elastic behavior of a haptic probe provides a robust edge detection mechanism when shear strain is sensed. We used a jamming-based robot gripper as a tactile sensor to empirically validate that shear strain processing gives accurate edge information that is invariant to changes in pressure, as predicted by the contact mechanics study. This result has implications for the design of effective tactile sensors as well as for the understanding of the early somatosensory processing in mammals.

Monitoring Street-Level Spatial-Temporal Variations of Carbon Monoxide in Urban Settings Using a Wireless Sensor Network (WSN) Framework

PubMed Central

Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang

2013-01-01

Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management. PMID:24287859

Monitoring street-level spatial-temporal variations of carbon monoxide in urban settings using a wireless sensor network (WSN) framework.

PubMed

Wen, Tzai-Hung; Jiang, Joe-Air; Sun, Chih-Hong; Juang, Jehn-Yih; Lin, Tzu-Shiang

2013-11-27

Air pollution has become a severe environmental problem due to urbanization and heavy traffic. Monitoring street-level air quality is an important issue, but most official monitoring stations are installed to monitor large-scale air quality conditions, and their limited spatial resolution cannot reflect the detailed variations in air quality that may be induced by traffic jams. By deploying wireless sensors on crossroads and main roads, this study established a pilot framework for a wireless sensor network (WSN)-based real-time monitoring system to understand street-level spatial-temporal changes of carbon monoxide (CO) in urban settings. The system consists of two major components. The first component is the deployment of wireless sensors. We deployed 44 sensor nodes, 40 transmitter nodes and four gateway nodes in this study. Each sensor node includes a signal processing module, a CO sensor and a wireless communication module. In order to capture realistic human exposure to traffic pollutants, all sensors were deployed at a height of 1.5 m on lampposts and traffic signs. The study area covers a total length of 1.5 km of Keelung Road in Taipei City. The other component is a map-based monitoring platform for sensor data visualization and manipulation in time and space. Using intensive real-time street-level monitoring framework, we compared the spatial-temporal patterns of air pollution in different time periods. Our results capture four CO concentration peaks throughout the day at the location, which was located along an arterial and nearby traffic sign. The hourly average could reach 5.3 ppm from 5:00 pm to 7:00 pm due to the traffic congestion. The proposed WSN-based framework captures detailed ground information and potential risk of human exposure to traffic-related air pollution. It also provides street-level insights into real-time monitoring for further early warning of air pollution and urban environmental management.

Heterogeneous delivering capability promotes traffic efficiency in complex networks

NASA Astrophysics Data System (ADS)

Zhu, Yan-Bo; Guan, Xiang-Min; Zhang, Xue-Jun

2015-12-01

Traffic is one of the most fundamental dynamical processes in networked systems. With the homogeneous delivery capability of nodes, the global dynamic routing strategy proposed by Ling et al. [Phys. Rev. E81, 016113 (2010)] adequately uses the dynamic information during the process and thus it can reach a quite high network capacity. In this paper, based on the global dynamic routing strategy, we proposed a heterogeneous delivery allocation strategy of nodes on scale-free networks with consideration of nodes degree. It is found that the network capacity as well as some other indexes reflecting transportation efficiency are further improved. Our work may be useful for the design of more efficient routing strategies in communication or transportation systems.

EDGE3: A web-based solution for management and analysis of Agilent two color microarray experiments

PubMed Central

Vollrath, Aaron L; Smith, Adam A; Craven, Mark; Bradfield, Christopher A

2009-01-01

Background The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE3 was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users. Results EDGE3 has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE3 has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE3 is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image. Conclusion Here, we present EDGE3, an open-source, web-based application that allows for the storage, analysis, and controlled sharing of transcription-based microarray data generated on the Agilent DNA platform. In addition, EDGE3 provides a means for managing RNA samples and arrays during the hybridization process. EDGE3 is freely available for download at . PMID:19732451

Fixed Point Learning Based Intelligent Traffic Control System

NASA Astrophysics Data System (ADS)

Zongyao, Wang; Cong, Sui; Cheng, Shao

2017-10-01

Fixed point learning has become an important tool to analyse large scale distributed system such as urban traffic network. This paper presents a fixed point learning based intelligence traffic network control system. The system applies convergence property of fixed point theorem to optimize the traffic flow density. The intelligence traffic control system achieves maximum road resources usage by averaging traffic flow density among the traffic network. The intelligence traffic network control system is built based on decentralized structure and intelligence cooperation. No central control is needed to manage the system. The proposed system is simple, effective and feasible for practical use. The performance of the system is tested via theoretical proof and simulations. The results demonstrate that the system can effectively solve the traffic congestion problem and increase the vehicles average speed. It also proves that the system is flexible, reliable and feasible for practical use.

An analysis of the low-earth-orbit communications environment

NASA Astrophysics Data System (ADS)

Diersing, Robert Joseph

Advances in microprocessor technology and availability of launch opportunities have caused interest in low-earth-orbit satellite based communications systems to increase dramatically during the past several years. In this research the capabilities of two low-cost, store-and-forward LEO communications satellites operating in the public domain are examined--PACSAT-1 (operated by the Radio Amateur Satellite Corporation) and UoSAT-3 (operated by the University of Surrey, England, Electrical Engineering Department). The file broadcasting and file transfer facilities are examined in detail and a simulation model of the downlink traffic pattern is developed. The simulator will aid the assessment of changes in design and implementation for other systems. The development of the downlink traffic simulator is based on three major parts. First, is a characterization of the low-earth-orbit operating environment along with preliminary measurements of the PACSAT-1 and UoSAT-3 systems including: satellite visibility constraints on communications, monitoring equipment configuration, link margin computations, determination of block and bit error rates, and establishing typical data capture rates for ground stations using computer-pointed directional antennas and fixed omni-directional antennas. Second, arrival rates for successful and unsuccessful file server connections are established along with transaction service times. Downlink traffic has been further characterized by measuring: frame and byte counts for all data-link layer traffic; 30-second interval average response time for all traffic and for file server traffic only; file server response time on a per-connection basis; and retry rates for information and supervisory frames. Finally, the model is verified by comparison with measurements of actual traffic not previously used in the model building process. The simulator is then used to predict operation of the PACSAT-1 satellite with modifications to the original design.

Understanding the PM2.5 imbalance between a far and near-road location: Results of high temporal frequency source apportionment and parameterization of black carbon

NASA Astrophysics Data System (ADS)

Sofowote, U. M.; Healy, R. M.; Su, Y.; Debosz, J.; Noble, M.; Munoz, A.; Jeong, C.-H.; Wang, J. M.; Hilker, N.; Evans, G. J.; Hopke, P. K.

2018-01-01

The differences in PM2.5 concentrations between two relatively close stations, one situated near a major highway and the other much more distant were used to develop a protocol for determining the impact of highway traffic on particulate matter concentrations at the roadside. The roadside station was <15 m away from the edge of a major highway while the other was located ∼170 m away. The roadside station contains a suite of continuous instrumentation capable of near-real-time speciation of PM2.5. The particulate matter difference, formally termed the PM2.5 imbalance was arbitrarily defined as a case wherein |Near-road PM2.5 - Far from road PM2.5|/Near-road PM2.5 ≳50%. Of interest was the variation of multi-time factors based on ME2 analyses of the speciation data from the roadside station during these imbalance events. Of the 7 mass-contributing ME2 factors, a black carbon factor was determined to be the major cause of the PM2.5 imbalance and was especially dominant for the case when PM2.5 concentrations at the roadside station were greater than the farther-station PM2.5. The black carbon concentrations observed during these specific events were further regressed against other traffic-related and meteorological parameters with two nonlinear optimization algorithms (generalized reduced gradient and rules ensemble) in our attempts to model any potential relationships. It was observed that the traffic counts of heavy duty vehicles (predominantly diesel-powered) dominated the relationship with black carbon while contributions from light duty vehicles were negligible during these [PM2.5]Roadside > [PM2.5]Farther events at the roadside station. This work details the most critical ways that highway traffic can contribute to local ambient PM2.5 concentrations that commuters are exposed to and will be important in informing policies and strategies for particulate matter pollution reduction.

The new car following model considering vehicle dynamics influence and numerical simulation

NASA Astrophysics Data System (ADS)

Sun, Dihua; Liu, Hui; Zhang, Geng; Zhao, Min

2015-12-01

In this paper, the car following model is investigated by considering the vehicle dynamics in a cyber physical view. In fact, that driving is a typical cyber physical process which couples the cyber aspect of the vehicles' information and driving decision tightly with the dynamics and physics of the vehicles and traffic environment. However, the influence from the physical (vehicle) view was been ignored in the previous car following models. In order to describe the car following behavior more reasonably in real traffic, a new car following model by considering vehicle dynamics (for short, D-CFM) is proposed. In this paper, we take the full velocity difference (FVD) car following model as a case. The stability condition is given on the base of the control theory. The analytical method and numerical simulation results show that the new models can describe the evolution of traffic congestion. The simulations also show vehicles with a more actual acceleration of starting process than early models.

Computing local edge probability in natural scenes from a population of oriented simple cells

PubMed Central

Ramachandra, Chaithanya A.; Mel, Bartlett W.

2013-01-01

A key computation in visual cortex is the extraction of object contours, where the first stage of processing is commonly attributed to V1 simple cells. The standard model of a simple cell—an oriented linear filter followed by a divisive normalization—fits a wide variety of physiological data, but is a poor performing local edge detector when applied to natural images. The brain's ability to finely discriminate edges from nonedges therefore likely depends on information encoded by local simple cell populations. To gain insight into the corresponding decoding problem, we used Bayes's rule to calculate edge probability at a given location/orientation in an image based on a surrounding filter population. Beginning with a set of ∼ 100 filters, we culled out a subset that were maximally informative about edges, and minimally correlated to allow factorization of the joint on- and off-edge likelihood functions. Key features of our approach include a new, efficient method for ground-truth edge labeling, an emphasis on achieving filter independence, including a focus on filters in the region orthogonal rather than tangential to an edge, and the use of a customized parametric model to represent the individual filter likelihood functions. The resulting population-based edge detector has zero parameters, calculates edge probability based on a sum of surrounding filter influences, is much more sharply tuned than the underlying linear filters, and effectively captures fine-scale edge structure in natural scenes. Our findings predict nonmonotonic interactions between cells in visual cortex, wherein a cell may for certain stimuli excite and for other stimuli inhibit the same neighboring cell, depending on the two cells' relative offsets in position and orientation, and their relative activation levels. PMID:24381295

Algorithm for Automated Detection of Edges of Clouds

NASA Technical Reports Server (NTRS)

Ward, Jennifer G.; Merceret, Francis J.

2006-01-01

An algorithm processes cloud-physics data gathered in situ by an aircraft, along with reflectivity data gathered by ground-based radar, to determine whether the aircraft is inside or outside a cloud at a given time. A cloud edge is deemed to be detected when the in/out state changes, subject to a hysteresis constraint. Such determinations are important in continuing research on relationships among lightning, electric charges in clouds, and decay of electric fields with distance from cloud edges.

Real-time biscuit tile image segmentation method based on edge detection.

PubMed

Matić, Tomislav; Aleksi, Ivan; Hocenski, Željko; Kraus, Dieter

2018-05-01

In this paper we propose a novel real-time Biscuit Tile Segmentation (BTS) method for images from ceramic tile production line. BTS method is based on signal change detection and contour tracing with a main goal of separating tile pixels from background in images captured on the production line. Usually, human operators are visually inspecting and classifying produced ceramic tiles. Computer vision and image processing techniques can automate visual inspection process if they fulfill real-time requirements. Important step in this process is a real-time tile pixels segmentation. BTS method is implemented for parallel execution on a GPU device to satisfy the real-time constraints of tile production line. BTS method outperforms 2D threshold-based methods, 1D edge detection methods and contour-based methods. Proposed BTS method is in use in the biscuit tile production line. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

76 FR 27743 - Notice of Availability of a Draft Environmental Assessment for a Proposed Airport Traffic Control...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-12

... Environmental Assessment for a Proposed Airport Traffic Control Tower and Base Building, University of Illinois... Availability of a Draft Environmental Assessment for a Proposed Airport Traffic Control Tower and Base Building...) proposes to fund, construct, and operate a new Airport Traffic Control Tower (ATCT) and Base Building at...

A novel scatter-matrix eigenvalues-based total variation (SMETV) regularization for medical image restoration

NASA Astrophysics Data System (ADS)

Huang, Zhenghua; Zhang, Tianxu; Deng, Lihua; Fang, Hao; Li, Qian

2015-12-01

Total variation(TV) based on regularization has been proven as a popular and effective model for image restoration, because of its ability of edge preserved. However, as the TV favors a piece-wise constant solution, the processing results in the flat regions of the image are easily produced "staircase effects", and the amplitude of the edges will be underestimated; the underlying cause of the problem is that the regularization parameter can not be changeable with spatial local information of image. In this paper, we propose a novel Scatter-matrix eigenvalues-based TV(SMETV) regularization with image blind restoration algorithm for deblurring medical images. The spatial information in different image regions is incorporated into regularization by using the edge indicator called difference eigenvalue to distinguish edges from flat areas. The proposed algorithm can effectively reduce the noise in flat regions as well as preserve the edge and detailed information. Moreover, it becomes more robust with the change of the regularization parameter. Extensive experiments demonstrate that the proposed approach produces results superior to most methods in both visual image quality and quantitative measures.

Sonification of network traffic flow for monitoring and situational awareness

PubMed Central

2018-01-01

Maintaining situational awareness of what is happening within a computer network is challenging, not only because the behaviour happens within machines, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation techniques are widely used to present information about network traffic dynamics. Although they provide operators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way. Also, because they require visual attention they are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system for monitoring computer networks to support network administrators’ situational awareness. SoNSTAR provides an auditory representation of all the TCP/IP traffic within a network based on the different traffic flows between between network hosts. A user study showed that SoNSTAR raises situational awareness levels by enabling operators to understand network behaviour and with the benefit of lower workload demands (as measured by the NASA TLX method) than visual techniques. SoNSTAR identifies network traffic features by inspecting the status flags of TCP/IP packet headers. Combinations of these features define particular traffic events which are mapped to recorded sounds to generate a soundscape that represents the real-time status of the network traffic environment. The sequence, timing, and loudness of the different sounds allow the network to be monitored and anomalous behaviour to be detected without the need to continuously watch a monitor screen. PMID:29672543

Sonification of network traffic flow for monitoring and situational awareness.

PubMed

Debashi, Mohamed; Vickers, Paul

2018-01-01

Maintaining situational awareness of what is happening within a computer network is challenging, not only because the behaviour happens within machines, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation techniques are widely used to present information about network traffic dynamics. Although they provide operators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way. Also, because they require visual attention they are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system for monitoring computer networks to support network administrators' situational awareness. SoNSTAR provides an auditory representation of all the TCP/IP traffic within a network based on the different traffic flows between between network hosts. A user study showed that SoNSTAR raises situational awareness levels by enabling operators to understand network behaviour and with the benefit of lower workload demands (as measured by the NASA TLX method) than visual techniques. SoNSTAR identifies network traffic features by inspecting the status flags of TCP/IP packet headers. Combinations of these features define particular traffic events which are mapped to recorded sounds to generate a soundscape that represents the real-time status of the network traffic environment. The sequence, timing, and loudness of the different sounds allow the network to be monitored and anomalous behaviour to be detected without the need to continuously watch a monitor screen.

Traffic and Driving Simulator Based on Architecture of Interactive Motion.

PubMed

Paz, Alexander; Veeramisti, Naveen; Khaddar, Romesh; de la Fuente-Mella, Hanns; Modorcea, Luiza

2015-01-01

This study proposes an architecture for an interactive motion-based traffic simulation environment. In order to enhance modeling realism involving actual human beings, the proposed architecture integrates multiple types of simulation, including: (i) motion-based driving simulation, (ii) pedestrian simulation, (iii) motorcycling and bicycling simulation, and (iv) traffic flow simulation. The architecture has been designed to enable the simulation of the entire network; as a result, the actual driver, pedestrian, and bike rider can navigate anywhere in the system. In addition, the background traffic interacts with the actual human beings. This is accomplished by using a hybrid mesomicroscopic traffic flow simulation modeling approach. The mesoscopic traffic flow simulation model loads the results of a user equilibrium traffic assignment solution and propagates the corresponding traffic through the entire system. The microscopic traffic flow simulation model provides background traffic around the vicinities where actual human beings are navigating the system. The two traffic flow simulation models interact continuously to update system conditions based on the interactions between actual humans and the fully simulated entities. Implementation efforts are currently in progress and some preliminary tests of individual components have been conducted. The implementation of the proposed architecture faces significant challenges ranging from multiplatform and multilanguage integration to multievent communication and coordination.

Traffic and Driving Simulator Based on Architecture of Interactive Motion

PubMed Central

Paz, Alexander; Veeramisti, Naveen; Khaddar, Romesh; de la Fuente-Mella, Hanns; Modorcea, Luiza

2015-01-01

This study proposes an architecture for an interactive motion-based traffic simulation environment. In order to enhance modeling realism involving actual human beings, the proposed architecture integrates multiple types of simulation, including: (i) motion-based driving simulation, (ii) pedestrian simulation, (iii) motorcycling and bicycling simulation, and (iv) traffic flow simulation. The architecture has been designed to enable the simulation of the entire network; as a result, the actual driver, pedestrian, and bike rider can navigate anywhere in the system. In addition, the background traffic interacts with the actual human beings. This is accomplished by using a hybrid mesomicroscopic traffic flow simulation modeling approach. The mesoscopic traffic flow simulation model loads the results of a user equilibrium traffic assignment solution and propagates the corresponding traffic through the entire system. The microscopic traffic flow simulation model provides background traffic around the vicinities where actual human beings are navigating the system. The two traffic flow simulation models interact continuously to update system conditions based on the interactions between actual humans and the fully simulated entities. Implementation efforts are currently in progress and some preliminary tests of individual components have been conducted. The implementation of the proposed architecture faces significant challenges ranging from multiplatform and multilanguage integration to multievent communication and coordination. PMID:26491711

Impact analysis of traffic-related air pollution based on real-time traffic and basic meteorological information.

PubMed

Pan, Long; Yao, Enjian; Yang, Yang

2016-12-01

With the rapid development of urbanization and motorization in China, traffic-related air pollution has become a major component of air pollution which constantly jeopardizes public health. This study proposes an integrated framework for estimating the concentration of traffic-related air pollution with real-time traffic and basic meteorological information and also for further evaluating the impact of traffic-related air pollution. First, based on the vehicle emission factor models sensitive to traffic status, traffic emissions are calculated according to the real-time link-based average traffic speed, traffic volume, and vehicular fleet composition. Then, based on differences in meteorological conditions, traffic pollution sources are divided into line sources and point sources, and the corresponding methods to determine the dynamic affecting areas are also proposed. Subsequently, with basic meteorological data, Gaussian dispersion model and puff integration model are applied respectively to estimate the concentration of traffic-related air pollution. Finally, the proposed estimating framework is applied to calculate the distribution of CO concentration in the main area of Beijing, and the population exposure is also calculated to evaluate the impact of traffic-related air pollution on public health. Results show that there is a certain correlation between traffic indicators (i.e., traffic speed and traffic intensity) of the affecting area and traffic-related CO concentration of the target grid, which indicates the methods to determine the affecting areas are reliable. Furthermore, the reliability of the proposed estimating framework is verified by comparing the predicted and the observed ambient CO concentration. In addition, results also show that the traffic-related CO concentration is higher in morning and evening peak hours, and has a heavier impact on public health within the Fourth Ring Road of Beijing due to higher population density and higher CO concentration under calm wind condition in this area. Copyright © 2016 Elsevier Ltd. All rights reserved.

A spatial editing and validation process for short count traffic data : final report, July 2006.

DOT National Transportation Integrated Search

2006-07-07

The Traffic Survey Unit (TSU) manages 40,000 traffic monitoring stations, of which 25,000 are updated annually. : These counts obtained by TSU play a crucial role in allocation of resources for the maintenance, upgrade, and : expansion of traffic inf...

A New Parallel Approach for Accelerating the GPU-Based Execution of Edge Detection Algorithms

PubMed Central

Emrani, Zahra; Bateni, Soroosh; Rabbani, Hossein

2017-01-01

Real-time image processing is used in a wide variety of applications like those in medical care and industrial processes. This technique in medical care has the ability to display important patient information graphi graphically, which can supplement and help the treatment process. Medical decisions made based on real-time images are more accurate and reliable. According to the recent researches, graphic processing unit (GPU) programming is a useful method for improving the speed and quality of medical image processing and is one of the ways of real-time image processing. Edge detection is an early stage in most of the image processing methods for the extraction of features and object segments from a raw image. The Canny method, Sobel and Prewitt filters, and the Roberts’ Cross technique are some examples of edge detection algorithms that are widely used in image processing and machine vision. In this work, these algorithms are implemented using the Compute Unified Device Architecture (CUDA), Open Source Computer Vision (OpenCV), and Matrix Laboratory (MATLAB) platforms. An existing parallel method for Canny approach has been modified further to run in a fully parallel manner. This has been achieved by replacing the breadth- first search procedure with a parallel method. These algorithms have been compared by testing them on a database of optical coherence tomography images. The comparison of results shows that the proposed implementation of the Canny method on GPU using the CUDA platform improves the speed of execution by 2–100× compared to the central processing unit-based implementation using the OpenCV and MATLAB platforms. PMID:28487831

A New Parallel Approach for Accelerating the GPU-Based Execution of Edge Detection Algorithms.

PubMed

Emrani, Zahra; Bateni, Soroosh; Rabbani, Hossein

2017-01-01

Real-time image processing is used in a wide variety of applications like those in medical care and industrial processes. This technique in medical care has the ability to display important patient information graphi graphically, which can supplement and help the treatment process. Medical decisions made based on real-time images are more accurate and reliable. According to the recent researches, graphic processing unit (GPU) programming is a useful method for improving the speed and quality of medical image processing and is one of the ways of real-time image processing. Edge detection is an early stage in most of the image processing methods for the extraction of features and object segments from a raw image. The Canny method, Sobel and Prewitt filters, and the Roberts' Cross technique are some examples of edge detection algorithms that are widely used in image processing and machine vision. In this work, these algorithms are implemented using the Compute Unified Device Architecture (CUDA), Open Source Computer Vision (OpenCV), and Matrix Laboratory (MATLAB) platforms. An existing parallel method for Canny approach has been modified further to run in a fully parallel manner. This has been achieved by replacing the breadth- first search procedure with a parallel method. These algorithms have been compared by testing them on a database of optical coherence tomography images. The comparison of results shows that the proposed implementation of the Canny method on GPU using the CUDA platform improves the speed of execution by 2-100× compared to the central processing unit-based implementation using the OpenCV and MATLAB platforms.

Comprehensibility of traffic signs among urban drivers in Turkey.

PubMed

Kirmizioglu, Erkut; Tuydes-Yaman, Hediye

2012-03-01

Traffic signs are commonly used traffic safety tools, mainly developed to provide crucial information in a short time to support safe drive; but the success depends on their comprehensibility by the drivers. Also, a sudden change in the traditionally used and accepted signs can cause significant safety problem, as in the case of cancellation of red oblique bars in 2004 as a part of the European Union Harmonization Process of Turkey. Having a severe traffic safety problem in Turkey, a need to assess both the comprehensibility of internationally accepted traffic signs and current level of driver education, was the main motivation behind this study. A paper-based survey study in 2009 that reached a sample of 1478 urban drivers in the City of Ankara, focused on the determination of comprehensibility of 30 selected traffic signs, which are commonly used and critical for safety, including two recently changed signs. The meaning of each sign is sought using an open-ended question format to capture different levels and types of comprehensions, which enabled the detection of "opposite" and "partially correct" answers besides "wrong" and "correct" ones. High comprehensibility of 9 control group signs shows the validity of the study. The recently changed signs are among the oppositely associated ones proving the increased risk in traffic safety and need for more aggressive campaigning to publicize them. Copyright © 2011 Elsevier Ltd. All rights reserved.

Network Visualization Project (NVP)

DTIC Science & Technology

2016-07-01

network visualization, network traffic analysis, network forensics 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF...shell, is a command-line framework used for network forensic analysis. Dshell processes existing pcap files and filters output information based on

Life cycle assessment framework of traffic systems based on microscopic simulation.

DOT National Transportation Integrated Search

2014-03-01

Transportation is an important infrastructure process needed in many steps of the supply chain of any product. Transportation-associated global impacts are therefore important factor influencing the sustainability of any product cycle. Moreover, traf...

Database architecture and query structures for probe data processing.

DOT National Transportation Integrated Search

2012-03-01

This report summarizes findings and implementations of probe vehicle data collection based on Bluetooth MAC address matching technology. Probe vehicle travel time data are studied in the following field deployment case studies: analysis of traffic ch...

Global Optimization of Emergency Evacuation Assignments

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

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

2006-01-01

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

Modification of strain and 2DEG density induced by wafer bending of AlGaN/GaN heterostructure: Influence of edges caused by processing

NASA Astrophysics Data System (ADS)

Wang, Ashu; Zeng, Lingyan; Wang, Wen; Calle, Fernando

2018-03-01

Due to the piezoelectricity, the density of 2DEG (NS) formed in the AlGaN/GaN heterostructure can be altered when it is deformed externally, which may be exploited to develop pressure sensors and to enhance the performance of power devices by stress engineering based on the heterostructure. In this paper, a 3D electro-mechanical simulation is presented to study how the induced strains and NS for the AlGaN/GaN wafer under bending exerted uniaxial stress are influenced by the edges caused by processing: the fabrication of the mesa used for isolation, the ohmic contact metal, the gate metal, and the passivation. Results show that the influences are dependent on distance between the edges, depth of the edges, and direction of the exerted uniaxial stress.

Edge-based image restoration.

PubMed

Rareş, Andrei; Reinders, Marcel J T; Biemond, Jan

2005-10-01

In this paper, we propose a new image inpainting algorithm that relies on explicit edge information. The edge information is used both for the reconstruction of a skeleton image structure in the missing areas, as well as for guiding the interpolation that follows. The structure reconstruction part exploits different properties of the edges, such as the colors of the objects they separate, an estimate of how well one edge continues into another one, and the spatial order of the edges with respect to each other. In order to preserve both sharp and smooth edges, the areas delimited by the recovered structure are interpolated independently, and the process is guided by the direction of the nearby edges. The novelty of our approach lies primarily in exploiting explicitly the constraint enforced by the numerical interpretation of the sequential order of edges, as well as in the pixel filling method which takes into account the proximity and direction of edges. Extensive experiments are carried out in order to validate and compare the algorithm both quantitatively and qualitatively. They show the advantages of our algorithm and its readily application to real world cases.

An application to model traffic intensity of agricultural machinery at field scale

NASA Astrophysics Data System (ADS)

Augustin, Katja; Kuhwald, Michael; Duttmann, Rainer

2017-04-01

Several soil-pressure-models deal with the impact of agricultural machines on soils. In many cases, these models were used for single spots and consider a static machine configuration. Therefore, a statement about the spatial distribution of soil compaction risk for entire working processes is limited. The aim of the study is the development of an application for the spatial modelling of traffic lanes from agricultural vehicles including wheel load, ground pressure and wheel passages at the field scale. The application is based on Open Source software, application and data formats, using python programming language. Minimum input parameters are GPS-positions, vehicles and tires (producer and model) and the tire inflation pressure. Five working processes were distinguished: soil tillage, manuring, plant protection, sowing and harvest. Currently, two different models (Diserens 2009, Rücknagel et al. 2015) were implemented to calculate the soil pressure. The application was tested at a study site in Lower Saxony, Germany. Since 2015, field traffic were recorded by RTK-GPS and used machine set ups were noted. Using these input information the traffic lanes, wheel load and soil pressure were calculated for all working processes. For instance, the maize harvest in 2016 with a crop chopper and one transport vehicle crossed about 55 % of the total field area. At some places the machines rolled over up to 46 times. Approximately 35 % of the total area was affected by wheel loads over 7 tons and soil pressures between 163 and 193 kPa. With the information about the spatial distribution of wheel passages, wheel load and soil pressure it is possible to identify hot spots of intensive field traffic. Additionally, the use of the application enables the analysis of soil compaction risk induced by agricultural machines for long- and short-term periods.

The role of edge-based and surface-based information in natural scene categorization: Evidence from behavior and event-related potentials.

PubMed

Fu, Qiufang; Liu, Yong-Jin; Dienes, Zoltan; Wu, Jianhui; Chen, Wenfeng; Fu, Xiaolan

2016-07-01

A fundamental question in vision research is whether visual recognition is determined by edge-based information (e.g., edge, line, and conjunction) or surface-based information (e.g., color, brightness, and texture). To investigate this question, we manipulated the stimulus onset asynchrony (SOA) between the scene and the mask in a backward masking task of natural scene categorization. The behavioral results showed that correct classification was higher for line-drawings than for color photographs when the SOA was 13ms, but lower when the SOA was longer. The ERP results revealed that most latencies of early components were shorter for the line-drawings than for the color photographs, and the latencies gradually increased with the SOA for the color photographs but not for the line-drawings. The results provide new evidence that edge-based information is the primary determinant of natural scene categorization, receiving priority processing; by contrast, surface information takes longer to facilitate natural scene categorization. Copyright © 2016 Elsevier Inc. All rights reserved.

Full velocity difference model for a car-following theory.

PubMed

Jiang, R; Wu, Q; Zhu, Z

2001-07-01

In this paper, we present a full velocity difference model for a car-following theory based on the previous models in the literature. To our knowledge, the model is an improvement over the previous ones theoretically, because it considers more aspects in car-following process than others. This point is verified by numerical simulation. Then we investigate the property of the model using both analytic and numerical methods, and find that the model can describe the phase transition of traffic flow and estimate the evolution of traffic congestion.

Proposal of a Roundabout Solution within a Particular Traflc Operation

NASA Astrophysics Data System (ADS)

Ližbetin, Ján; Stopka, Ondrej

2016-11-01

This paper presents the practical solution of the transport telematics elements within a particular traffic operation when providing a transport and logistics services. A roundabout helps to increase the fluency and safety of transport and logistics services in cities and urban areas, however, the positive effect can be achieved only after determining the proper intersection parameters. Based on a survey performed in a real traffic situation, the practical application of roundabout in the city of Pilsen is processed in the most important part of the paper.

Risk assessment on an Argentinean road with a dynamic traffic simulator

NASA Astrophysics Data System (ADS)

Voumard, Jérémie; Baumann, Valérie; Jaboyedoff, Michel; Derron, Marc-Henri; Penna, Ivanna

2014-05-01

The National Route 7 in Argentina is one of the most important corridors crossing the Andean Cordillera. It concentrates most of the traffic related to the Southern Common Market (MERCOSUR), it also connects Mendoza city (the fourth most populated in Argentina) with Santiago de Chile (the Chile capital city), and is used by tourists to access to the Aconcagua National park, Puente del Inca natural monument, skiing resorts, and to local displacements for the villages along the Mendoza valley. The road crosses the Andes through the Mendoza river valley at an elevation between 2'000 and 3'000 m. The traffic (2500 vehicles/day) is composed of motorcycles, cars and pickup trucks, trucks without trailer, buses, and semi-trailer trucks. Debris flows developed along tributaries of the Mendoza River, and due to remobilization of talus materials, impact frequently the road, causing traffic disruptions, bridges damages, etc. Rock falls detached from highly fractured outcrops also impact frequently the road, causing sometimes casualties. The aim of this study is to evaluate risk along sections of the National Road 7 develop along the Mendoza river, using a dynamic traffic simulator based on MATLAB© routine. The dynamic traffic simulator developed for natural hazards events on roads consider different scenarios based on traffic speeds, vehicle types, interactions types, road properties and natural processes. Here we show that vehicle types and traffic variations may influence the risk estimation. The analyzed risk on several critical sections of the National Route 7 demonstrates that risk may significantly increase: 1) on sinuous sections, steep sections and because of road conditions changes (exit of tunnel, bridges, road width, etc.) because of decreasing vehicle speed, particularly with semi-trailer trucks; 2) when an event, such a debris flow, occurs and generates a vehicle tailback increasing their duration presence in the risk area.

Geographic Information System (GIS) capabilities in traffic accident information management: a qualitative approach.

PubMed

Ahmadi, Maryam; Valinejadi, Ali; Goodarzi, Afshin; Safari, Ameneh; Hemmat, Morteza; Majdabadi, Hesamedin Askari; Mohammadi, Ali

2017-06-01

Traffic accidents are one of the more important national and international issues, and their consequences are important for the political, economical, and social level in a country. Management of traffic accident information requires information systems with analytical and accessibility capabilities to spatial and descriptive data. The aim of this study was to determine the capabilities of a Geographic Information System (GIS) in management of traffic accident information. This qualitative cross-sectional study was performed in 2016. In the first step, GIS capabilities were identified via literature retrieved from the Internet and based on the included criteria. Review of the literature was performed until data saturation was reached; a form was used to extract the capabilities. In the second step, study population were hospital managers, police, emergency, statisticians, and IT experts in trauma, emergency and police centers. Sampling was purposive. Data was collected using a questionnaire based on the first step data; validity and reliability were determined by content validity and Cronbach's alpha of 75%. Data was analyzed using the decision Delphi technique. GIS capabilities were identified in ten categories and 64 sub-categories. Import and process of spatial and descriptive data and so, analysis of this data were the most important capabilities of GIS in traffic accident information management. Storing and retrieving of descriptive and spatial data, providing statistical analysis in table, chart and zoning format, management of bad structure issues, determining the cost effectiveness of the decisions and prioritizing their implementation were the most important capabilities of GIS which can be efficient in the management of traffic accident information.

14 CFR 91.139 - Emergency air traffic rules.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 2 2014-01-01 2014-01-01 false Emergency air traffic rules. 91.139 Section...) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Flight Rules General § 91.139 Emergency air traffic rules. (a) This section prescribes a process for utilizing Notices to Airmen...

14 CFR 91.139 - Emergency air traffic rules.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 2 2012-01-01 2012-01-01 false Emergency air traffic rules. 91.139 Section...) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Flight Rules General § 91.139 Emergency air traffic rules. (a) This section prescribes a process for utilizing Notices to Airmen...

14 CFR 91.139 - Emergency air traffic rules.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 2 2010-01-01 2010-01-01 false Emergency air traffic rules. 91.139 Section...) AIR TRAFFIC AND GENERAL OPERATING RULES GENERAL OPERATING AND FLIGHT RULES Flight Rules General § 91.139 Emergency air traffic rules. (a) This section prescribes a process for utilizing Notices to Airmen...

Managed traffic evacuation using distributed sensor processing

NASA Astrophysics Data System (ADS)

Ramuhalli, Pradeep; Biswas, Subir

2005-05-01

This paper presents an integrated sensor network and distributed event processing architecture for managed in-building traffic evacuation during natural and human-caused disasters, including earthquakes, fire and biological/chemical terrorist attacks. The proposed wireless sensor network protocols and distributed event processing mechanisms offer a new distributed paradigm for improving reliability in building evacuation and disaster management. The networking component of the system is constructed using distributed wireless sensors for measuring environmental parameters such as temperature, humidity, and detecting unusual events such as smoke, structural failures, vibration, biological/chemical or nuclear agents. Distributed event processing algorithms will be executed by these sensor nodes to detect the propagation pattern of the disaster and to measure the concentration and activity of human traffic in different parts of the building. Based on this information, dynamic evacuation decisions are taken for maximizing the evacuation speed and minimizing unwanted incidents such as human exposure to harmful agents and stampedes near exits. A set of audio-visual indicators and actuators are used for aiding the automated evacuation process. In this paper we develop integrated protocols, algorithms and their simulation models for the proposed sensor networking and the distributed event processing framework. Also, efficient harnessing of the individually low, but collectively massive, processing abilities of the sensor nodes is a powerful concept behind our proposed distributed event processing algorithms. Results obtained through simulation in this paper are used for a detailed characterization of the proposed evacuation management system and its associated algorithmic components.

Large-scale transportation network congestion evolution prediction using deep learning theory.

PubMed

Ma, Xiaolei; Yu, Haiyang; Wang, Yunpeng; Wang, Yinhai

2015-01-01

Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS) and Internet of Things (IoT), transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS) data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU)-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation.

Large-Scale Transportation Network Congestion Evolution Prediction Using Deep Learning Theory

PubMed Central

Ma, Xiaolei; Yu, Haiyang; Wang, Yunpeng; Wang, Yinhai

2015-01-01

Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS) and Internet of Things (IoT), transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS) data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU)-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation. PMID:25780910

Silicon K-edge XANES spectra of silicate minerals

NASA Astrophysics Data System (ADS)

Li, Dien; Bancroft, G. M.; Fleet, M. E.; Feng, X. H.

1995-03-01

Silicon K-edge x-ray absorption near-edge structure (XANES) spectra of a selection of silicate and aluminosilicate minerals have been measured using synchrotron radiation (SR). The spectra are qualitatively interpreted based on MO calculation of the tetrahedral SiO{4/4-}cluster. The Si K-edge generally shifts to higher energy with increased polymerization of silicates by about 1.3 eV, but with considerable overlap for silicates of different polymerization types. The substitution of Al for Si shifts the Si K-edge to lower energy. The chemical shift of Si K-edge is also sensitive to cations in more distant atom shells; for example, the Si K-edge shifts to lower energy with the substitution of Al for Mg in octahedral sites. The shifts of the Si K-edge show weak correlation with average Si-O bond distance (dSi-O), Si-O bond valence (sSi-O) and distortion of SiO4 tetrahedra, due to the crystal structure complexity of silicate minerals and multiple factors effecting the x-ray absorption processes.

Infrared traffic image enhancement algorithm based on dark channel prior and gamma correction

NASA Astrophysics Data System (ADS)

Zheng, Lintao; Shi, Hengliang; Gu, Ming

2017-07-01

The infrared traffic image acquired by the intelligent traffic surveillance equipment has low contrast, little hierarchical differences in perceptions of image and the blurred vision effect. Therefore, infrared traffic image enhancement, being an indispensable key step, is applied to nearly all infrared imaging based traffic engineering applications. In this paper, we propose an infrared traffic image enhancement algorithm that is based on dark channel prior and gamma correction. In existing research dark channel prior, known as a famous image dehazing method, here is used to do infrared image enhancement for the first time. Initially, in the proposed algorithm, the original degraded infrared traffic image is transformed with dark channel prior as the initial enhanced result. A further adjustment based on the gamma curve is needed because initial enhanced result has lower brightness. Comprehensive validation experiments reveal that the proposed algorithm outperforms the current state-of-the-art algorithms.

Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks

PubMed Central

Artuñedo, Antonio; del Toro, Raúl M.; Haber, Rodolfo E.

2017-01-01

Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller (TLC) network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks. PMID:28445398

Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks.

PubMed

Artuñedo, Antonio; Del Toro, Raúl M; Haber, Rodolfo E

2017-04-26

Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller ( TLC ) network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks.

Path-preference cellular-automaton model for traffic flow through transit points and its application to the transcription process in human cells.

PubMed

Ohta, Yoshihiro; Nishiyama, Akinobu; Wada, Yoichiro; Ruan, Yijun; Kodama, Tatsuhiko; Tsuboi, Takashi; Tokihiro, Tetsuji; Ihara, Sigeo

2012-08-01

We all use path routing everyday as we take shortcuts to avoid traffic jams, or by using faster traffic means. Previous models of traffic flow of RNA polymerase II (RNAPII) during transcription, however, were restricted to one dimension along the DNA template. Here we report the modeling and application of traffic flow in transcription that allows preferential paths of different dimensions only restricted to visit some transit points, as previously introduced between the 5' and 3' end of the gene. According to its position, an RNAPII protein molecule prefers paths obeying two types of time-evolution rules. One is an asymmetric simple exclusion process (ASEP) along DNA, and the other is a three-dimensional jump between transit points in DNA where RNAPIIs are staying. Simulations based on our model, and comparison experimental results, reveal how RNAPII molecules are distributed at the DNA-loop-formation-related protein binding sites as well as CTCF insulator proteins (or exons). As time passes after the stimulation, the RNAPII density at these sites becomes higher. Apparent far-distance jumps in one dimension are realized by short-range three-dimensional jumps between DNA loops. We confirm the above conjecture by applying our model calculation to the SAMD4A gene by comparing the experimental results. Our probabilistic model provides possible scenarios for assembling RNAPII molecules into transcription factories, where RNAPII and related proteins cooperatively transcribe DNA.

Direct Detection Doppler Lidar for Spaceborne Wind Measurement

NASA Technical Reports Server (NTRS)

Korb, C. Laurence; Flesia, Cristina

1999-01-01

Aerosol and molecular based versions of the double-edge technique can be used for direct detection Doppler lidar spaceborne wind measurement. The edge technique utilizes the edge of a high spectral resolution filter for high accuracy wind measurement using direct detection lidar. The signal is split between an edge filter channel and a broadband energy monitor channel. The energy monitor channel is used for signal normalization. The edge measurement is made as a differential frequency measurement between the outgoing laser signal and the atmospheric backscattered return for each pulse. As a result the measurement is insensitive to laser and edge filter frequency jitter and drift at a level less than a few parts in 10(exp 10). We have developed double edge versions of the edge technique for aerosol and molecular-based lidar measurement of the wind. Aerosol-based wind measurements have been made at Goddard Space Flight Center and molecular-based wind measurements at the University of Geneva. We have demonstrated atmospheric measurements using these techniques for altitudes from 1 to more than 10 km. Measurement accuracies of better than 1.25 m/s have been obtained with integration times from 5 to 30 seconds. The measurements can be scaled to space and agree, within a factor of two, with satellite-based simulations of performance based on Poisson statistics. The theory of the double edge aerosol technique is described by a generalized formulation which substantially extends the capabilities of the edge technique. It uses two edges with opposite slopes located about the laser frequency at approximately the half-width of each edge filter. This doubles the signal change for a given Doppler shift and yields a factor of 1.6 improvement in the measurement accuracy compared to the single edge technique. The use of two high resolution edge filters substantially reduces the effects of Rayleigh scattering on the measurement, as much as order of magnitude, and allows the signal to noise ratio to be substantially improved in areas of low aerosol backscatter. We describe a method that allows the Rayleigh and aerosol components of the signal to be independently determined using the two edge channels and an energy monitor channel. The effects of Rayleigh scattering may then subtracted from the measurement and we show that the correction process does not significantly increase the measurement noise for Rayleigh to aerosol ratios up to 10. We show that for small Doppler shifts a measurement accuracy of 0.4 m/s can be obtained for 5000 detected photon, 1.2 m/s for 1000 detected photons, and 3.7 m/s for 50 detected photons for a Rayleigh to aerosol ratio of 5. Methods for increasing the dynamic range of the aerosol-based system to more than +/- 100 m/s are given.

FAST-TRAC evaluation : evaluation summary report

DOT National Transportation Integrated Search

FAST-TRAC is an Intelligent Transportation System (ITS) that integrates advanced traffic control with a variety of advanced traffic information systems through centralized collection, processing, and dissemination of traffic data. The Road Commission...

ESnet: Large-Scale Science and Data Management ( (LBNL Summer Lecture Series)

ScienceCinema

Johnston, Bill

2017-12-09

Summer Lecture Series 2004: Bill Johnston of Berkeley Lab's Computing Sciences is a distinguished networking and computing researcher. He managed the Energy Sciences Network (ESnet), a leading-edge, high-bandwidth network funded by DOE's Office of Science. Used for everything from videoconferencing to climate modeling, and flexible enough to accommodate a wide variety of data-intensive applications and services, ESNet's traffic volume is doubling every year and currently surpasses 200 terabytes per month.

An improved car-following model from the perspective of driver’s forecast behavior

NASA Astrophysics Data System (ADS)

Liu, Da-Wei; Shi, Zhong-Ke; Ai, Wen-Huan

In this paper, a new car-following model considering effect of the driver’s forecast behavior is proposed based on the full velocity difference model (FVDM). Using the new model, we investigate the starting process of the vehicle motion under a traffic signal and find that the delay time of vehicle motion is reduced. Then the stability condition of the new model is derived and the modified Korteweg-de Vries (mKdV) equation is constructed to describe the traffic behavior near the critical point. Numerical simulation is compatible with the analysis of theory such as density wave, hysteresis loop, which shows that the new model is reasonable. The results show that considering the effect of driver’s forecast behavior can help to enhance the stability of traffic flow.

Comparison between genetic algorithm and self organizing map to detect botnet network traffic

NASA Astrophysics Data System (ADS)

Yugandhara Prabhakar, Shinde; Parganiha, Pratishtha; Madhu Viswanatham, V.; Nirmala, M.

2017-11-01

In Cyber Security world the botnet attacks are increasing. To detect botnet is a challenging task. Botnet is a group of computers connected in a coordinated fashion to do malicious activities. Many techniques have been developed and used to detect and prevent botnet traffic and the attacks. In this paper, a comparative study is done on Genetic Algorithm (GA) and Self Organizing Map (SOM) to detect the botnet network traffic. Both are soft computing techniques and used in this paper as data analytics system. GA is based on natural evolution process and SOM is an Artificial Neural Network type, uses unsupervised learning techniques. SOM uses neurons and classifies the data according to the neurons. Sample of KDD99 dataset is used as input to GA and SOM.

Space evolution model and empirical analysis of an urban public transport network

NASA Astrophysics Data System (ADS)

Sui, Yi; Shao, Feng-jing; Sun, Ren-cheng; Li, Shu-jing

2012-07-01

This study explores the space evolution of an urban public transport network, using empirical evidence and a simulation model validated on that data. Public transport patterns primarily depend on traffic spatial-distribution, demands of passengers and expected utility of investors. Evolution is an iterative process of satisfying the needs of passengers and investors based on a given traffic spatial-distribution. The temporal change of urban public transport network is evaluated both using topological measures and spatial ones. The simulation model is validated using empirical data from nine big cities in China. Statistical analyses on topological and spatial attributes suggest that an evolution network with traffic demands characterized by power-law numerical values which distribute in a mode of concentric circles tallies well with these nine cities.

D-MSR: a distributed network management scheme for real-time monitoring and process control applications in wireless industrial automation.

PubMed

Zand, Pouria; Dilo, Arta; Havinga, Paul

2013-06-27

Current wireless technologies for industrial applications, such as WirelessHART and ISA100.11a, use a centralized management approach where a central network manager handles the requirements of the static network. However, such a centralized approach has several drawbacks. For example, it cannot cope with dynamicity/disturbance in large-scale networks in a real-time manner and it incurs a high communication overhead and latency for exchanging management traffic. In this paper, we therefore propose a distributed network management scheme, D-MSR. It enables the network devices to join the network, schedule their communications, establish end-to-end connections by reserving the communication resources for addressing real-time requirements, and cope with network dynamicity (e.g., node/edge failures) in a distributed manner. According to our knowledge, this is the first distributed management scheme based on IEEE 802.15.4e standard, which guides the nodes in different phases from joining until publishing their sensor data in the network. We demonstrate via simulation that D-MSR can address real-time and reliable communication as well as the high throughput requirements of industrial automation wireless networks, while also achieving higher efficiency in network management than WirelessHART, in terms of delay and overhead.

D-MSR: A Distributed Network Management Scheme for Real-Time Monitoring and Process Control Applications in Wireless Industrial Automation

PubMed Central

Zand, Pouria; Dilo, Arta; Havinga, Paul

2013-01-01

Current wireless technologies for industrial applications, such as WirelessHART and ISA100.11a, use a centralized management approach where a central network manager handles the requirements of the static network. However, such a centralized approach has several drawbacks. For example, it cannot cope with dynamicity/disturbance in large-scale networks in a real-time manner and it incurs a high communication overhead and latency for exchanging management traffic. In this paper, we therefore propose a distributed network management scheme, D-MSR. It enables the network devices to join the network, schedule their communications, establish end-to-end connections by reserving the communication resources for addressing real-time requirements, and cope with network dynamicity (e.g., node/edge failures) in a distributed manner. According to our knowledge, this is the first distributed management scheme based on IEEE 802.15.4e standard, which guides the nodes in different phases from joining until publishing their sensor data in the network. We demonstrate via simulation that D-MSR can address real-time and reliable communication as well as the high throughput requirements of industrial automation wireless networks, while also achieving higher efficiency in network management than WirelessHART, in terms of delay and overhead. PMID:23807687

City traffic flow breakdown prediction based on fuzzy rough set

NASA Astrophysics Data System (ADS)

Yang, Xu; Da-wei, Hu; Bing, Su; Duo-jia, Zhang

2017-05-01

In city traffic management, traffic breakdown is a very important issue, which is defined as a speed drop of a certain amount within a dense traffic situation. In order to predict city traffic flow breakdown accurately, in this paper, we propose a novel city traffic flow breakdown prediction algorithm based on fuzzy rough set. Firstly, we illustrate the city traffic flow breakdown problem, in which three definitions are given, that is, 1) Pre-breakdown flow rate, 2) Rate, density, and speed of the traffic flow breakdown, and 3) Duration of the traffic flow breakdown. Moreover, we define a hazard function to represent the probability of the breakdown ending at a given time point. Secondly, as there are many redundant and irrelevant attributes in city flow breakdown prediction, we propose an attribute reduction algorithm using the fuzzy rough set. Thirdly, we discuss how to predict the city traffic flow breakdown based on attribute reduction and SVM classifier. Finally, experiments are conducted by collecting data from I-405 Freeway, which is located at Irvine, California. Experimental results demonstrate that the proposed algorithm is able to achieve lower average error rate of city traffic flow breakdown prediction.

Quantum Efficiency Loss after PID Stress: Wavelength Dependence on Cell Surface and Cell Edge

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

Oh, Jaewon; Bowden, Stuart; TamizhMani, GovindaSamy

2015-06-14

It is known that the potential induced degradation (PID) stress of conventional p-base solar cells affects power, shunt resistance, junction recombination, and quantum efficiency (QE). One of the primary solutions to address the PID issue is a modification of chemical and physical properties of antireflection coating (ARC) on the cell surface. Depending on the edge isolation method used during cell processing, the ARC layer near the edges may be uniformly or non-uniformly damaged. Therefore, the pathway for sodium migration from glass to the cell junction could be either through all of the ARC surface if surface and edge ARC havemore » low quality or through the cell edge if surface ARC has high quality but edge ARC is defective due to certain edge isolation process. In this study, two PID susceptible cells from two different manufacturers have been investigated. The QE measurements of these cells before and after PID stress were performed at both surface and edge. We observed the wavelength dependent QE loss only in the first manufacturer's cell but not in the second manufacturer's cell. The first manufacturer's cell appeared to have low quality ARC whereas the second manufacturer's cell appeared to have high quality ARC with defective edge. To rapidly screen a large number of cells for PID stress testing, a new but simple test setup that does not require laminated cell coupon has been developed and is used in this investigation.« less

Visual information processing II; Proceedings of the Meeting, Orlando, FL, Apr. 14-16, 1993

NASA Technical Reports Server (NTRS)

Huck, Friedrich O. (Editor); Juday, Richard D. (Editor)

1993-01-01

Various papers on visual information processing are presented. Individual topics addressed include: aliasing as noise, satellite image processing using a hammering neural network, edge-detetion method using visual perception, adaptive vector median filters, design of a reading test for low-vision image warping, spatial transformation architectures, automatic image-enhancement method, redundancy reduction in image coding, lossless gray-scale image compression by predictive GDF, information efficiency in visual communication, optimizing JPEG quantization matrices for different applications, use of forward error correction to maintain image fidelity, effect of peanoscanning on image compression. Also discussed are: computer vision for autonomous robotics in space, optical processor for zero-crossing edge detection, fractal-based image edge detection, simulation of the neon spreading effect by bandpass filtering, wavelet transform (WT) on parallel SIMD architectures, nonseparable 2D wavelet image representation, adaptive image halftoning based on WT, wavelet analysis of global warming, use of the WT for signal detection, perfect reconstruction two-channel rational filter banks, N-wavelet coding for pattern classification, simulation of image of natural objects, number-theoretic coding for iconic systems.

Visual enhancement of unmixed multispectral imagery using adaptive smoothing

USGS Publications Warehouse

Lemeshewsky, G.P.; Rahman, Z.-U.; Schowengerdt, R.A.; Reichenbach, S.E.

2004-01-01

Adaptive smoothing (AS) has been previously proposed as a method to smooth uniform regions of an image, retain contrast edges, and enhance edge boundaries. The method is an implementation of the anisotropic diffusion process which results in a gray scale image. This paper discusses modifications to the AS method for application to multi-band data which results in a color segmented image. The process was used to visually enhance the three most distinct abundance fraction images produced by the Lagrange constraint neural network learning-based unmixing of Landsat 7 Enhanced Thematic Mapper Plus multispectral sensor data. A mutual information-based method was applied to select the three most distinct fraction images for subsequent visualization as a red, green, and blue composite. A reported image restoration technique (partial restoration) was applied to the multispectral data to reduce unmixing error, although evaluation of the performance of this technique was beyond the scope of this paper. The modified smoothing process resulted in a color segmented image with homogeneous regions separated by sharpened, coregistered multiband edges. There was improved class separation with the segmented image, which has importance to subsequent operations involving data classification.

Autonomous Flight Rules - A Concept for Self-Separation in U.S. Domestic Airspace

NASA Technical Reports Server (NTRS)

Wing, David J.; Cotton, William B.

2011-01-01

Autonomous Flight Rules (AFR) are proposed as a new set of operating regulations in which aircraft navigate on tracks of their choice while self-separating from traffic and weather. AFR would exist alongside Instrument and Visual Flight Rules (IFR and VFR) as one of three available flight options for any appropriately trained and qualified operator with the necessary certified equipment. Historically, ground-based separation services evolved by necessity as aircraft began operating in the clouds and were unable to see each other. Today, technologies for global navigation, airborne surveillance, and onboard computing enable the functions of traffic conflict management to be fully integrated with navigation procedures onboard the aircraft. By self-separating, aircraft can operate with more flexibility and fewer restrictions than are required when using ground-based separation. The AFR concept is described in detail and provides practical means by which self-separating aircraft could share the same airspace as IFR and VFR aircraft without disrupting the ongoing processes of Air Traffic Control.

Analysis of Air Traffic Track Data with the AutoBayes Synthesis System

NASA Technical Reports Server (NTRS)

Schumann, Johann Martin Philip; Cate, Karen; Lee, Alan G.

2010-01-01

The Next Generation Air Traffic System (NGATS) is aiming to provide substantial computer support for the air traffic controllers. Algorithms for the accurate prediction of aircraft movements are of central importance for such software systems but trajectory prediction has to work reliably in the presence of unknown parameters and uncertainties. We are using the AutoBayes program synthesis system to generate customized data analysis algorithms that process large sets of aircraft radar track data in order to estimate parameters and uncertainties. In this paper, we present, how the tasks of finding structure in track data, estimation of important parameters in climb trajectories, and the detection of continuous descent approaches can be accomplished with compact task-specific AutoBayes specifications. We present an overview of the AutoBayes architecture and describe, how its schema-based approach generates customized analysis algorithms, documented C/C++ code, and detailed mathematical derivations. Results of experiments with actual air traffic control data are discussed.

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.

A lightweight network anomaly detection technique

DOE PAGES

Kim, Jinoh; Yoo, Wucherl; Sim, Alex; ...

2017-03-13

While the network anomaly detection is essential in network operations and management, it becomes further challenging to perform the first line of detection against the exponentially increasing volume of network traffic. In this paper, we develop a technique for the first line of online anomaly detection with two important considerations: (i) availability of traffic attributes during the monitoring time, and (ii) computational scalability for streaming data. The presented learning technique is lightweight and highly scalable with the beauty of approximation based on the grid partitioning of the given dimensional space. With the public traffic traces of KDD Cup 1999 andmore » NSL-KDD, we show that our technique yields 98.5% and 83% of detection accuracy, respectively, only with a couple of readily available traffic attributes that can be obtained without the help of post-processing. Finally, the results are at least comparable with the classical learning methods including decision tree and random forest, with approximately two orders of magnitude faster learning performance.« less

A lightweight network anomaly detection technique

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

Kim, Jinoh; Yoo, Wucherl; Sim, Alex

While the network anomaly detection is essential in network operations and management, it becomes further challenging to perform the first line of detection against the exponentially increasing volume of network traffic. In this paper, we develop a technique for the first line of online anomaly detection with two important considerations: (i) availability of traffic attributes during the monitoring time, and (ii) computational scalability for streaming data. The presented learning technique is lightweight and highly scalable with the beauty of approximation based on the grid partitioning of the given dimensional space. With the public traffic traces of KDD Cup 1999 andmore » NSL-KDD, we show that our technique yields 98.5% and 83% of detection accuracy, respectively, only with a couple of readily available traffic attributes that can be obtained without the help of post-processing. Finally, the results are at least comparable with the classical learning methods including decision tree and random forest, with approximately two orders of magnitude faster learning performance.« less

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

FPGA-Based High-Performance Embedded Systems for Adaptive Edge Computing in Cyber-Physical Systems: The ARTICo³ Framework.

PubMed

Rodríguez, Alfonso; Valverde, Juan; Portilla, Jorge; Otero, Andrés; Riesgo, Teresa; de la Torre, Eduardo

2018-06-08

Cyber-Physical Systems are experiencing a paradigm shift in which processing has been relocated to the distributed sensing layer and is no longer performed in a centralized manner. This approach, usually referred to as Edge Computing, demands the use of hardware platforms that are able to manage the steadily increasing requirements in computing performance, while keeping energy efficiency and the adaptability imposed by the interaction with the physical world. In this context, SRAM-based FPGAs and their inherent run-time reconfigurability, when coupled with smart power management strategies, are a suitable solution. However, they usually fail in user accessibility and ease of development. In this paper, an integrated framework to develop FPGA-based high-performance embedded systems for Edge Computing in Cyber-Physical Systems is presented. This framework provides a hardware-based processing architecture, an automated toolchain, and a runtime to transparently generate and manage reconfigurable systems from high-level system descriptions without additional user intervention. Moreover, it provides users with support for dynamically adapting the available computing resources to switch the working point of the architecture in a solution space defined by computing performance, energy consumption and fault tolerance. Results show that it is indeed possible to explore this solution space at run time and prove that the proposed framework is a competitive alternative to software-based edge computing platforms, being able to provide not only faster solutions, but also higher energy efficiency for computing-intensive algorithms with significant levels of data-level parallelism.

7210.56 air traffic quality assurance

DOT National Transportation Integrated Search

1998-02-01

This order is the culmination of a long and thoughtful process involving the : active participation of nearly all elements of air traffic, including : headquarters, regional offices, facility managers, Air Traffic Supervisors : Committee (SUPCOM), Na...

Enabling User Preferences Through Data Exchange

DOT National Transportation Integrated Search

1997-08-01

This paper describes a process, via user- air traffic management (ATM) data : exchange, for enabling user preferences in an ATM-based system. User : preferences may be defined in terms of a four-dimensional (4D) user-preferred : trajectory, or a seri...

Use of Structure as a Basis for Abstraction in Air Traffic Control

NASA Technical Reports Server (NTRS)

Davison, Hayley J.; Hansman, R. John

2004-01-01

The safety and efficiency of the air traffic control domain is highly dependent on the capabilities and limitations of its human controllers. Past research has indicated that structure provided by the airspace and procedures could aid in simplifying the controllers cognitive tasks. In this paper, observations, interviews, voice command data analyses, and radar analyses were conducted at the Boston Terminal Route Control (TRACON) facility to determine if there was evidence of controllers using structure to simplify their cognitive processes. The data suggest that controllers do use structure-based abstractions to simplify their cognitive processes, particularly the projection task. How structure simplifies the projection task and the implications of understanding the benefits structure provides to the projection task was discussed.

Cumulus cloud base height estimation from high spatial resolution Landsat data - A Hough transform approach

NASA Technical Reports Server (NTRS)

Berendes, Todd; Sengupta, Sailes K.; Welch, Ron M.; Wielicki, Bruce A.; Navar, Murgesh

1992-01-01

A semiautomated methodology is developed for estimating cumulus cloud base heights on the basis of high spatial resolution Landsat MSS data, using various image-processing techniques to match cloud edges with their corresponding shadow edges. The cloud base height is then estimated by computing the separation distance between the corresponding generalized Hough transform reference points. The differences between the cloud base heights computed by these means and a manual verification technique are of the order of 100 m or less; accuracies of 50-70 m may soon be possible via EOS instruments.

Real-time video analysis for retail stores

NASA Astrophysics Data System (ADS)

Hassan, Ehtesham; Maurya, Avinash K.

2015-03-01

With the advancement in video processing technologies, we can capture subtle human responses in a retail store environment which play decisive role in the store management. In this paper, we present a novel surveillance video based analytic system for retail stores targeting localized and global traffic estimate. Development of an intelligent system for human traffic estimation in real-life poses a challenging problem because of the variation and noise involved. In this direction, we begin with a novel human tracking system by an intelligent combination of motion based and image level object detection. We demonstrate the initial evaluation of this approach on available standard dataset yielding promising result. Exact traffic estimate in a retail store require correct separation of customers from service providers. We present a role based human classification framework using Gaussian mixture model for this task. A novel feature descriptor named graded colour histogram is defined for object representation. Using, our role based human classification and tracking system, we have defined a novel computationally efficient framework for two types of analytics generation i.e., region specific people count and dwell-time estimation. This system has been extensively evaluated and tested on four hours of real-life video captured from a retail store.

A new kind of high durable traffic weighbridge based on FBG sensors

NASA Astrophysics Data System (ADS)

Zhou, Zhi; Liu, Jing; Li, Hui; Ou, Jinping

2005-05-01

Durability is the key problem of traditional traffic weighbridge based on electrical gauges. In this paper, a new kind of high durable traffic weighbridge based on FBG (Fiber Bragg Grating) sensors has been studied and developed. The principle of the smart FBG-weighbridge is based on that the traffic weight can be gotten from the deformation of the reinforced concrete beam with embedded FRP (Fiber Reinforced Polymer) - packaged FBG strain sensors. The FBG-based weighbridge is designed to be a reinforced concrete board supported by composite beams, and the truck load is shared by the composite beams. A 30-ton full scale FBG-based weighbridge has been set up, and the results from the tests and calibration analysis show that this kind of weighbridge features high durability, simplicity, convenience, low cost, etc. This new kind of FBG-based weighbridge shows good prospect in future to replace the traditional traffic weighbridge for long-term monitoring of traffic load.

A Fair Contention Access Scheme for Low-Priority Traffic in Wireless Body Area Networks

PubMed Central

Sajeel, Muhammad; Bashir, Faisal; Asfand-e-yar, Muhammad; Tauqir, Muhammad

2017-01-01

Recently, wireless body area networks (WBANs) have attracted significant consideration in ubiquitous healthcare. A number of medium access control (MAC) protocols, primarily derived from the superframe structure of the IEEE 802.15.4, have been proposed in literature. These MAC protocols aim to provide quality of service (QoS) by prioritizing different traffic types in WBANs. A contention access period (CAP)with high contention in priority-based MAC protocols can result in higher number of collisions and retransmissions. During CAP, traffic classes with higher priority are dominant over low-priority traffic; this has led to starvation of low-priority traffic, thus adversely affecting WBAN throughput, delay, and energy consumption. Hence, this paper proposes a traffic-adaptive priority-based superframe structure that is able to reduce contention in the CAP period, and provides a fair chance for low-priority traffic. Simulation results in ns-3 demonstrate that the proposed MAC protocol, called traffic- adaptive priority-based MAC (TAP-MAC), achieves low energy consumption, high throughput, and low latency compared to the IEEE 802.15.4 standard, and the most recent priority-based MAC protocol, called priority-based MAC protocol (PA-MAC). PMID:28832495

Active transportation to support diabetes prevention: Expanding school health promotion programming in an Indigenous community.

PubMed

Macridis, Soultana; Garcia Bengoechea, Enrique; McComber, Alex M; Jacobs, Judi; Macaulay, Ann C

2016-06-01

School-based physical activity (PA) interventions, including school active transportation (AT), provide opportunities to increase daily PA levels, improves fitness, and reduces risk of diseases, such as type 2 diabetes. Based on a community-identified need, the Kahnawake Schools Diabetes Prevention Project, within an Indigenous community, undertook school travel planning to contribute to PA programming for two elementary schools. Using community-based participatory research, the Active & Safe Routes to School's School Travel Planning (STP) process was undertaken in two schools with an STP-Committee comprised of community stakeholders and researchers. STP activities were adapted for local context including: school profile form, family survey, in-class travel survey, pedestrian-traffic observations, walkability checklist, and student mapping. STP data were jointly collected, analyzed and interpreted by researchers and community. Traffic-pedestrian observations, walkability and parent surveys identified key pedestrian-traffic locations, helped develop safe/direct routes, and traffic calming strategies. In-class travel and mapping surveys identified a need and student desire to increase school AT. The STP-Committee translated findings into STP-action plans for two schools, which were implemented in 2014-2015 school year. Combining CBPR with STP merges community and researcher expertise. This project offered evidence-informed practice for active living promotions. Experience and findings could benefit Indigenous and non-Indigenous communities. Copyright © 2016 Elsevier Ltd. All rights reserved.

Tailoring advanced technologies for air traffic control : the importance of the development process

DOT National Transportation Integrated Search

1995-04-01

This paper describes a process that is currently being applied to the : development and assessment of an advanced air traffic control (ATC) system, the : Center TRACON Automation System (CTAS). This process deviates from established : practices of AT...

Surveying traffic congestion based on the concept of community structure of complex networks

NASA Astrophysics Data System (ADS)

Ma, Lili; Zhang, Zhanli; Li, Meng

2016-07-01

In this paper, taking the traffic of Beijing city as an instance, we study city traffic states, especially traffic congestion, based on the concept of network community structure. Concretely, using the floating car data (FCD) information of vehicles gained from the intelligent transport system (ITS) of the city, we construct a new traffic network model which is with floating cars as network nodes and time-varying. It shows that this traffic network has Gaussian degree distributions at different time points. Furthermore, compared with free traffic situations, our simulations show that the traffic network generally has more obvious community structures with larger values of network fitness for congested traffic situations, and through the GPSspg web page, we show that all of our results are consistent with the reality. Then, it indicates that network community structure should be an available way for investigating city traffic congestion problems.

A Game-Theory Based Incentive Framework for an Intelligent Traffic System as Part of a Smart City Initiative.

PubMed

Mei, Haibo; Poslad, Stefan; Du, Shuang

2017-12-11

Intelligent Transportation Systems (ITSs) can be applied to inform and incentivize travellers to help them make cognizant choices concerning their trip routes and transport modality use for their daily travel whilst achieving more sustainable societal and transport authority goals. However, in practice, it is challenging for an ITS to enable incentive generation that is context-driven and personalized, whilst supporting multi-dimensional travel goals. This is because an ITS has to address the situation where different travellers have different travel preferences and constraints for route and modality, in the face of dynamically-varying traffic conditions. Furthermore, personalized incentive generation also needs to dynamically achieve different travel goals from multiple travellers, in the face of their conducts being a mix of both competitive and cooperative behaviours. To address this challenge, a Rule-based Incentive Framework (RIF) is proposed in this paper that utilizes both decision tree and evolutionary game theory to process travel information and intelligently generate personalized incentives for travellers. The travel information processed includes travellers' mobile patterns, travellers' modality preferences and route traffic volume information. A series of MATLAB simulations of RIF was undertaken to validate RIF to show that it is potentially an effective way to incentivize travellers to change travel routes and modalities as an essential smart city service.

Traffic offense sentencing processes and highway safety. Volume 1, Summary report

DOT National Transportation Integrated Search

1977-04-01

The history and development of traffic offense sanctions are reviewed. Criteria for traffic offense sanctions are discussed in terms of evenness, economy, appropriateness, rational allocation, effectiveness and parsimony. The framework for developmen...

Texas traffic thermostat software tool.

DOT National Transportation Integrated Search

2013-04-01

The traffic thermostat decision tool is built to help guide the user through a logical, step-wise, process of examining potential changes to their Manage Lane/toll facility. : **NOTE: Project Title: Application of the Traffic Thermostat Framework. Ap...

Texas traffic thermostat marketing package.

DOT National Transportation Integrated Search

2013-04-01

The traffic thermostat decision tool is built to help guide the user through a logical, step-wise, process of examining potential changes to their Manage Lane/toll facility. : **NOTE: Project Title: Application of the Traffic Thermostat Framework. Ap...

Supporting the Future Air Traffic Control Projection Process

NASA Technical Reports Server (NTRS)

Davison, Hayley J.; Hansman, R. John, Jr.

2002-01-01

In air traffic control, projecting what the air traffic situation will be over the next 30 seconds to 30 minutes is a key process in identifying conflicts that may arise so that evasive action can be taken upon discovery of these conflicts. A series of field visits in the Boston and New York terminal radar approach control (TRACON) facilities and in the oceanic air traffic control facilities in New York and Reykjavik, Iceland were conducted to investigate the projection process in two different ATC domains. The results from the site visits suggest that two types of projection are currently used in ATC tasks, depending on the type of separation minima and/or traffic restriction and information display used by the controller. As technologies improve and procedures change, care should be taken by designers to support projection through displays, automation, and procedures. It is critical to prevent time/space mismatches between interfaces and restrictions. Existing structure in traffic dynamics could be utilized to provide controllers with useful behavioral models on which to build projections. Subtle structure that the controllers are unable to internalize could be incorporated into an ATC projection aid.

A deblocking algorithm based on color psychology for display quality enhancement

NASA Astrophysics Data System (ADS)

Yeh, Chia-Hung; Tseng, Wen-Yu; Huang, Kai-Lin

2012-12-01

This article proposes a post-processing deblocking filter to reduce blocking effects. The proposed algorithm detects blocking effects by fusing the results of Sobel edge detector and wavelet-based edge detector. The filtering stage provides four filter modes to eliminate blocking effects at different color regions according to human color vision and color psychology analysis. Experimental results show that the proposed algorithm has better subjective and objective qualities for H.264/AVC reconstructed videos when compared to several existing methods.

Information theoretic analysis of canny edge detection in visual communication

NASA Astrophysics Data System (ADS)

Jiang, Bo; Rahman, Zia-ur

2011-06-01

In general edge detection evaluation, the edge detectors are examined, analyzed, and compared either visually or with a metric for specific an application. This analysis is usually independent of the characteristics of the image-gathering, transmission and display processes that do impact the quality of the acquired image and thus, the resulting edge image. We propose a new information theoretic analysis of edge detection that unites the different components of the visual communication channel and assesses edge detection algorithms in an integrated manner based on Shannon's information theory. The edge detection algorithm here is considered to achieve high performance only if the information rate from the scene to the edge approaches the maximum possible. Thus, by setting initial conditions of the visual communication system as constant, different edge detection algorithms could be evaluated. This analysis is normally limited to linear shift-invariant filters so in order to examine the Canny edge operator in our proposed system, we need to estimate its "power spectral density" (PSD). Since the Canny operator is non-linear and shift variant, we perform the estimation for a set of different system environment conditions using simulations. In our paper we will first introduce the PSD of the Canny operator for a range of system parameters. Then, using the estimated PSD, we will assess the Canny operator using information theoretic analysis. The information-theoretic metric is also used to compare the performance of the Canny operator with other edge-detection operators. This also provides a simple tool for selecting appropriate edgedetection algorithms based on system parameters, and for adjusting their parameters to maximize information throughput.

Contour sensitive saliency and depth application in image retargeting

NASA Astrophysics Data System (ADS)

Lu, Hongju; Yue, Pengfei; Zhao, Yanhui; Liu, Rui; Fu, Yuanbin; Zheng, Yuanjie; Cui, Jia

2018-04-01

Image retargeting technique requires important information preservation and less edge distortion during increasing/decreasing image size. The major existed content-aware methods perform well. However, there are two problems should be improved: the slight distortion appeared at the object edges and the structure distortion in the nonsalient area. According to psychological theories, people evaluate image quality based on multi-level judgments and comparison between different areas, both image content and image structure. The paper proposes a new standard: the structure preserving in non-salient area. After observation and image analysis, blur (slight blur) is generally existed at the edge of objects. The blur feature is used to estimate the depth cue, named blur depth descriptor. It can be used in the process of saliency computation for balanced image retargeting result. In order to keep the structure information in nonsalient area, the salient edge map is presented in Seam Carving process, instead of field-based saliency computation. The derivative saliency from x- and y-direction can avoid the redundant energy seam around salient objects causing structure distortion. After the comparison experiments between classical approaches and ours, the feasibility of our algorithm is proved.

Edge-Based Image Compression with Homogeneous Diffusion

NASA Astrophysics Data System (ADS)

Mainberger, Markus; Weickert, Joachim

It is well-known that edges contain semantically important image information. In this paper we present a lossy compression method for cartoon-like images that exploits information at image edges. These edges are extracted with the Marr-Hildreth operator followed by hysteresis thresholding. Their locations are stored in a lossless way using JBIG. Moreover, we encode the grey or colour values at both sides of each edge by applying quantisation, subsampling and PAQ coding. In the decoding step, information outside these encoded data is recovered by solving the Laplace equation, i.e. we inpaint with the steady state of a homogeneous diffusion process. Our experiments show that the suggested method outperforms the widely-used JPEG standard and can even beat the advanced JPEG2000 standard for cartoon-like images.

Determination of traffic intensity from camera images using image processing and pattern recognition techniques

NASA Astrophysics Data System (ADS)

Mehrübeoğlu, Mehrübe; McLauchlan, Lifford

2006-02-01

The goal of this project was to detect the intensity of traffic on a road at different times of the day during daytime. Although the work presented utilized images from a section of a highway, the results of this project are intended for making decisions on the type of intervention necessary on any given road at different times for traffic control, such as installation of traffic signals, duration of red, green and yellow lights at intersections, and assignment of traffic control officers near school zones or other relevant locations. In this project, directional patterns are used to detect and count the number of cars in traffic images over a fixed area of the road to determine local traffic intensity. Directional patterns are chosen because they are simple and common to almost all moving vehicles. Perspective vision effects specific to each camera orientation has to be considered, as they affect the size and direction of patterns to be recognized. In this work, a simple and fast algorithm has been developed based on horizontal directional pattern matching and perspective vision adjustment. The results of the algorithm under various conditions are presented and compared in this paper. Using the developed algorithm, the traffic intensity can accurately be determined on clear days with average sized cars. The accuracy is reduced on rainy days when the camera lens contains raindrops, when there are very long vehicles, such as trucks or tankers, in the view, and when there is very low light around dusk or dawn.

Negative differential resistance observation in complex convoluted fullerene junctions

NASA Astrophysics Data System (ADS)

Kaur, Milanpreet; Sawhney, Ravinder Singh; Engles, Derick

2018-04-01

In this work, we simulated the smallest fullerene molecule, C20 in a two-probe device model with gold electrodes. The gold electrodes comprised of (011) miller planes were carved to construct the novel geometry based four unique shapes, which were strung to fullerene molecules through mechanically controlled break junction techniques. The organized devices were later scrutinized using non-equilibrium Green's function based on the density functional theory to calculate their molecular orbitals, energy levels, charge transfers, and electrical parameters. After intense scrutiny, we concluded that five-edged and six-edged devices have the lowest and highest current-conductance values, which result from their electrode-dominating and electrode-subsidiary effects, respectively. However, an interesting observation was that the three-edged and four-edged electrodes functioned as semi-metallic in nature, allowing the C20 molecule to demonstrate its performance with the complementary effect of these electrodes in the electron conduction process of a two-probe device.

Monitoring Traffic Information with a Developed Acceleration Sensing Node.

PubMed

Ye, Zhoujing; Wang, Linbing; Xu, Wen; Gao, Zhifei; Yan, Guannan

2017-12-05

In this paper, an acceleration sensing node for pavement vibration was developed to monitor traffic information, including vehicle speed, vehicle types, and traffic flow, where a hardware design with low energy consumption and node encapsulation could be accomplished. The service performance of the sensing node was evaluated, by methods including waterproof test, compression test, sensing performance analysis, and comparison test. The results demonstrate that the sensing node is low in energy consumption, high in strength, IPX8 waterproof, and high in sensitivity and resolution. These characteristics can be applied to practical road environments. Two sensing nodes were spaced apart in the direction of travelling. In the experiment, three types of vehicles passed by the monitoring points at several different speeds and values of d (the distance between the sensor and the nearest tire center line). Based on cross-correlation with kernel pre-smoothing, a calculation method was applied to process the raw data. New algorithms for traffic flow, speed, and axle length were proposed. Finally, the effects of vehicle speed, vehicle weight, and d value on acceleration amplitude were statistically evaluated. It was found that the acceleration sensing node can be used for traffic flow, vehicle speed, and other types of monitoring.

Monitoring Traffic Information with a Developed Acceleration Sensing Node

PubMed Central

Ye, Zhoujing; Wang, Linbing; Xu, Wen; Gao, Zhifei; Yan, Guannan

2017-01-01

In this paper, an acceleration sensing node for pavement vibration was developed to monitor traffic information, including vehicle speed, vehicle types, and traffic flow, where a hardware design with low energy consumption and node encapsulation could be accomplished. The service performance of the sensing node was evaluated, by methods including waterproof test, compression test, sensing performance analysis, and comparison test. The results demonstrate that the sensing node is low in energy consumption, high in strength, IPX8 waterproof, and high in sensitivity and resolution. These characteristics can be applied to practical road environments. Two sensing nodes were spaced apart in the direction of travelling. In the experiment, three types of vehicles passed by the monitoring points at several different speeds and values of d (the distance between the sensor and the nearest tire center line). Based on cross-correlation with kernel pre-smoothing, a calculation method was applied to process the raw data. New algorithms for traffic flow, speed, and axle length were proposed. Finally, the effects of vehicle speed, vehicle weight, and d value on acceleration amplitude were statistically evaluated. It was found that the acceleration sensing node can be used for traffic flow, vehicle speed, and other types of monitoring. PMID:29206169

Dynamic Density: An Air Traffic Management Metric

NASA Technical Reports Server (NTRS)

Laudeman, I. V.; Shelden, S. G.; Branstrom, R.; Brasil, C. L.

1998-01-01

The definition of a metric of air traffic controller workload based on air traffic characteristics is essential to the development of both air traffic management automation and air traffic procedures. Dynamic density is a proposed concept for a metric that includes both traffic density (a count of aircraft in a volume of airspace) and traffic complexity (a measure of the complexity of the air traffic in a volume of airspace). It was hypothesized that a metric that includes terms that capture air traffic complexity will be a better measure of air traffic controller workload than current measures based only on traffic density. A weighted linear dynamic density function was developed and validated operationally. The proposed dynamic density function includes a traffic density term and eight traffic complexity terms. A unit-weighted dynamic density function was able to account for an average of 22% of the variance in observed controller activity not accounted for by traffic density alone. A comparative analysis of unit weights, subjective weights, and regression weights for the terms in the dynamic density equation was conducted. The best predictor of controller activity was the dynamic density equation with regression-weighted complexity terms.

Automatic airline baggage counting using 3D image segmentation

NASA Astrophysics Data System (ADS)

Yin, Deyu; Gao, Qingji; Luo, Qijun

2017-06-01

The baggage number needs to be checked automatically during baggage self-check-in. A fast airline baggage counting method is proposed in this paper using image segmentation based on height map which is projected by scanned baggage 3D point cloud. There is height drop in actual edge of baggage so that it can be detected by the edge detection operator. And then closed edge chains are formed from edge lines that is linked by morphological processing. Finally, the number of connected regions segmented by closed chains is taken as the baggage number. Multi-bag experiment that is performed on the condition of different placement modes proves the validity of the method.

Spatial Copula Model for Imputing Traffic Flow Data from Remote Microwave Sensors.

PubMed

Ma, Xiaolei; Luan, Sen; Du, Bowen; Yu, Bin

2017-09-21

Issues of missing data have become increasingly serious with the rapid increase in usage of traffic sensors. Analyses of the Beijing ring expressway have showed that up to 50% of microwave sensors pose missing values. The imputation of missing traffic data must be urgently solved although a precise solution that cannot be easily achieved due to the significant number of missing portions. In this study, copula-based models are proposed for the spatial interpolation of traffic flow from remote traffic microwave sensors. Most existing interpolation methods only rely on covariance functions to depict spatial correlation and are unsuitable for coping with anomalies due to Gaussian consumption. Copula theory overcomes this issue and provides a connection between the correlation function and the marginal distribution function of traffic flow. To validate copula-based models, a comparison with three kriging methods is conducted. Results indicate that copula-based models outperform kriging methods, especially on roads with irregular traffic patterns. Copula-based models demonstrate significant potential to impute missing data in large-scale transportation networks.

Patterning control strategies for minimum edge placement error in logic devices

NASA Astrophysics Data System (ADS)

Mulkens, Jan; Hanna, Michael; Slachter, Bram; Tel, Wim; Kubis, Michael; Maslow, Mark; Spence, Chris; Timoshkov, Vadim

2017-03-01

In this paper we discuss the edge placement error (EPE) for multi-patterning semiconductor manufacturing. In a multi-patterning scheme the creation of the final pattern is the result of a sequence of lithography and etching steps, and consequently the contour of the final pattern contains error sources of the different process steps. We describe the fidelity of the final pattern in terms of EPE, which is defined as the relative displacement of the edges of two features from their intended target position. We discuss our holistic patterning optimization approach to understand and minimize the EPE of the final pattern. As an experimental test vehicle we use the 7-nm logic device patterning process flow as developed by IMEC. This patterning process is based on Self-Aligned-Quadruple-Patterning (SAQP) using ArF lithography, combined with line cut exposures using EUV lithography. The computational metrology method to determine EPE is explained. It will be shown that ArF to EUV overlay, CDU from the individual process steps, and local CD and placement of the individual pattern features, are the important contributors. Based on the error budget, we developed an optimization strategy for each individual step and for the final pattern. Solutions include overlay and CD metrology based on angle resolved scatterometry, scanner actuator control to enable high order overlay corrections and computational lithography optimization to minimize imaging induced pattern placement errors of devices and metrology targets.

Concept for a Satellite-Based Advanced Air Traffic Management System : Volume 1. Summary.

DOT National Transportation Integrated Search

1974-02-01

The report contains the results of studies and analyses directed toward the definition of a Satellite-Based Advanced Air Traffic Management System (SAATMS). This system is an advanced, integrated air traffic control system which is based on the use o...

Line grouping using perceptual saliency and structure prediction for car detection in traffic scenes

NASA Astrophysics Data System (ADS)

Denasi, Sandra; Quaglia, Giorgio

1993-08-01

Autonomous and guide assisted vehicles make a heavy use of computer vision techniques to perceive the environment where they move. In this context, the European PROMETHEUS program is carrying on activities in order to develop autonomous vehicle monitoring that assists people to achieve safer driving. Car detection is one of the topics that are faced by the program. Our contribution proposes the development of this task in two stages: the localization of areas of interest and the formulation of object hypotheses. In particular, the present paper proposes a new approach that builds structural descriptions of objects from edge segmentations by using geometrical organization. This approach has been applied to the detection of cars in traffic scenes. We have analyzed images taken from a moving vehicle in order to formulate obstacle hypotheses: preliminary results confirm the efficiency of the method.

Analysis and Classification of Traffic in Wireless Sensor Network

DTIC Science & Technology

2007-03-01

34 1. Hurst Parameter ................................................................................35 2. Self-Similarity...traffic is self-similar, buffer size can be better designed from the forecasted traffic workload. 1. Hurst Parameter To determine the extent of self...similarity in WSN traffic, the Hurst parameter, H, is used. H also calculates the length of the long range dependence of a stochastic process. If H

Application of the user-centred design process according ISO 9241-210 in air traffic control.

PubMed

König, Christina; Hofmann, Thomas; Bruder, Ralph

2012-01-01

Designing a usable human machine interface for air traffic control is challenging and should follow approved methods. The ISO 9241-210 standard promises high usability of products by integrating future users and following an iterative process. This contribution describes the proceeding and first results of the analysis and application of ISO 9241-210 to develop a planning tool for air traffic controllers.

The research of edge extraction and target recognition based on inherent feature of objects

NASA Astrophysics Data System (ADS)

Xie, Yu-chan; Lin, Yu-chi; Huang, Yin-guo

2008-03-01

Current research on computer vision often needs specific techniques for particular problems. Little use has been made of high-level aspects of computer vision, such as three-dimensional (3D) object recognition, that are appropriate for large classes of problems and situations. In particular, high-level vision often focuses mainly on the extraction of symbolic descriptions, and pays little attention to the speed of processing. In order to extract and recognize target intelligently and rapidly, in this paper we developed a new 3D target recognition method based on inherent feature of objects in which cuboid was taken as model. On the basis of analysis cuboid nature contour and greyhound distributing characteristics, overall fuzzy evaluating technique was utilized to recognize and segment the target. Then Hough transform was used to extract and match model's main edges, we reconstruct aim edges by stereo technology in the end. There are three major contributions in this paper. Firstly, the corresponding relations between the parameters of cuboid model's straight edges lines in an image field and in the transform field were summed up. By those, the aimless computations and searches in Hough transform processing can be reduced greatly and the efficiency is improved. Secondly, as the priori knowledge about cuboids contour's geometry character known already, the intersections of the component extracted edges are taken, and assess the geometry of candidate edges matches based on the intersections, rather than the extracted edges. Therefore the outlines are enhanced and the noise is depressed. Finally, a 3-D target recognition method is proposed. Compared with other recognition methods, this new method has a quick response time and can be achieved with high-level computer vision. The method present here can be used widely in vision-guide techniques to strengthen its intelligence and generalization, which can also play an important role in object tracking, port AGV, robots fields. The results of simulation experiments and theory analyzing demonstrate that the proposed method could suppress noise effectively, extracted target edges robustly, and achieve the real time need. Theory analysis and experiment shows the method is reasonable and efficient.

Evaluation of the Monotonic Lagrangian Grid and Lat-Long Grid for Air Traffic Management

NASA Technical Reports Server (NTRS)

Kaplan, Carolyn; Dahm, Johann; Oran, Elaine; Alexandrov, Natalia; Boris, Jay

2011-01-01

The Air Traffic Monotonic Lagrangian Grid (ATMLG) is used to simulate a 24 hour period of air traffic flow in the National Airspace System (NAS). During this time period, there are 41,594 flights over the United States, and the flight plan information (departure and arrival airports and times, and waypoints along the way) are obtained from an Federal Aviation Administration (FAA) Enhanced Traffic Management System (ETMS) dataset. Two simulation procedures are tested and compared: one based on the Monotonic Lagrangian Grid (MLG), and the other based on the stationary Latitude-Longitude (Lat- Long) grid. Simulating one full day of air traffic over the United States required the following amounts of CPU time on a single processor of an SGI Altix: 88 s for the MLG method, and 163 s for the Lat-Long grid method. We present a discussion of the amount of CPU time required for each of the simulation processes (updating aircraft trajectories, sorting, conflict detection and resolution, etc.), and show that the main advantage of the MLG method is that it is a general sorting algorithm that can sort on multiple properties. We discuss how many MLG neighbors must be considered in the separation assurance procedure in order to ensure a five-mile separation buffer between aircraft, and we investigate the effect of removing waypoints from aircraft trajectories. When aircraft choose their own trajectory, there are more flights with shorter duration times and fewer CD&R maneuvers, resulting in significant fuel savings.

Vision-based weld pool boundary extraction and width measurement during keyhole fiber laser welding

NASA Astrophysics Data System (ADS)

Luo, Masiyang; Shin, Yung C.

2015-01-01

In keyhole fiber laser welding processes, the weld pool behavior is essential to determining welding quality. To better observe and control the welding process, the accurate extraction of the weld pool boundary as well as the width is required. This work presents a weld pool edge detection technique based on an off axial green illumination laser and a coaxial image capturing system that consists of a CMOS camera and optic filters. According to the difference of image quality, a complete developed edge detection algorithm is proposed based on the local maximum gradient of greyness searching approach and linear interpolation. The extracted weld pool geometry and the width are validated by the actual welding width measurement and predictions by a numerical multi-phase model.

Coordinated traffic incident management using the I-Net embedded sensor architecture

NASA Astrophysics Data System (ADS)

Dudziak, Martin J.

1999-01-01

The I-Net intelligent embedded sensor architecture enables the reconfigurable construction of wide-area remote sensing and data collection networks employing diverse processing and data acquisition modules communicating over thin- server/thin-client protocols. Adaptive initially for operation using mobile remotely-piloted vehicle platforms such as small helicopter robots such as the Hornet and Ascend-I, the I-Net architecture lends itself to a critical problem in the management of both spontaneous and planned traffic congestion and rerouting over major interstate thoroughfares such as the I-95 Corridor. Pre-programmed flight plans and ad hoc operator-assisted navigation of the lightweight helicopter, using an auto-pilot and gyroscopic stabilization augmentation units, allows daytime or nighttime over-the-horizon flights of the unit to collect and transmit real-time video imagery that may be stored or transmitted to other locations. With on-board GPS and ground-based pattern recognition capabilities to augment the standard video collection process, this approach enables traffic management and emergency response teams to plan and assist real-time in the adjustment of traffic flows in high- density or congested areas or during dangerous road conditions such as during ice, snow, and hurricane storms. The I-Net architecture allows for integration of land-based and roadside sensors within a comprehensive automated traffic management system with communications to and form an airborne or other platform to devices in the network other than human-operated desktop computers, thereby allowing more rapid assimilation and response for critical data. Experiments have been conducted using several modified platforms and standard video and still photographic equipment. Current research and development is focused upon modification of the modular instrumentation units in order to accommodate faster loading and reloading of equipment onto the RPV, extension of the I-Net architecture to enable RPV-to-RPV signaling and control, and refinement of safety and emergency mechanisms to handle RPV mechanical failure during flight.

Yield impact for wafer shape misregistration-based binning for overlay APC diagnostic enhancement

NASA Astrophysics Data System (ADS)

Jayez, David; Jock, Kevin; Zhou, Yue; Govindarajulu, Venugopal; Zhang, Zhen; Anis, Fatima; Tijiwa-Birk, Felipe; Agarwal, Shivam

2018-03-01

The importance of traditionally acceptable sources of variation has started to become more critical as semiconductor technologies continue to push into smaller technology nodes. New metrology techniques are needed to pursue the process uniformity requirements needed for controllable lithography. Process control for lithography has the advantage of being able to adjust for cross-wafer variability, but this requires that all processes are close in matching between process tools/chambers for each process. When this is not the case, the cumulative line variability creates identifiable groups of wafers1 . This cumulative shape based effect is described as impacting overlay measurements and alignment by creating misregistration of the overlay marks. It is necessary to understand what requirements might go into developing a high volume manufacturing approach which leverages this grouping methodology, the key inputs and outputs, and what can be extracted from such an approach. It will be shown that this line variability can be quantified into a loss of electrical yield primarily at the edge of the wafer and proposes a methodology for root cause identification and improvement. This paper will cover the concept of wafer shape based grouping as a diagnostic tool for overlay control and containment, the challenges in implementing this in a manufacturing setting, and the limitations of this approach. This will be accomplished by showing that there are identifiable wafer shape based signatures. These shape based wafer signatures will be shown to be correlated to overlay misregistration, primarily at the edge. It will also be shown that by adjusting for this wafer shape signal, improvements can be made to both overlay as well as electrical yield. These improvements show an increase in edge yield, and a reduction in yield variability.

NASA Ames and Future of Space Exploration, Science, and Aeronautics

NASA Technical Reports Server (NTRS)

Cohen, Jacob

2015-01-01

Pushing the frontiers of aeronautics and space exploration presents multiple challenges. NASA Ames Research Center is at the forefront of tackling these issues, conducting cutting edge research in the fields of air traffic management, entry systems, advanced information technology, intelligent human and robotic systems, astrobiology, aeronautics, space, earth and life sciences and small satellites. Knowledge gained from this research helps ensure the success of NASA's missions, leading us closer to a world that was only imagined as science fiction just decades ago.

Weighted networks as randomly reinforced urn processes

NASA Astrophysics Data System (ADS)

Caldarelli, Guido; Chessa, Alessandro; Crimaldi, Irene; Pammolli, Fabio

2013-02-01

We analyze weighted networks as randomly reinforced urn processes, in which the edge-total weights are determined by a reinforcement mechanism. We develop a statistical test and a procedure based on it to study the evolution of networks over time, detecting the “dominance” of some edges with respect to the others and then assessing if a given instance of the network is taken at its steady state or not. Distance from the steady state can be considered as a measure of the relevance of the observed properties of the network. Our results are quite general, in the sense that they are not based on a particular probability distribution or functional form of the random weights. Moreover, the proposed tool can be applied also to dense networks, which have received little attention by the network community so far, since they are often problematic. We apply our procedure in the context of the International Trade Network, determining a core of “dominant edges.”

Analysis of Child-related Road Traffic Accidents in Vietnam

NASA Astrophysics Data System (ADS)

Vu, Anh Tuan; Nguyen, Dinh Vinh Man

2018-04-01

In recent years, the number of road traffic accidents, fatalities and injuries have been decreasing, but the figures of children road traffic accidents have been increasing in Ho Chi Minh City of Vietnam. This fact strongly calls for implementing effective solutions to improve traffic safety for children by the local government. This paper presents the trends, patterns and causes of road traffic accidents involving children based on the analysis of road traffic accident data over the period 2010-2015 and the video-based observations of road traffic law violations at 15 typical school gates and 10 typical roads. The results could be useful for the city government to formulate solutions to effectively improve traffic safety for children in Ho Chi Minh City and other cities in Vietnam.

Geographic Information System (GIS) capabilities in traffic accident information management: a qualitative approach

PubMed Central

Ahmadi, Maryam; Valinejadi, Ali; Goodarzi, Afshin; Safari, Ameneh; Hemmat, Morteza; Majdabadi, Hesamedin Askari; Mohammadi, Ali

2017-01-01

Background Traffic accidents are one of the more important national and international issues, and their consequences are important for the political, economical, and social level in a country. Management of traffic accident information requires information systems with analytical and accessibility capabilities to spatial and descriptive data. Objective The aim of this study was to determine the capabilities of a Geographic Information System (GIS) in management of traffic accident information. Methods This qualitative cross-sectional study was performed in 2016. In the first step, GIS capabilities were identified via literature retrieved from the Internet and based on the included criteria. Review of the literature was performed until data saturation was reached; a form was used to extract the capabilities. In the second step, study population were hospital managers, police, emergency, statisticians, and IT experts in trauma, emergency and police centers. Sampling was purposive. Data was collected using a questionnaire based on the first step data; validity and reliability were determined by content validity and Cronbach’s alpha of 75%. Data was analyzed using the decision Delphi technique. Results GIS capabilities were identified in ten categories and 64 sub-categories. Import and process of spatial and descriptive data and so, analysis of this data were the most important capabilities of GIS in traffic accident information management. Conclusion Storing and retrieving of descriptive and spatial data, providing statistical analysis in table, chart and zoning format, management of bad structure issues, determining the cost effectiveness of the decisions and prioritizing their implementation were the most important capabilities of GIS which can be efficient in the management of traffic accident information. PMID:28848627

Incorporating ITS into transportation planning : phase 1 final report

DOT National Transportation Integrated Search

2000-04-01

Incident management is the process of managing multi-agency, multi-jurisdictional responses to highway traffic disruptions. Traffic incidents are a major cause of congestion on the nation?s highway network. More than half of all freeway traffic conge...

Traffic Surveillance Data Processing in Urban Freeway Corridors Using Kalman Filter Techniques

DOT National Transportation Integrated Search

1978-11-01

Real-time surveillance of traffic conditions on urban freeway corridors using spatially discrete presence detectors is addressed. Using a finite-dimensional (macroscopic) fluid-analog model for freeway vehicular traffic flow, an extended Kalman filte...

Right-\\0xADturn traffic volume adjustment in traffic signal warrant analysis : final report.

DOT National Transportation Integrated Search

2016-05-06

This report was based on the research project, Right-Turn Traffic Volume Adjustment in : Traffic Signal Warrants, sponsored by the Nevada Department of Transportation (NDOT) : and SOLARIS. Right-turn traffic does not affect intersection performance i...

Right-­turn traffic volume adjustment in traffic signal warrant analysis : final report.

DOT National Transportation Integrated Search

2016-05-06

This report was based on the research project, Right-Turn Traffic Volume Adjustment in Traffic Signal Warrants, sponsored by the Nevada Department of Transportation (NDOT) and SOLARIS. Right-turn traffic does not affect intersection performance in th...

LLSURE: local linear SURE-based edge-preserving image filtering.

PubMed

Qiu, Tianshuang; Wang, Aiqi; Yu, Nannan; Song, Aimin

2013-01-01

In this paper, we propose a novel approach for performing high-quality edge-preserving image filtering. Based on a local linear model and using the principle of Stein's unbiased risk estimate as an estimator for the mean squared error from the noisy image only, we derive a simple explicit image filter which can filter out noise while preserving edges and fine-scale details. Moreover, this filter has a fast and exact linear-time algorithm whose computational complexity is independent of the filtering kernel size; thus, it can be applied to real time image processing tasks. The experimental results demonstrate the effectiveness of the new filter for various computer vision applications, including noise reduction, detail smoothing and enhancement, high dynamic range compression, and flash/no-flash denoising.

Intelligent lightening system of urban and rural road traffic based on pyroelectric infrared detector

NASA Astrophysics Data System (ADS)

Miao, Man-Xiang

2007-12-01

By using the photo-voltage characteristics of pyroelectric infrared detector to fulfill signal acquisition, the detecting signal is processed with the core of a single chip microprocessor AT89C51. AT89C51 controls the CAN bus controller SJA1000/transceiver 82C250 to structure CAN bus communication system to transmit data through serial interface MAX232 connected with PC. The intelligent lightening system of urban and rural road traffic was carried out. In this paper, its construction and part's methods of hardware and software design were introduced in detail.

Research on moving target defense based on SDN

NASA Astrophysics Data System (ADS)

Chen, Mingyong; Wu, Weimin

2017-08-01

An address mutation strategy was proposed. This strategy provided an unpredictable change in address, replacing the real address of the packet forwarding process and path mutation, thus hiding the real address of the host and path. a mobile object defense technology based on Spatio-temporal Mutation on this basis is proposed, Using the software Defined Network centralized control architecture advantage combines sFlow traffic monitoring technology and Moving Target Defense. A mutated time period which can be changed in real time according to the network traffic is changed, and the destination address is changed while the controller abruptly changes the address while the data packet is transferred between the switches to construct a moving target, confusing the host within the network, thereby protecting the host and network.

Multispectral image sharpening using wavelet transform techniques and spatial correlation of edges

USGS Publications Warehouse

Lemeshewsky, George P.; Schowengerdt, Robert A.

2000-01-01

Several reported image fusion or sharpening techniques are based on the discrete wavelet transform (DWT). The technique described here uses a pixel-based maximum selection rule to combine respective transform coefficients of lower spatial resolution near-infrared (NIR) and higher spatial resolution panchromatic (pan) imagery to produce a sharpened NIR image. Sharpening assumes a radiometric correlation between the spectral band images. However, there can be poor correlation, including edge contrast reversals (e.g., at soil-vegetation boundaries), between the fused images and, consequently, degraded performance. To improve sharpening, a local area-based correlation technique originally reported for edge comparison with image pyramid fusion is modified for application with the DWT process. Further improvements are obtained by using redundant, shift-invariant implementation of the DWT. Example images demonstrate the improvements in NIR image sharpening with higher resolution pan imagery.

Activating without Inhibiting: Left-Edge Boundary Tones and Syntactic Processing

ERIC Educational Resources Information Center

Roll, Mikael; Horne, Merle; Lindgren, Magnus

2011-01-01

Right-edge boundary tones have earlier been found to restrict syntactic processing by closing a clause for further integration of incoming words. The role of left-edge intonation, however, has received little attention to date. We show that Swedish left-edge boundary tones selectively facilitate the on-line processing of main clauses, the…

Speech-based E-mail and driver behavior: effects of an in-vehicle message system interface.

PubMed

Jamson, A Hamish; Westerman, Stephen J; Hockey, G Robert J; Carsten, Oliver M J

2004-01-01

As mobile office technology becomes more advanced, drivers have increased opportunity to process information "on the move." Although speech-based interfaces can minimize direct interference with driving, the cognitive demands associated with such systems may still cause distraction. We studied the effects on driving performance of an in-vehicle simulated "E-mail" message system; E-mails were either system controlled or driver controlled. A high-fidelity, fixed-base driving simulator was used to test 19 participants on a car-following task. Virtual traffic scenarios varying in driving demand. Drivers compensated for the secondary task by adopting longer headways but showed reduced anticipation of braking requirements and shorter time to collision. Drivers were also less reactive when processing E-mails, demonstrated by a reduction in steering wheel inputs. In most circumstances, there were advantages in providing drivers with control over when E-mails were opened. However, during periods without E-mail interaction in demanding traffic scenarios, drivers showed reduced braking anticipation. This may be a result of increased cognitive costs associated with the decision making process when using a driver-controlled interface when the task of scheduling E-mail acceptance is added to those of driving and E-mail response. Actual or potential applications of this research include the design of speech-based in-vehicle messaging systems.

THE DETROIT ASTHMA MORBIDITY, AIR QUALITY AND TRAFFIC (DAMAT) STUDY

EPA Science Inventory

The project was completed successfully. In Project Year 1, the health outcome and exposure data sets were collected, cleaned and processed, including specifically:

• A set of daily exposure measures, based on measurements of the selected pollutants measure...

• Temperate forest fragments maintain aboveground carbon stocks out to the forest edge despite changes in community composition.

  PubMed

  Ziter, Carly; Bennett, Elena M; Gonzalez, Andrew

  2014-11-01

  Edge effects are among the primary mechanisms by which forest fragmentation can influence the link between biodiversity and ecosystem processes, but relatively few studies have quantified these mechanisms in temperate regions. Carbon storage is an important ecosystem function altered by edge effects, with implications for climate change mitigation. Two opposing hypotheses suggest that aboveground carbon (AGC) stocks at the forest edge will (a) decrease due to increased tree mortality and compositional shifts towards smaller, lower wood density species (e.g., as seen in tropical systems) or, less often, (b) increase due to light/temperature-induced increases in diversity and productivity. We used field-based measurements, allometry, and mixed models to investigate the effects of proximity to the forest edge on AGC stocks, species richness, and community composition in 24 forest fragments in southern Quebec. We also asked whether fragment size or connectivity with surrounding forests altered these edge effects. AGC stocks remained constant across a 100 m edge-to-interior gradient in all fragment types, despite changes in tree community composition and stem density consistent with expectations of forest edge effects. We attribute this constancy primarily to compensatory effects of small trees at the forest edge; however, it is due in some cases to the retention of large trees at forest edges, likely a result of forest management. Our results suggest important differences between temperate and tropical fragments with respect to mechanisms linking biodiversity and AGC dynamics. Small temperate forest fragments may be valuable in conservation efforts based on maintaining biodiversity and multiple ecosystem services.

• Forests on the edge: housing development on America’s private forests.

  Treesearch

  Ronald E. McRoberts; Ralph J. Alig; Mark D. Nelson; David M. Theobald; Mike Eley; Mike Dechter; Mary. Carr

  2005-01-01

  The private working land base of America’s forests is being converted to developed uses, with implications for the condition and management of affected private forests and the watersheds in which they occur. The Forests on the Edge project seeks to improve understanding of the processes and thresholds associated with increases in housing density in private forests and...

• Bag-of-visual-phrases and hierarchical deep models for traffic sign detection and recognition in mobile laser scanning data

  NASA Astrophysics Data System (ADS)

  Yu, Yongtao; Li, Jonathan; Wen, Chenglu; Guan, Haiyan; Luo, Huan; Wang, Cheng

  2016-03-01

  This paper presents a novel algorithm for detection and recognition of traffic signs in mobile laser scanning (MLS) data for intelligent transportation-related applications. The traffic sign detection task is accomplished based on 3-D point clouds by using bag-of-visual-phrases representations; whereas the recognition task is achieved based on 2-D images by using a Gaussian-Bernoulli deep Boltzmann machine-based hierarchical classifier. To exploit high-order feature encodings of feature regions, a deep Boltzmann machine-based feature encoder is constructed. For detecting traffic signs in 3-D point clouds, the proposed algorithm achieves an average recall, precision, quality, and F-score of 0.956, 0.946, 0.907, and 0.951, respectively, on the four selected MLS datasets. For on-image traffic sign recognition, a recognition accuracy of 97.54% is achieved by using the proposed hierarchical classifier. Comparative studies with the existing traffic sign detection and recognition methods demonstrate that our algorithm obtains promising, reliable, and high performance in both detecting traffic signs in 3-D point clouds and recognizing traffic signs on 2-D images.

• Increasing the default interletter spacing of words can help drivers to read traffic signs at longer distances.

  PubMed

  Tejero, Pilar; Insa, Beatriz; Roca, Javier

  2018-08-01

  Would an increase in the default interletter spacing improve the legibility of words in traffic signs? Previous evidence on traffic sign design and recent studies on the cognitive processes involved in visual word recognition have provided conflicting results. The present work examined whether an increase in the default interletter spacing would improve the search of a word in direction traffic signs. To achieve this objective, twenty-two drivers participated in a driving simulation experiment. They followed a highway route and indicated whether a target place name was present among a set of distractors shown on direction traffic signs along the route. We compared the default interletter spacing of the Spanish "CC Rige" font (which is based on the internationally-used Transport font) and a 2.5-times expanded interletter spacing. The results revealed that the drivers were able to give a correct response at a distance to the traffic sign that was on average longer in the expanded than in the default spacing condition. This advantage in the legibility distance was observed in the absence of significant differences in reading accuracy, gaze behavior, or driving performance measures. Therefore, the evidence provided supports that drivers can benefit from a slight increase in interletter spacing relative to the standard spacing. Some of the design factors influencing this effect are discussed. Copyright © 2018 Elsevier Ltd. All rights reserved.

• Gulf Coast megaregion evacuation traffic simulation modeling and analysis.

  DOT National Transportation Integrated Search

  2015-12-01

  This paper describes a project to develop a micro-level traffic simulation for a megaregion. To : accomplish this, a mass evacuation event was modeled using a traffic demand generation process that : created a spatial and temporal distribution of dep...

• Utilization of index stations for prediction of interstate traffic volumes.

  DOT National Transportation Integrated Search

  2006-10-01

  To facilitate the collection of traffic volumes along the Interstate System and better utilize the available resources. A method to factor adjacent traffic count locations from index counts collected on an annual basis has been proposed. This process...

• A learning-based autonomous driver: emulate human driver's intelligence in low-speed car following

  NASA Astrophysics Data System (ADS)

  Wei, Junqing; Dolan, John M.; Litkouhi, Bakhtiar

  2010-04-01

  In this paper, an offline learning mechanism based on the genetic algorithm is proposed for autonomous vehicles to emulate human driver behaviors. The autonomous driving ability is implemented based on a Prediction- and Cost function-Based algorithm (PCB). PCB is designed to emulate a human driver's decision process, which is modeled as traffic scenario prediction and evaluation. This paper focuses on using a learning algorithm to optimize PCB with very limited training data, so that PCB can have the ability to predict and evaluate traffic scenarios similarly to human drivers. 80 seconds of human driving data was collected in low-speed (< 30miles/h) car-following scenarios. In the low-speed car-following tests, PCB was able to perform more human-like carfollowing after learning. A more general 120 kilometer-long simulation showed that PCB performs robustly even in scenarios that are not part of the training set.

• Built-up edge investigation in vibration drilling of Al2024-T6.

  PubMed

  Barani, A; Amini, S; Paktinat, H; Fadaei Tehrani, A

  2014-07-01

  Adding ultrasonic vibrations to drilling process results in an advanced hybrid machining process, entitled "vibration drilling". This study presents the design and fabrication of a vibration drilling tool by which both rotary and vibrating motions are applied to drill simultaneously. High frequency and low amplitude vibrations were generated by an ultrasonic transducer with frequency of 19.65 kHz. Ultrasonic transducer was controlled by a MPI ultrasonic generator with 3 kW power. The drilling tool and workpiece material were HSS two-flute twist drill and Al2024-T6, respectively. The aim of this study was investigating on the effect of ultrasonic vibrations on built-up edge, surface quality, chip morphology and wear mechanisms of drill edges. Therefore, these factors were studied in both vibration and ordinary drilling. Based on the achieved results, vibration drilling offers less built-up edge and better surface quality compared to ordinary drilling. Copyright © 2014 Elsevier B.V. All rights reserved.

• An approach for setting evidence-based and stakeholder-informed research priorities in low- and middle-income countries.

  PubMed

  Rehfuess, Eva A; Durão, Solange; Kyamanywa, Patrick; Meerpohl, Joerg J; Young, Taryn; Rohwer, Anke

  2016-04-01

  To derive evidence-based and stakeholder-informed research priorities for implementation in African settings, the international research consortium Collaboration for Evidence-Based Healthcare and Public Health in Africa (CEBHA+) developed and applied a pragmatic approach. First, an online survey and face-to-face consultation between CEBHA+ partners and policy-makers generated priority research areas. Second, evidence maps for these priority research areas identified gaps and related priority research questions. Finally, study protocols were developed for inclusion within a grant proposal. Policy and practice representatives were involved throughout the process. Tuberculosis, diabetes, hypertension and road traffic injuries were selected as priority research areas. Evidence maps covered screening and models of care for diabetes and hypertension, population-level prevention of diabetes and hypertension and their risk factors, and prevention and management of road traffic injuries. Analysis of these maps yielded three priority research questions on hypertension and diabetes and one on road traffic injuries. The four resulting study protocols employ a broad range of primary and secondary research methods; a fifth promotes an integrated methodological approach across all research activities. The CEBHA+ approach, in particular evidence mapping, helped to formulate research questions and study protocols that would be owned by African partners, fill gaps in the evidence base, address policy and practice needs and be feasible given the existing research infrastructure and expertise. The consortium believes that the continuous involvement of decision-makers throughout the research process is an important means of ensuring that studies are relevant to the African context and that findings are rapidly implemented.

• Holistic, model-based optimization of edge leveling as an enabler for lithographic focus control: application to a memory use case

  NASA Astrophysics Data System (ADS)

  Hasan, T.; Kang, Y.-S.; Kim, Y.-J.; Park, S.-J.; Jang, S.-Y.; Hu, K.-Y.; Koop, E. J.; Hinnen, P. C.; Voncken, M. M. A. J.

  2016-03-01

  Advancement of the next generation technology nodes and emerging memory devices demand tighter lithographic focus control. Although the leveling performance of the latest-generation scanners is state of the art, challenges remain at the wafer edge due to large process variations. There are several customer configurable leveling control options available in ASML scanners, some of which are application specific in their scope of leveling improvement. In this paper, we assess the usability of leveling non-correctable error models to identify yield limiting edge dies. We introduce a novel dies-inspec based holistic methodology for leveling optimization to guide tool users in selecting an optimal configuration of leveling options. Significant focus gain, and consequently yield gain, can be achieved with this integrated approach. The Samsung site in Hwaseong observed an improved edge focus performance in a production of a mid-end memory product layer running on an ASML NXT 1960 system. 50% improvement in focus and a 1.5%p gain in edge yield were measured with the optimized configurations.

• Turbine airfoil fabricated from tapered extrusions

  DOEpatents

  Marra, John J

  2013-07-16

  An airfoil (30) and fabrication process for turbine blades with cooling channels (26). Tapered tubes (32A-32D) are bonded together in a parallel sequence, forming a leading edge (21), a trailing edge (22), and pressure and suction side walls (23, 24) connected by internal ribs (25). The tapered tubes may be extruded without camber to simplify the extrusion process, then bonded along matching surfaces (34), forming a non-cambered airfoil (28), which may be cambered in a hot forming process and cut (48) to length. The tubes may have tapered walls that are thinner at the blade tip (T1) than at the base (T2), reducing mass. A cap (50) may be attached to the blade tip. A mounting lug (58) may be forged (60) on the airfoil base and then machined, completing the blade for mounting in a turbine rotor disk.

• Variation in Local-Scale Edge Effects: Mechanisms and landscape Context

  Treesearch

  Therese M. Donovan; Peter W. Jones; Elizabeth M. Annand; Frank R. Thompson III

  1997-01-01

  Ecological processes near habitat edges often differ from processes away from edges. Yet, the generality of "edge effects" has been hotly debated because results vary tremendously. To understand the factors responsible for this variation, we described nest predation and cowbird distribution patterns in forest edge and forest core habitats on 36 randomly...

• Signal optimization in urban transport: A totally asymmetric simple exclusion process with traffic lights.

  PubMed

  Arita, Chikashi; Foulaadvand, M Ebrahim; Santen, Ludger

  2017-03-01

  We consider the exclusion process on a ring with time-dependent defective bonds at which the hopping rate periodically switches between zero and one. This system models main roads in city traffics, intersecting with perpendicular streets. We explore basic properties of the system, in particular dependence of the vehicular flow on the parameters of signalization as well as the system size and the car density. We investigate various types of the spatial distribution of the vehicular density, and show existence of a shock profile. We also measure waiting time behind traffic lights, and examine its relationship with the traffic flow.

• Signal optimization in urban transport: A totally asymmetric simple exclusion process with traffic lights

  NASA Astrophysics Data System (ADS)

  Arita, Chikashi; Foulaadvand, M. Ebrahim; Santen, Ludger

  2017-03-01

  We consider the exclusion process on a ring with time-dependent defective bonds at which the hopping rate periodically switches between zero and one. This system models main roads in city traffics, intersecting with perpendicular streets. We explore basic properties of the system, in particular dependence of the vehicular flow on the parameters of signalization as well as the system size and the car density. We investigate various types of the spatial distribution of the vehicular density, and show existence of a shock profile. We also measure waiting time behind traffic lights, and examine its relationship with the traffic flow.

• 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.

• Air Traffic Control: Immature Software Acquisition Processes Increase FAA System Acquisition Risks

  DOT National Transportation Integrated Search

  1997-03-01

  The General Accounting Office (GAO) at the request of Congress reviewed (1) : the maturity of Federal Aviation Administration's (FAA's) Air Traffic Control : (ATC) modernization software acquisition processes, and (2) the steps/actions : FAA has unde...

• In Patients With Cirrhosis, Driving Simulator Performance Is Associated With Real-life Driving.

  PubMed

  Lauridsen, Mette M; Thacker, Leroy R; White, Melanie B; Unser, Ariel; Sterling, Richard K; Stravitz, Richard T; Matherly, Scott; Puri, Puneet; Sanyal, Arun J; Gavis, Edith A; Luketic, Velimir; Siddiqui, Muhammad S; Heuman, Douglas M; Fuchs, Michael; Bajaj, Jasmohan S

  2016-05-01

  Minimal hepatic encephalopathy (MHE) has been linked to higher real-life rates of automobile crashes and poor performance in driving simulation studies, but the link between driving simulator performance and real-life automobile crashes has not been clearly established. Furthermore, not all patients with MHE are unsafe drivers, but it is unclear how to distinguish them from unsafe drivers. We investigated the link between performance on driving simulators and real-life automobile accidents and traffic violations. We also aimed to identify features of unsafe drivers with cirrhosis and evaluated changes in simulated driving skills and MHE status after 1 year. We performed a study of outpatients with cirrhosis (n = 205; median 55 years old; median model for end-stage liver disease score, 9.5; none with overt hepatic encephalopathy or alcohol or illicit drug use within previous 6 months) seen at the Virginia Commonwealth University and McGuire Veterans Administration Medical Center, from November 2008 through April 2014. All participants were given paper-pencil tests to diagnose MHE (98 had MHE; 48%), and 163 patients completed a standardized driving simulation. Data were collected on traffic violations and automobile accidents from the Virginia Department of Motor Vehicles and from participants' self-assessments when they entered the study, and from 73 participants 1 year later. Participants also completed a questionnaire about alcohol use and cessation patterns. The driving simulator measured crashes, run-time, road center and edge excursions, and illegal turns during navigation; before and after each driving simulation session, patients were asked to rate their overall driving skills. Drivers were classified as safe or unsafe based on crashes and violations reported on official driving records; simulation results were compared with real-life driving records. Multivariable regression analyses of real-life crashes and violations was performed using data on demographics, cirrhosis details, MHE status, and alcohol cessation patterns, at baseline and at 1 year. Drivers categorized as unsafe had more crashes and made more illegal turns on the driving simulator than drivers categorized as safe; a higher proportion of subjects with MHE were categorized as unsafe drivers at baseline (16%) than subjects without MHE (7%; P = .02), and at 1-year follow-up (18% vs 0%; P = .02). Alcohol cessation within <1 year and illegal turns during simulator navigation tasks were associated with real-life automobile crashes and MHE in regression analysis; road edge excursions in the simulator were associated with real-life traffic violations. Personal assessment of driving skills improved after each simulation episode. In a study of 205 patients with cirrhosis, we associated results from driving simulation tests with real-life driving records and MHE. Traffic safety counseling should focus on patients with cirrhosis who recently quit consuming alcohol and perform poorly on driving simulation. Copyright © 2016 AGA Institute. Published by Elsevier Inc. All rights reserved.

Enrichment and sources of trace metals in roadside soils in Shanghai, China: A case study of two urban/rural roads.

PubMed

Yan, Geng; Mao, Lingchen; Liu, Shuoxun; Mao, Yu; Ye, Hua; Huang, Tianshu; Li, Feipeng; Chen, Ling

2018-08-01

The road traffic has become one of the main sources of urban pollution and could directly affect roadside soils. To understand the level of contamination and potential sources of trace metals in roadside soils of Shanghai, 10 trace metals (Sb, Cr, Co, Ni, Cu, Cd, Pb, Hg, Mn and Zn) from two urban/rural roads (Hutai Road and Wunign-Caoan Road) were analyzed in this study. Antimony, Ni, Cu, Cd, Pb, Hg and Zn concentrations were higher than that of soil background values of Shanghai, whereas accumulation of Cr, Co and Mn were minimal. Significantly higher Sb, Cd, Pb contents were found in samples from urban areas than those from suburban area, suggesting the impact from urbanization. The concentrations of Sb and Cd in older road (Hutai) were higher than that in younger road (Wunign-Caoan). Multivariate statistical analysis revealed that Sb, Cu, Cd, Pb and Zn were mainly controlled by traffic activities (e.g. brake wear, tire wear, automobile exhaust) with high contamination levels found near traffic-intensive areas; Cr, Co, Ni and Mn derived primarily from soil parent materials; Hg was related to industrial activities. Besides, the enrichment of Sb, Cd, Cu, Pb and Zn showed a decreasing trend with distance to the road edges. According to the enrichment factors (EF s ), 78.5% of Sb, Cu, Cd, Pb and Zn were in moderate or significant pollution, indicating considerable traffic contribution. In particular, recently introduced in automotive technology, accumulation of Sb has been recognized in 42.9% samples of both roads. The accumulation of these traffic-derived metals causes potential negative impact to human health and ecological environment and should be concerned, especially the emerging trace elements like Sb. Copyright © 2018 Elsevier B.V. All rights reserved.

Spatial Copula Model for Imputing Traffic Flow Data from Remote Microwave Sensors

PubMed Central

Ma, Xiaolei; Du, Bowen; Yu, Bin

2017-01-01

Issues of missing data have become increasingly serious with the rapid increase in usage of traffic sensors. Analyses of the Beijing ring expressway have showed that up to 50% of microwave sensors pose missing values. The imputation of missing traffic data must be urgently solved although a precise solution that cannot be easily achieved due to the significant number of missing portions. In this study, copula-based models are proposed for the spatial interpolation of traffic flow from remote traffic microwave sensors. Most existing interpolation methods only rely on covariance functions to depict spatial correlation and are unsuitable for coping with anomalies due to Gaussian consumption. Copula theory overcomes this issue and provides a connection between the correlation function and the marginal distribution function of traffic flow. To validate copula-based models, a comparison with three kriging methods is conducted. Results indicate that copula-based models outperform kriging methods, especially on roads with irregular traffic patterns. Copula-based models demonstrate significant potential to impute missing data in large-scale transportation networks. PMID:28934164

Analysis on the Correlation of Traffic Flow in Hainan Province Based on Baidu Search

NASA Astrophysics Data System (ADS)

Chen, Caixia; Shi, Chun

2018-03-01

Internet search data records user’s search attention and consumer demand, providing necessary database for the Hainan traffic flow model. Based on Baidu Index, with Hainan traffic flow as example, this paper conduct both qualitative and quantitative analysis on the relationship between search keyword from Baidu Index and actual Hainan tourist traffic flow, and build multiple regression model by SPSS.

49 CFR 1139.2 - Traffic study.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 8 2010-10-01 2010-10-01 false Traffic study. 1139.2 Section 1139.2... of General Commodities § 1139.2 Traffic study. (a) The respondents shall submit a traffic study for... “base-calendar year—actual.” The study shall include a probability sampling of the actual traffic...

49 CFR 1139.2 - Traffic study.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 8 2011-10-01 2011-10-01 false Traffic study. 1139.2 Section 1139.2... of General Commodities § 1139.2 Traffic study. (a) The respondents shall submit a traffic study for... “base-calendar year—actual.” The study shall include a probability sampling of the actual traffic...

Implementation of sobel method to detect the seed rubber plant leaves

NASA Astrophysics Data System (ADS)

Suyanto; Munte, J.

2018-03-01

This research was conducted to develop a system that can identify and recognize the type of rubber tree based on the pattern of leaves of the plant. The steps research are started with the identification of the image data acquisition, image processing, image edge detection and identification method template matching. Edge detection is using Sobel edge detection. Pattern recognition would detect image as input and compared with other images in a database called templates. Experiments carried out in one phase, identification of the leaf edge, using a rubber plant leaf image 14 are superior and 5 for each type of test images (clones) of the plant. From the experimental results obtained by the recognition rate of 91.79%.

NbN/MgO/NbN edge-geometry tunnel junctions

NASA Technical Reports Server (NTRS)

Hunt, B. D.; Leduc, H. G.; Cypher, S. R.; Stern, J. A.; Judas, A.

1989-01-01

The fabrication and low-frequency testing of the first edge-geometry NbN/MgO/NbN superconducting tunnel junctions are reported. The use of an edge geometry allows very small junction areas to be obtained, while the all-NbN electrodes permit operation at 8-10 K with a potential maximum operating frequency above 1 THz. Edge definition in the base NbN film was accomplished utilizing Ar ion milling with an Al2O3 milling mask, followed by a lower energy ion cleaning step. This process has produced all-refractory-material tunnel junctions with areas as small as 0.1 sq micron, resistance-area products less than 21 ohm sq micron, and subgap to normal state resistance ratios larger than 18.

Wavelet domain image restoration with adaptive edge-preserving regularization.

PubMed

Belge, M; Kilmer, M E; Miller, E L

2000-01-01

In this paper, we consider a wavelet based edge-preserving regularization scheme for use in linear image restoration problems. Our efforts build on a collection of mathematical results indicating that wavelets are especially useful for representing functions that contain discontinuities (i.e., edges in two dimensions or jumps in one dimension). We interpret the resulting theory in a statistical signal processing framework and obtain a highly flexible framework for adapting the degree of regularization to the local structure of the underlying image. In particular, we are able to adapt quite easily to scale-varying and orientation-varying features in the image while simultaneously retaining the edge preservation properties of the regularizer. We demonstrate a half-quadratic algorithm for obtaining the restorations from observed data.

A novel multisensor traffic state assessment system based on incomplete data.

PubMed

Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Jiang, Yaoliang

2014-01-01

A novel multisensor system with incomplete data is presented for traffic state assessment. The system comprises probe vehicle detection sensors, fixed detection sensors, and traffic state assessment algorithm. First of all, the validity checking of the traffic flow data is taken as preprocessing of this method. And then a new method based on the history data information is proposed to fuse and recover the incomplete data. According to the characteristics of space complementary of data based on the probe vehicle detector and fixed detector, a fusion model of space matching is presented to estimate the mean travel speed of the road. Finally, the traffic flow data include flow, speed and, occupancy rate, which are detected between Beijing Deshengmen bridge and Drum Tower bridge, are fused to assess the traffic state of the road by using the fusion decision model of rough sets and cloud. The accuracy of experiment result can reach more than 98%, and the result is in accordance with the actual road traffic state. This system is effective to assess traffic state, and it is suitable for the urban intelligent transportation system.

A Novel Multisensor Traffic State Assessment System Based on Incomplete Data

PubMed Central

Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Jiang, Yaoliang

2014-01-01

A novel multisensor system with incomplete data is presented for traffic state assessment. The system comprises probe vehicle detection sensors, fixed detection sensors, and traffic state assessment algorithm. First of all, the validity checking of the traffic flow data is taken as preprocessing of this method. And then a new method based on the history data information is proposed to fuse and recover the incomplete data. According to the characteristics of space complementary of data based on the probe vehicle detector and fixed detector, a fusion model of space matching is presented to estimate the mean travel speed of the road. Finally, the traffic flow data include flow, speed and, occupancy rate, which are detected between Beijing Deshengmen bridge and Drum Tower bridge, are fused to assess the traffic state of the road by using the fusion decision model of rough sets and cloud. The accuracy of experiment result can reach more than 98%, and the result is in accordance with the actual road traffic state. This system is effective to assess traffic state, and it is suitable for the urban intelligent transportation system. PMID:25162055

Face recognition via edge-based Gabor feature representation for plastic surgery-altered images

NASA Astrophysics Data System (ADS)

Chude-Olisah, Chollette C.; Sulong, Ghazali; Chude-Okonkwo, Uche A. K.; Hashim, Siti Z. M.

2014-12-01

Plastic surgery procedures on the face introduce skin texture variations between images of the same person (intra-subject), thereby making the task of face recognition more difficult than in normal scenario. Usually, in contemporary face recognition systems, the original gray-level face image is used as input to the Gabor descriptor, which translates to encoding some texture properties of the face image. The texture-encoding process significantly degrades the performance of such systems in the case of plastic surgery due to the presence of surgically induced intra-subject variations. Based on the proposition that the shape of significant facial components such as eyes, nose, eyebrow, and mouth remains unchanged after plastic surgery, this paper employs an edge-based Gabor feature representation approach for the recognition of surgically altered face images. We use the edge information, which is dependent on the shapes of the significant facial components, to address the plastic surgery-induced texture variation problems. To ensure that the significant facial components represent useful edge information with little or no false edges, a simple illumination normalization technique is proposed for preprocessing. Gabor wavelet is applied to the edge image to accentuate on the uniqueness of the significant facial components for discriminating among different subjects. The performance of the proposed method is evaluated on the Georgia Tech (GT) and the Labeled Faces in the Wild (LFW) databases with illumination and expression problems, and the plastic surgery database with texture changes. Results show that the proposed edge-based Gabor feature representation approach is robust against plastic surgery-induced face variations amidst expression and illumination problems and outperforms the existing plastic surgery face recognition methods reported in the literature.

Improving vehicle tracking rate and speed estimation in dusty and snowy weather conditions with a vibrating camera

PubMed Central

Yaghoobi Ershadi, Nastaran

2017-01-01

Traffic surveillance systems are interesting to many researchers to improve the traffic control and reduce the risk caused by accidents. In this area, many published works are only concerned about vehicle detection in normal conditions. The camera may vibrate due to wind or bridge movement. Detection and tracking of vehicles is a very difficult task when we have bad weather conditions in winter (snowy, rainy, windy, etc.), dusty weather in arid and semi-arid regions, at night, etc. Also, it is very important to consider speed of vehicles in the complicated weather condition. In this paper, we improved our method to track and count vehicles in dusty weather with vibrating camera. For this purpose, we used a background subtraction based strategy mixed with an extra processing to segment vehicles. In this paper, the extra processing included the analysis of the headlight size, location, and area. In our work, tracking was done between consecutive frames via a generalized particle filter to detect the vehicle and pair the headlights using the connected component analysis. So, vehicle counting was performed based on the pairing result, with Centroid of each blob we calculated distance between two frames by simple formula and hence dividing it by the time between two frames obtained from the video. Our proposed method was tested on several video surveillance records in different conditions such as dusty or foggy weather, vibrating camera, and in roads with medium-level traffic volumes. The results showed that the new proposed method performed better than our previously published method and other methods, including the Kalman filter or Gaussian model, in different traffic conditions. PMID:29261719

Improving vehicle tracking rate and speed estimation in dusty and snowy weather conditions with a vibrating camera.

PubMed

Yaghoobi Ershadi, Nastaran

2017-01-01

Traffic surveillance systems are interesting to many researchers to improve the traffic control and reduce the risk caused by accidents. In this area, many published works are only concerned about vehicle detection in normal conditions. The camera may vibrate due to wind or bridge movement. Detection and tracking of vehicles is a very difficult task when we have bad weather conditions in winter (snowy, rainy, windy, etc.), dusty weather in arid and semi-arid regions, at night, etc. Also, it is very important to consider speed of vehicles in the complicated weather condition. In this paper, we improved our method to track and count vehicles in dusty weather with vibrating camera. For this purpose, we used a background subtraction based strategy mixed with an extra processing to segment vehicles. In this paper, the extra processing included the analysis of the headlight size, location, and area. In our work, tracking was done between consecutive frames via a generalized particle filter to detect the vehicle and pair the headlights using the connected component analysis. So, vehicle counting was performed based on the pairing result, with Centroid of each blob we calculated distance between two frames by simple formula and hence dividing it by the time between two frames obtained from the video. Our proposed method was tested on several video surveillance records in different conditions such as dusty or foggy weather, vibrating camera, and in roads with medium-level traffic volumes. The results showed that the new proposed method performed better than our previously published method and other methods, including the Kalman filter or Gaussian model, in different traffic conditions.

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.

Virtualized MME Design for IoT Support in 5G Systems.

PubMed

Andres-Maldonado, Pilar; Ameigeiras, Pablo; Prados-Garzon, Jonathan; Ramos-Munoz, Juan Jose; Lopez-Soler, Juan Manuel

2016-08-22

Cellular systems are recently being considered an option to provide support to the Internet of Things (IoT). To enable this support, the 3rd Generation Partnership Project (3GPP) has introduced new procedures specifically targeted for cellular IoT. With one of these procedures, the transmissions of small and infrequent data packets from/to the devices are encapsulated in signaling messages and sent through the control plane. However, these transmissions from/to a massive number of devices may imply a major increase of the processing load on the control plane entities of the network and in particular on the Mobility Management Entity (MME). In this paper, we propose two designs of an MME based on Network Function Virtualization (NFV) that aim at facilitating the IoT support. The first proposed design partially separates the processing resources dedicated to each traffic class. The second design includes traffic shaping to control the traffic of each class. We consider three classes: Mobile Broadband (MBB), low latency Machine to Machine communications (lM2M) and delay-tolerant M2M communications. Our proposals enable reducing the processing resources and, therefore, the cost. Additionally, results show that the proposed designs lessen the impact between classes, so they ease the compliance of the delay requirements of MBB and lM2M communications.

Edge-region grouping in figure-ground organization and depth perception.

PubMed

Palmer, Stephen E; Brooks, Joseph L

2008-12-01

Edge-region grouping (ERG) is proposed as a unifying and previously unrecognized class of relational information that influences figure-ground organization and perceived depth across an edge. ERG occurs when the edge between two regions is differentially grouped with one region based on classic principles of similarity grouping. The ERG hypothesis predicts that the grouped side will tend to be perceived as the closer, figural region. Six experiments are reported that test the predictions of the ERG hypothesis for 6 similarity-based factors: common fate, blur similarity, color similarity, orientation similarity, proximity, and flicker synchrony. All 6 factors produce the predicted effects, although to different degrees. In a 7th experiment, the strengths of these figural/depth effects were found to correlate highly with the strength of explicit grouping ratings of the same visual displays. The relations of ERG to prior results in the literature are discussed, and possible reasons for ERG-based figural/depth effects are considered. We argue that grouping processes mediate at least some of the effects we report here, although ecological explanations are also likely to be relevant in the majority of cases.

Edge-Region Grouping in Figure-Ground Organization and Depth Perception

PubMed Central

Palmer, Stephen E.; Brooks, Joseph L.

2008-01-01

Edge-region grouping (ERG) is proposed as a unifying and previously unrecognized class of relational information that influences figure-ground organization and perceived depth across an edge. ERG occurs when the edge between two regions is differentially grouped with one region based on classic principles of similarity grouping. The ERG hypothesis predicts that the grouped side will tend to be perceived as the closer, figural region. Six experiments are reported that test the predictions of the ERG hypothesis for six similarity-based factors: common fate, blur similarity, color similarity, orientation similarity, proximity, and flicker synchrony. All six factors produce the predicted effects, although to different degrees. In the seventh experiment, the strengths of these figural/depth effects were found to correlate highly with the strength of explicit grouping ratings of the same visual displays. The relations of ERG to prior results in the literature are discussed, and possible reasons for ERG-based figural/depth effects are considered. We argue that grouping processes mediate at least some of the effects we report here, although ecological explanations are also likely to be relevant in the majority of cases. PMID:19045980

A microscopic lane changing process model for multilane traffic

NASA Astrophysics Data System (ADS)

Lv, Wei; Song, Wei-guo; Liu, Xiao-dong; Ma, Jian

2013-03-01

In previous simulations lane-changing behavior is usually assumed as an instantaneous action. However, in real traffic, lane changing is a continuing process which can seriously affect the following cars. In this paper, a microscopic lane-changing process (LCP) model is clearly described. A new idea of simplifying the lane-changing process to the car-following framework is presented by controlling fictitious cars. To verify the model, the results of flow, lane-changing frequency, and single-car velocity are extracted from experimental observations and are compared with corresponding simulation. It is found that the LCP model agrees well with actual traffic flow and lane-changing behaviors may induce a 12%-18% reduction of traffic flow. The results also reflect that most of the drivers on the two roads in a city are conservative but not aggressive to change lanes. Investigation of lane-changing frequency shows that the largest lane-changing frequency occurs at a medium density range from 15 vehs km lane to 35 vehs km lane. It also implies that the lane-changing process might strengthen velocity variation at medium density and weaken velocity variation at high density. It is hoped that the idea of this study may be helpful to promote the modeling and simulation study of traffic flow.

Macroscopic modeling of freeway traffic using an artificial neural network

DOT National Transportation Integrated Search

1997-01-01

Traffic flow on freeways is a complex process that often is described by a set of highly nonlinear, dynamic equations in the form of a macroscopic traffic flow model. However, some of the existing macroscopic models have been found to exhibit instabi...

Deinterlacing using modular neural network

NASA Astrophysics Data System (ADS)

Woo, Dong H.; Eom, Il K.; Kim, Yoo S.

2004-05-01

Deinterlacing is the conversion process from the interlaced scan to progressive one. While many previous algorithms that are based on weighted-sum cause blurring in edge region, deinterlacing using neural network can reduce the blurring through recovering of high frequency component by learning process, and is found robust to noise. In proposed algorithm, input image is divided into edge and smooth region, and then, to each region, one neural network is assigned. Through this process, each neural network learns only patterns that are similar, therefore it makes learning more effective and estimation more accurate. But even within each region, there are various patterns such as long edge and texture in edge region. To solve this problem, modular neural network is proposed. In proposed modular neural network, two modules are combined in output node. One is for low frequency feature of local area of input image, and the other is for high frequency feature. With this structure, each modular neural network can learn different patterns with compensating for drawback of counterpart. Therefore it can adapt to various patterns within each region effectively. In simulation, the proposed algorithm shows better performance compared with conventional deinterlacing methods and single neural network method.

Transparent flexible nanogenerator as self-powered sensor for transportation monitoring

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

Wang, Zhong Lin; Hu, Youfan; Lin, Long

2016-06-14

A traffic sensor includes a flexible substrate having a top surface. A piezoelectric structure extends from the first electrode layer. The piezoelectric structure has a top end. An insulating layer is infused into the piezoelectric structure. A first electrode layer is disposed on top of the insulating layer. A second electrode layer is disposed below the flexible substrate. A packaging layer is disposed around the substrate, the first electrode layer, the piezoelectric structure, the insulating layer and the second electrode layer. In a method of sensing a traffic parameter, a piezoelectric nanostructure-based traffic sensor is applied to a roadway. Anmore » electrical event generated by the piezoelectric nanostructure-based traffic sensor in response to a vehicle interacting with the piezoelectric nanostructure-based traffic sensor is detected. The electrical event is correlated with the traffic parameter.« less

Feature extraction algorithm for space targets based on fractal theory

NASA Astrophysics Data System (ADS)

Tian, Balin; Yuan, Jianping; Yue, Xiaokui; Ning, Xin

2007-11-01

In order to offer a potential for extending the life of satellites and reducing the launch and operating costs, satellite servicing including conducting repairs, upgrading and refueling spacecraft on-orbit become much more frequently. Future space operations can be more economically and reliably executed using machine vision systems, which can meet real time and tracking reliability requirements for image tracking of space surveillance system. Machine vision was applied to the research of relative pose for spacecrafts, the feature extraction algorithm was the basis of relative pose. In this paper fractal geometry based edge extraction algorithm which can be used in determining and tracking the relative pose of an observed satellite during proximity operations in machine vision system was presented. The method gets the gray-level image distributed by fractal dimension used the Differential Box-Counting (DBC) approach of the fractal theory to restrain the noise. After this, we detect the consecutive edge using Mathematical Morphology. The validity of the proposed method is examined by processing and analyzing images of space targets. The edge extraction method not only extracts the outline of the target, but also keeps the inner details. Meanwhile, edge extraction is only processed in moving area to reduce computation greatly. Simulation results compared edge detection using the method which presented by us with other detection methods. The results indicate that the presented algorithm is a valid method to solve the problems of relative pose for spacecrafts.

Pulsed Film Cooling on a Turbine Blade Leading Edge

DTIC Science & Technology

2009-09-01

LEADING EDGE 1. Introduction Gas turbine engines are based on the Brayton cycle in which atmospheric air is compressed, heated via combustion...generation. Because the working fluid is in an open loop, a cooling process is absent from the Brayton cycle. The ideal Brayton cycle (one in which...Technology, Taylor & Francis, 2000. Harrison, K. and Bogard, D., “CFD Predictions of Film Cooling Adiabatic Effectiveness for Cylindrical Holes Embedded

Delay-feedback control strategy for reducing CO2 emission of traffic flow system

NASA Astrophysics Data System (ADS)

Zhang, Li-Dong; Zhu, Wen-Xing

2015-06-01

To study the signal control strategy for reducing traffic emission theoretically, we first presented a kind of discrete traffic flow model with relative speed term based on traditional coupled map car-following model. In the model, the relative speed difference between two successive running cars is incorporated into following vehicle's acceleration running equation. Then we analyzed its stability condition with discrete control system stability theory. Third, we designed a delay-feedback controller to suppress traffic jam and decrease traffic emission based on modern controller theory. Last, numerical simulations are made to support our theoretical results, including the comparison of models' stability analysis, the influence of model type and signal control on CO2 emissions. The results show that the temporal behavior of our model is superior to other models, and the traffic signal controller has good effect on traffic jam suppression and traffic CO2 emission, which fully supports the theoretical conclusions.

Prediction based active ramp metering control strategy with mobility and safety assessment

NASA Astrophysics Data System (ADS)

Fang, Jie; Tu, Lili

2018-04-01

Ramp metering is one of the most direct and efficient motorway traffic flow management measures so as to improve traffic conditions. However, owing to short of traffic conditions prediction, in earlier studies, the impact on traffic flow dynamics of the applied RM control was not quantitatively evaluated. In this study, a RM control algorithm adopting Model Predictive Control (MPC) framework to predict and assess future traffic conditions, which taking both the current traffic conditions and the RM-controlled future traffic states into consideration, was presented. The designed RM control algorithm targets at optimizing the network mobility and safety performance. The designed algorithm is evaluated in a field-data-based simulation. Through comparing the presented algorithm controlled scenario with the uncontrolled scenario, it was proved that the proposed RM control algorithm can effectively relieve the congestion of traffic network with no significant compromises in safety aspect.

A graph signal filtering-based approach for detection of different edge types on airborne lidar data

NASA Astrophysics Data System (ADS)

Bayram, Eda; Vural, Elif; Alatan, Aydin

2017-10-01

Airborne Laser Scanning is a well-known remote sensing technology, which provides a dense and highly accurate, yet unorganized point cloud of earth surface. During the last decade, extracting information from the data generated by airborne LiDAR systems has been addressed by many studies in geo-spatial analysis and urban monitoring applications. However, the processing of LiDAR point clouds is challenging due to their irregular structure and 3D geometry. In this study, we propose a novel framework for the detection of the boundaries of an object or scene captured by LiDAR. Our approach is motivated by edge detection techniques in vision research and it is established on graph signal filtering which is an exciting and promising field of signal processing for irregular data types. Due to the convenient applicability of graph signal processing tools on unstructured point clouds, we achieve the detection of the edge points directly on 3D data by using a graph representation that is constructed exclusively to answer the requirements of the application. Moreover, considering the elevation data as the (graph) signal, we leverage aerial characteristic of the airborne LiDAR data. The proposed method can be employed both for discovering the jump edges on a segmentation problem and for exploring the crease edges on a LiDAR object on a reconstruction/modeling problem, by only adjusting the filter characteristics.

2D Radiative Processes Near Cloud Edges

NASA Technical Reports Server (NTRS)

Varnai, T.

2012-01-01

Because of the importance and complexity of dynamical, microphysical, and radiative processes taking place near cloud edges, the transition zone between clouds and cloud free air has been the subject of intense research both in the ASR program and in the wider community. One challenge in this research is that the one-dimensional (1D) radiative models widely used in both remote sensing and dynamical simulations become less accurate near cloud edges: The large horizontal gradients in particle concentrations imply that accurate radiative calculations need to consider multi-dimensional radiative interactions among areas that have widely different optical properties. This study examines the way the importance of multidimensional shortwave radiative interactions changes as we approach cloud edges. For this, the study relies on radiative simulations performed for a multiyear dataset of clouds observed over the NSA, SGP, and TWP sites. This dataset is based on Microbase cloud profiles as well as wind measurements and ARM cloud classification products. The study analyzes the way the difference between 1D and 2D simulation results increases near cloud edges. It considers both monochromatic radiances and broadband radiative heating, and it also examines the influence of factors such as cloud type and height, and solar elevation. The results provide insights into the workings of radiative processes and may help better interpret radiance measurements and better estimate the radiative impacts of this critical region.

Numerical and experimental investigation of strip deformation in cage roll forming process for pipes with low ratio of thickness/diameter

NASA Astrophysics Data System (ADS)

Kasaei, M. M.; Naeini, H. Moslemi; Tehrani, M. Salmani; Tafti, R. Azizi

2011-01-01

Cage roll forming is one of the advanced methods of cold roll forming process which is used widely for producing ERW pipes. In addition to decreasing the production cost and time, using cage roll forming provides smooth deformation on the strip. Few studies can be found about cage roll forming because of its complexity, and the available knowledge is experience-based more than science-based. In this paper, deformation of pipes with low ratio of thickness/diameter is investigated by 3D finite element simulation in Marc-Mentat software. Edge buckling defect in cage roll forming of low ratio of thickness/diameter pipes is very important. Due to direct influence of longitudinal strain on the edge buckling phenomenon, longitudinal strains at the edge and center line of the strip are investigated and high risk stands are introduced. The deformed strip is predicted using the simulation results and effects of each cage forming stage on the deformed strip profile are specified. In order to verify the simulation results, strip width and opening distance of the two edges in different forming stages are obtained from the simulations and compared with the experimental data which were measured from the production line. A good agreement between the experimental and simulated results is observed.

Intelligent model-based OPC

NASA Astrophysics Data System (ADS)

Huang, W. C.; Lai, C. M.; Luo, B.; Tsai, C. K.; Chih, M. H.; Lai, C. W.; Kuo, C. C.; Liu, R. G.; Lin, H. T.

2006-03-01

Optical proximity correction is the technique of pre-distorting mask layouts so that the printed patterns are as close to the desired shapes as possible. For model-based optical proximity correction, a lithographic model to predict the edge position (contour) of patterns on the wafer after lithographic processing is needed. Generally, segmentation of edges is performed prior to the correction. Pattern edges are dissected into several small segments with corresponding target points. During the correction, the edges are moved back and forth from the initial drawn position, assisted by the lithographic model, to finally settle on the proper positions. When the correction converges, the intensity predicted by the model in every target points hits the model-specific threshold value. Several iterations are required to achieve the convergence and the computation time increases with the increase of the required iterations. An artificial neural network is an information-processing paradigm inspired by biological nervous systems, such as how the brain processes information. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. A neural network can be a powerful data-modeling tool that is able to capture and represent complex input/output relationships. The network can accurately predict the behavior of a system via the learning procedure. A radial basis function network, a variant of artificial neural network, is an efficient function approximator. In this paper, a radial basis function network was used to build a mapping from the segment characteristics to the edge shift from the drawn position. This network can provide a good initial guess for each segment that OPC has carried out. The good initial guess reduces the required iterations. Consequently, cycle time can be shortened effectively. The optimization of the radial basis function network for this system was practiced by genetic algorithm, which is an artificially intelligent optimization method with a high probability to obtain global optimization. From preliminary results, the required iterations were reduced from 5 to 2 for a simple dumbbell-shape layout.

A new smart traffic monitoring method using embedded cement-based piezoelectric sensors

NASA Astrophysics Data System (ADS)

Zhang, Jinrui; Lu, Youyuan; Lu, Zeyu; Liu, Chao; Sun, Guoxing; Li, Zongjin

2015-02-01

Cement-based piezoelectric composites are employed as the sensing elements of a new smart traffic monitoring system. The piezoelectricity of the cement-based piezoelectric sensors enables powerful and accurate real-time detection of the pressure induced by the traffic flow. To describe the mechanical-electrical conversion mechanism between traffic flow and the electrical output of the embedded piezoelectric sensors, a mathematical model is established based on Duhamel’s integral, the constitutive law and the charge-leakage characteristics of the piezoelectric composite. Laboratory tests show that the voltage magnitude of the sensor is linearly proportional to the applied pressure, which ensures the reliability of the cement-based piezoelectric sensors for traffic monitoring. A series of on-site road tests by a 10 tonne truck and a 6.8 tonne van show that vehicle weight-in-motion can be predicted based on the mechanical-electrical model by taking into account the vehicle speed and the charge-leakage property of the piezoelectric sensor. In the speed range from 20 km h-1 to 70 km h-1, the error of the repeated weigh-in-motion measurements of the 6.8 tonne van is less than 1 tonne. The results indicate that the embedded cement-based piezoelectric sensors and associated measurement setup have good capability of smart traffic monitoring, such as traffic flow detection, vehicle speed detection and weigh-in-motion measurement.

Key Technology of Real-Time Road Navigation Method Based on Intelligent Data Research

PubMed Central

Tang, Haijing; Liang, Yu; Huang, Zhongnan; Wang, Taoyi; He, Lin; Du, Yicong; Ding, Gangyi

2016-01-01

The effect of traffic flow prediction plays an important role in routing selection. Traditional traffic flow forecasting methods mainly include linear, nonlinear, neural network, and Time Series Analysis method. However, all of them have some shortcomings. This paper analyzes the existing algorithms on traffic flow prediction and characteristics of city traffic flow and proposes a road traffic flow prediction method based on transfer probability. This method first analyzes the transfer probability of upstream of the target road and then makes the prediction of the traffic flow at the next time by using the traffic flow equation. Newton Interior-Point Method is used to obtain the optimal value of parameters. Finally, it uses the proposed model to predict the traffic flow at the next time. By comparing the existing prediction methods, the proposed model has proven to have good performance. It can fast get the optimal value of parameters faster and has higher prediction accuracy, which can be used to make real-time traffic flow prediction. PMID:27872637

A Game-Theory Based Incentive Framework for an Intelligent Traffic System as Part of a Smart City Initiative

PubMed Central

Mei, Haibo; Poslad, Stefan; Du, Shuang

2017-01-01

Intelligent Transportation Systems (ITSs) can be applied to inform and incentivize travellers to help them make cognizant choices concerning their trip routes and transport modality use for their daily travel whilst achieving more sustainable societal and transport authority goals. However, in practice, it is challenging for an ITS to enable incentive generation that is context-driven and personalized, whilst supporting multi-dimensional travel goals. This is because an ITS has to address the situation where different travellers have different travel preferences and constraints for route and modality, in the face of dynamically-varying traffic conditions. Furthermore, personalized incentive generation also needs to dynamically achieve different travel goals from multiple travellers, in the face of their conducts being a mix of both competitive and cooperative behaviours. To address this challenge, a Rule-based Incentive Framework (RIF) is proposed in this paper that utilizes both decision tree and evolutionary game theory to process travel information and intelligently generate personalized incentives for travellers. The travel information processed includes travellers’ mobile patterns, travellers’ modality preferences and route traffic volume information. A series of MATLAB simulations of RIF was undertaken to validate RIF to show that it is potentially an effective way to incentivize travellers to change travel routes and modalities as an essential smart city service. PMID:29232907

Emerging Definition of Next-Generation of Aeronautical Communications

NASA Technical Reports Server (NTRS)

Kerczewski, Robert J.

2006-01-01

Aviation continues to experience rapid growth. In regions such as the United States and Europe air traffic congestion is constraining operations, leading to major new efforts to develop methodologies and infrastructures to enable continued aviation growth through transformational air traffic management systems. Such a transformation requires better communications linking airborne and ground-based elements. Technologies for next-generation communications, the required capacities, frequency spectrum of operation, network interconnectivity, and global interoperability are now receiving increased attention. A number of major planning and development efforts have taken place or are in process now to define the transformed airspace of the future. These activities include government and industry led efforts in the United States and Europe, and by international organizations. This paper will review the features, approaches, and activities of several representative planning and development efforts, and identify the emerging global consensus on requirements of next generation aeronautical communications systems for air traffic control.

Processing and filtrating of driver fatigue characteristic parameters based on rough set

NASA Astrophysics Data System (ADS)

Ye, Wenwu; Zhao, Xuyang

2018-05-01

With the rapid development of economy, people become increasingly rich, and cars have become a common means of transportation in daily life. However, the problem of traffic safety is becoming more and more serious. And fatigue driving is one of the main causes of traffic accidents. Therefore, it is of great importance for us to study the detection of fatigue driving to improve traffic safety. In the cause of determining whether the driver is tired, the characteristic quantity related to the steering angle of the steering wheel and the characteristic quantity of the driver's pulse are all important indicators. The fuzzy c-means clustering is used to discretize the above indexes. Because the characteristic parameters are too miscellaneous, rough set is used to filtrate these characteristics. Finally, this paper finds out the highest correlation with fatigue driving. It is proved that these selected characteristics are of great significance to the evaluation of fatigue driving.

LEDs as light source: examining quality of acquired images

NASA Astrophysics Data System (ADS)

Bachnak, Rafic; Funtanilla, Jeng; Hernandez, Jose

2004-05-01

Recent advances in technology have made light emitting diodes (LEDs) viable in a number of applications, including vehicle stoplights, traffic lights, machine-vision-inspection, illumination, and street signs. This paper presents the results of comparing images taken by a videoscope using two different light sources. One of the sources is the internal metal halide lamp and the other is a LED placed at the tip of the insertion tube. Images acquired using these two light sources were quantitatively compared using their histogram, intensity profile along a line segment, and edge detection. Also, images were qualitatively compared using image registration and transformation. The gray-level histogram, edge detection, image profile and image registration do not offer conclusive results. The LED light source, however, produces good images for visual inspection by an operator. The paper will present the results and discuss the usefulness and shortcomings of various comparison methods.

Task-Related Edge Density (TED)—A New Method for Revealing Dynamic Network Formation in fMRI Data of the Human Brain

PubMed Central

Lohmann, Gabriele; Stelzer, Johannes; Zuber, Verena; Buschmann, Tilo; Margulies, Daniel; Bartels, Andreas; Scheffler, Klaus

2016-01-01

The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach “Task-related Edge Density” (TED). TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function. PMID:27341204

Task-Related Edge Density (TED)-A New Method for Revealing Dynamic Network Formation in fMRI Data of the Human Brain.

PubMed

Lohmann, Gabriele; Stelzer, Johannes; Zuber, Verena; Buschmann, Tilo; Margulies, Daniel; Bartels, Andreas; Scheffler, Klaus

2016-01-01

The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach "Task-related Edge Density" (TED). TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function.

Traffic pollution and countermeasures of urban traffic environment

NASA Astrophysics Data System (ADS)

He, Yuhong; Zheng, Chaocheng

2018-01-01

Background: Traffic environment has become a serious social problem in China currently, therefore, urban traffic environment governance is the requirement to solve this issue because as an important place in people's social life, urban traffic environment shows a strong city's energy. Objective: Based on analysis on social function of city traffic environment and its influence of traffic on urban environment in this paper, the goal to establish a healthy urban traffic environment must be included under the aim of sustainable development eternally and feasible measures were put forward afterwards. Method, result, conclusion and possible applications.

NextGen Operational Improvements: Will they Improve Human Performance

NASA Technical Reports Server (NTRS)

Beard, Bettina L.; Johnston, James C.; Holbrook, Jon

2013-01-01

Modernization of the National Airspace System depends critically on the development of advanced technology, including cutting-edge automation, controller decision-support tools and integrated on-demand information. The Next Generation Air Transportation System national plan envisions air traffic control tower automation that proposes solutions for seven problems: 1) departure metering, 2) taxi routing, 3) taxi and runway scheduling, 4) departure runway assignments, 5) departure flow management, 6) integrated arrival and departure scheduling and 7) runway configuration management. Government, academia and industry are simultaneously pursuing the development of these tools. For each tool, the development process typically begins by assessing its potential benefits, and then progresses to designing preliminary versions of the tool, followed by testing the tool's strengths and weaknesses using computational modeling, human-in-the-loop simulation and/or field tests. We compiled the literature, evaluated the methodological rigor of the studies and served as referee for partisan conclusions that were sometimes overly optimistic. Here we provide the results of this review.

Defining the origins of electron transfer at screen-printed graphene-like and graphite electrodes: MoO2 nanowire fabrication on edge plane sites reveals electrochemical insights.

PubMed

Rowley-Neale, Samuel J; Brownson, Dale A C; Banks, Craig E

2016-08-18

Molybdenum (di)oxide (MoO2) nanowires are fabricated onto graphene-like and graphite screen-printed electrodes (SPEs) for the first time, revealing crucial insights into the electrochemical properties of carbon/graphitic based materials. Distinctive patterns observed in the electrochemical process of nanowire decoration show that electron transfer occurs predominantly on edge plane sites when utilising SPEs fabricated/comprised of graphitic materials. Nanowire fabrication along the edge plane sites (and on edge plane like-sites/defects) of graphene/graphite is confirmed with Cyclic Voltammetry, Scanning Electron Microscopy (SEM) and Raman Spectroscopy. Comparison of the heterogeneous electron transfer (HET) rate constants (k°) at unmodified and nanowire coated SPEs show a reduction in the electrochemical reactivity of SPEs when the edge plane sites are effectively blocked/coated with MoO2. Throughout the process, the basal plane sites of the graphene/graphite electrodes remain relatively uncovered; except when the available edge plane sites have been utilised, in which case MoO2 deposition grows from the edge sites covering the entire surface of the electrode. This work clearly illustrates the distinct electron transfer properties of edge and basal plane sites on graphitic materials, indicating favourable electrochemical reactivity at the edge planes in contrast to limited reactivity at the basal plane sites. In addition to providing fundamental insights into the electron transfer properties of graphite and graphene-like SPEs, the reported simple, scalable, and cost effective formation of unique and intriguing MoO2 nanowires realised herein is of significant interest for use in both academic and commercial applications.

Swarm Intelligence for Optimizing Hybridized Smoothing Filter in Image Edge Enhancement

NASA Astrophysics Data System (ADS)

Rao, B. Tirumala; Dehuri, S.; Dileep, M.; Vindhya, A.

In this modern era, image transmission and processing plays a major role. It would be impossible to retrieve information from satellite and medical images without the help of image processing techniques. Edge enhancement is an image processing step that enhances the edge contrast of an image or video in an attempt to improve its acutance. Edges are the representations of the discontinuities of image intensity functions. For processing these discontinuities in an image, a good edge enhancement technique is essential. The proposed work uses a new idea for edge enhancement using hybridized smoothening filters and we introduce a promising technique of obtaining best hybrid filter using swarm algorithms (Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO)) to search for an optimal sequence of filters from among a set of rather simple, representative image processing filters. This paper deals with the analysis of the swarm intelligence techniques through the combination of hybrid filters generated by these algorithms for image edge enhancement.

Symbols and warrants for major traffic generator guide signing.

DOT National Transportation Integrated Search

2009-09-01

The Texas Manual on Uniform Traffic Control Devices (TMUTCD) provides the definition of regular traffic generators based on four population types but not for major traffic generators (MTGs). MTG signs have been considered to supplement the overall si...

Development of a mobile probe-based traffic data fusion and flow management platform for innovative public-private information-based partnerships.

DOT National Transportation Integrated Search

2011-10-17

"Under the aegis of Intelligent Transportation Systems (ITS), real-time traffic information provision strategies are being proposed to manage traffic congestion, alleviate the effects of incidents, enhance response efficiency after disasters, and imp...

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.

Predicting commuter flows in spatial networks using a radiation model based on temporal ranges

NASA Astrophysics Data System (ADS)

Ren, Yihui; Ercsey-Ravasz, Mária; Wang, Pu; González, Marta C.; Toroczkai, Zoltán

2014-11-01

Understanding network flows such as commuter traffic in large transportation networks is an ongoing challenge due to the complex nature of the transportation infrastructure and human mobility. Here we show a first-principles based method for traffic prediction using a cost-based generalization of the radiation model for human mobility, coupled with a cost-minimizing algorithm for efficient distribution of the mobility fluxes through the network. Using US census and highway traffic data, we show that traffic can efficiently and accurately be computed from a range-limited, network betweenness type calculation. The model based on travel time costs captures the log-normal distribution of the traffic and attains a high Pearson correlation coefficient (0.75) when compared with real traffic. Because of its principled nature, this method can inform many applications related to human mobility driven flows in spatial networks, ranging from transportation, through urban planning to mitigation of the effects of catastrophic events.

Evaluation of Roadway Reallocation Projects: Analysis of Before-and-After Travel Speeds and Congestion Utilizing High-Resolution Bus Transit Data

DOT National Transportation Integrated Search

2017-11-01

The traditional process of identifying corridors for road diet improvements involves selecting potential corridors (mostly based on identifying fourlane roads) and conducting a traffic impact analysis of proposed changes on a selected roadway before ...

Neural methods based on modified reputation rules for detection and identification of intrusion attacks in wireless ad hoc sensor networks

NASA Astrophysics Data System (ADS)

Hortos, William S.

2010-04-01

Determining methods to secure the process of data fusion against attacks by compromised nodes in wireless sensor networks (WSNs) and to quantify the uncertainty that may exist in the aggregation results is a critical issue in mitigating the effects of intrusion attacks. Published research has introduced the concept of the trustworthiness (reputation) of a single sensor node. Reputation is evaluated using an information-theoretic concept, the Kullback- Leibler (KL) distance. Reputation is added to the set of security features. In data aggregation, an opinion, a metric of the degree of belief, is generated to represent the uncertainty in the aggregation result. As aggregate information is disseminated along routes to the sink node(s), its corresponding opinion is propagated and regulated by Josang's belief model. By applying subjective logic on the opinion to manage trust propagation, the uncertainty inherent in aggregation results can be quantified for use in decision making. The concepts of reputation and opinion are modified to allow their application to a class of dynamic WSNs. Using reputation as a factor in determining interim aggregate information is equivalent to implementation of a reputation-based security filter at each processing stage of data fusion, thereby improving the intrusion detection and identification results based on unsupervised techniques. In particular, the reputation-based version of the probabilistic neural network (PNN) learns the signature of normal network traffic with the random probability weights normally used in the PNN replaced by the trust-based quantified reputations of sensor data or subsequent aggregation results generated by the sequential implementation of a version of Josang's belief model. A two-stage, intrusion detection and identification algorithm is implemented to overcome the problems of large sensor data loads and resource restrictions in WSNs. Performance of the twostage algorithm is assessed in simulations of WSN scenarios with multiple sensors at edge nodes for known intrusion attacks. Simulation results show improved robustness of the two-stage design based on reputation-based NNs to intrusion anomalies from compromised nodes and external intrusion attacks.

Generation algorithm of craniofacial structure contour in cephalometric images

NASA Astrophysics Data System (ADS)

Mondal, Tanmoy; Jain, Ashish; Sardana, H. K.

2010-02-01

Anatomical structure tracing on cephalograms is a significant way to obtain cephalometric analysis. Computerized cephalometric analysis involves both manual and automatic approaches. The manual approach is limited in accuracy and repeatability. In this paper we have attempted to develop and test a novel method for automatic localization of craniofacial structure based on the detected edges on the region of interest. According to the grey scale feature at the different region of the cephalometric images, an algorithm for obtaining tissue contour is put forward. Using edge detection with specific threshold an improved bidirectional contour tracing approach is proposed by an interactive selection of the starting edge pixels, the tracking process searches repetitively for an edge pixel at the neighborhood of previously searched edge pixel to segment images, and then craniofacial structures are obtained. The effectiveness of the algorithm is demonstrated by the preliminary experimental results obtained with the proposed method.

XAS study of TiO2-based nanomaterials

NASA Astrophysics Data System (ADS)

Schneider, K.; Zajac, D.; Sikora, M.; Kapusta, Cz.; Michalow-Mauke, K.; Graule, Th.; Rekas, M.

2015-07-01

X-Ray Absorption Spectroscopy studies of the W (0-1 at% W) and Mo-doped TiO2 (0-1 at% Mo) nanoparticle specimens at the K edges of titanium and molybdenum as well as at the L2 L3 edges of tungsten are presented. The materials were prepared with Flame Spray Synthesis process by oxidation of metal-organic precursors. The Ti:K edge spectra in the XANES range show pre-edge and post-edge features characteristic for anatase. A decrease of the amplitude of the EXAFS function with doping is observed and attributed to a softening of the crystal lattice. The Mo EXAFS functions show a considerable decrease of the second-neighbour-shell peak with increasing Mo content, which is attributed to an increased number of cation vacancies. For tungsten a less pronounced effect is observed. The Mo and W XANES spectra do not show noticeable changes with doping level, which indicates their unchanged oxidation states.

Measurements and modelling of base station power consumption under real traffic loads.

PubMed

Lorincz, Josip; Garma, Tonko; Petrovic, Goran

2012-01-01

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient.

Measurements and Modelling of Base Station Power Consumption under Real Traffic Loads †

PubMed Central

Lorincz, Josip; Garma, Tonko; Petrovic, Goran

2012-01-01

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient. PMID:22666026

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.

Iris Location Algorithm Based on the CANNY Operator and Gradient Hough Transform

NASA Astrophysics Data System (ADS)

Zhong, L. H.; Meng, K.; Wang, Y.; Dai, Z. Q.; Li, S.

2017-12-01

In the iris recognition system, the accuracy of the localization of the inner and outer edges of the iris directly affects the performance of the recognition system, so iris localization has important research meaning. Our iris data contain eyelid, eyelashes, light spot and other noise, even the gray transformation of the images is not obvious, so the general methods of iris location are unable to realize the iris location. The method of the iris location based on Canny operator and gradient Hough transform is proposed. Firstly, the images are pre-processed; then, calculating the gradient information of images, the inner and outer edges of iris are coarse positioned using Canny operator; finally, according to the gradient Hough transform to realize precise localization of the inner and outer edge of iris. The experimental results show that our algorithm can achieve the localization of the inner and outer edges of the iris well, and the algorithm has strong anti-interference ability, can greatly reduce the location time and has higher accuracy and stability.

Fast and accurate edge orientation processing during object manipulation

PubMed Central

Flanagan, J Randall; Johansson, Roland S

2018-01-01

Quickly and accurately extracting information about a touched object’s orientation is a critical aspect of dexterous object manipulation. However, the speed and acuity of tactile edge orientation processing with respect to the fingertips as reported in previous perceptual studies appear inadequate in these respects. Here we directly establish the tactile system’s capacity to process edge-orientation information during dexterous manipulation. Participants extracted tactile information about edge orientation very quickly, using it within 200 ms of first touching the object. Participants were also strikingly accurate. With edges spanning the entire fingertip, edge-orientation resolution was better than 3° in our object manipulation task, which is several times better than reported in previous perceptual studies. Performance remained impressive even with edges as short as 2 mm, consistent with our ability to precisely manipulate very small objects. Taken together, our results radically redefine the spatial processing capacity of the tactile system. PMID:29611804

Traffic Games: Modeling Freeway Traffic with Game Theory

PubMed Central

Cortés-Berrueco, Luis E.; Gershenson, Carlos; Stephens, Christopher R.

2016-01-01

We apply game theory to a vehicular traffic model to study the effect of driver strategies on traffic flow. The resulting model inherits the realistic dynamics achieved by a two-lane traffic model and aims to incorporate phenomena caused by driver-driver interactions. To achieve this goal, a game-theoretic description of driver interaction was developed. This game-theoretic formalization allows one to model different lane-changing behaviors and to keep track of mobility performance. We simulate the evolution of cooperation, traffic flow, and mobility performance for different modeled behaviors. The analysis of these results indicates a mobility optimization process achieved by drivers’ interactions. PMID:27855176

Traffic Games: Modeling Freeway Traffic with Game Theory.

PubMed

Cortés-Berrueco, Luis E; Gershenson, Carlos; Stephens, Christopher R

2016-01-01

We apply game theory to a vehicular traffic model to study the effect of driver strategies on traffic flow. The resulting model inherits the realistic dynamics achieved by a two-lane traffic model and aims to incorporate phenomena caused by driver-driver interactions. To achieve this goal, a game-theoretic description of driver interaction was developed. This game-theoretic formalization allows one to model different lane-changing behaviors and to keep track of mobility performance. We simulate the evolution of cooperation, traffic flow, and mobility performance for different modeled behaviors. The analysis of these results indicates a mobility optimization process achieved by drivers' interactions.

The importance of antipersistence for traffic jams

NASA Astrophysics Data System (ADS)

Krause, Sebastian M.; Habel, Lars; Guhr, Thomas; Schreckenberg, Michael

2017-05-01

Universal characteristics of road networks and traffic patterns can help to forecast and control traffic congestion. The antipersistence of traffic flow time series has been found for many data sets, but its relevance for congestion has been overseen. Based on empirical data from motorways in Germany, we study how antipersistence of traffic flow time-series impacts the duration of traffic congestion on a wide range of time scales. We find a large number of short-lasting traffic jams, which implies a large risk for rear-end collisions.

Method for wafer edge profile extraction using optical images obtained in edge defect inspection process

NASA Astrophysics Data System (ADS)

Okamoto, Hiroaki; Sakaguchi, Naoshi; Hayano, Fuminori

2010-03-01

It is becoming increasingly important to monitor wafer edge profiles in the immersion lithography era. A Nikon edge defect inspection tool acquires the circumferential optical images of the wafer edge during its inspection process. Nikon's unique illumination system and optics make it possible to then convert the brightness data of the captured images to quantifiable edge profile information. During this process the wafer's outer shape is also calculated. Test results show that even newly shipped bare wafers may not have a constant shape over 360 degree. In some cases repeated deformations with 90 degree pitch are observed.

A cortical edge-integration model of object-based lightness computation that explains effects of spatial context and individual differences

PubMed Central

Rudd, Michael E.

2014-01-01

Previous work has demonstrated that perceived surface reflectance (lightness) can be modeled in simple contexts in a quantitatively exact way by assuming that the visual system first extracts information about local, directed steps in log luminance, then spatially integrates these steps along paths through the image to compute lightness (Rudd and Zemach, 2004, 2005, 2007). This method of computing lightness is called edge integration. Recent evidence (Rudd, 2013) suggests that human vision employs a default strategy to integrate luminance steps only along paths from a common background region to the targets whose lightness is computed. This implies a role for gestalt grouping in edge-based lightness computation. Rudd (2010) further showed the perceptual weights applied to edges in lightness computation can be influenced by the observer's interpretation of luminance steps as resulting from either spatial variation in surface reflectance or illumination. This implies a role for top-down factors in any edge-based model of lightness (Rudd and Zemach, 2005). Here, I show how the separate influences of grouping and attention on lightness can be modeled in tandem by a cortical mechanism that first employs top-down signals to spatially select regions of interest for lightness computation. An object-based network computation, involving neurons that code for border-ownership, then automatically sets the neural gains applied to edge signals surviving the earlier spatial selection stage. Only the borders that survive both processing stages are spatially integrated to compute lightness. The model assumptions are consistent with those of the cortical lightness model presented earlier by Rudd (2010, 2013), and with neurophysiological data indicating extraction of local edge information in V1, network computations to establish figure-ground relations and border ownership in V2, and edge integration to encode lightness and darkness signals in V4. PMID:25202253

A cortical edge-integration model of object-based lightness computation that explains effects of spatial context and individual differences.

PubMed

Rudd, Michael E

2014-01-01

Previous work has demonstrated that perceived surface reflectance (lightness) can be modeled in simple contexts in a quantitatively exact way by assuming that the visual system first extracts information about local, directed steps in log luminance, then spatially integrates these steps along paths through the image to compute lightness (Rudd and Zemach, 2004, 2005, 2007). This method of computing lightness is called edge integration. Recent evidence (Rudd, 2013) suggests that human vision employs a default strategy to integrate luminance steps only along paths from a common background region to the targets whose lightness is computed. This implies a role for gestalt grouping in edge-based lightness computation. Rudd (2010) further showed the perceptual weights applied to edges in lightness computation can be influenced by the observer's interpretation of luminance steps as resulting from either spatial variation in surface reflectance or illumination. This implies a role for top-down factors in any edge-based model of lightness (Rudd and Zemach, 2005). Here, I show how the separate influences of grouping and attention on lightness can be modeled in tandem by a cortical mechanism that first employs top-down signals to spatially select regions of interest for lightness computation. An object-based network computation, involving neurons that code for border-ownership, then automatically sets the neural gains applied to edge signals surviving the earlier spatial selection stage. Only the borders that survive both processing stages are spatially integrated to compute lightness. The model assumptions are consistent with those of the cortical lightness model presented earlier by Rudd (2010, 2013), and with neurophysiological data indicating extraction of local edge information in V1, network computations to establish figure-ground relations and border ownership in V2, and edge integration to encode lightness and darkness signals in V4.

A Hidden Markov Model for Urban-Scale Traffic Estimation Using Floating Car Data.

PubMed

Wang, Xiaomeng; Peng, Ling; Chi, Tianhe; Li, Mengzhu; Yao, Xiaojing; Shao, Jing

2015-01-01

Urban-scale traffic monitoring plays a vital role in reducing traffic congestion. Owing to its low cost and wide coverage, floating car data (FCD) serves as a novel approach to collecting traffic data. However, sparse probe data represents the vast majority of the data available on arterial roads in most urban environments. In order to overcome the problem of data sparseness, this paper proposes a hidden Markov model (HMM)-based traffic estimation model, in which the traffic condition on a road segment is considered as a hidden state that can be estimated according to the conditions of road segments having similar traffic characteristics. An algorithm based on clustering and pattern mining rather than on adjacency relationships is proposed to find clusters with road segments having similar traffic characteristics. A multi-clustering strategy is adopted to achieve a trade-off between clustering accuracy and coverage. Finally, the proposed model is designed and implemented on the basis of a real-time algorithm. Results of experiments based on real FCD confirm the applicability, accuracy, and efficiency of the model. In addition, the results indicate that the model is practicable for traffic estimation on urban arterials and works well even when more than 70% of the probe data are missing.

Chemical compositions and source identification of PM₂.₅ aerosols for estimation of a diesel source surrogate.

PubMed

Sahu, Manoranjan; Hu, Shaohua; Ryan, Patrick H; Le Masters, Grace; Grinshpun, Sergey A; Chow, Judith C; Biswas, Pratim

2011-06-01

Exposure to traffic-related pollution during childhood has been associated with asthma exacerbation, and asthma incidence. The objective of the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS) is to determine if the development of allergic and respiratory disease is associated with exposure to diesel engine exhaust particles. A detailed receptor model analyses was undertaken by applying positive matrix factorization (PMF) and UNMIX receptor models to two PM₂.₅ data sets: one consisting of two carbon fractions and the other of eight temperature-resolved carbon fractions. Based on the source profiles resolved from the analyses, markers of traffic-related air pollution were estimated: the elemental carbon attributed to traffic (ECAT) and elemental carbon attributed to diesel vehicle emission (ECAD). Application of UNMIX to the two data sets generated four source factors: combustion related sulfate, traffic, metal processing and soil/crustal. The PMF application generated six source factors derived from analyzing two carbon fractions and seven factors from temperature-resolved eight carbon fractions. The source factors (with source contribution estimates by mass concentrations in parentheses) are: combustion sulfate (46.8%), vegetative burning (15.8%), secondary sulfate (12.9%), diesel vehicle emission (10.9%), metal processing (7.5%), gasoline vehicle emission (5.6%) and soil/crustal (0.7%). Diesel and gasoline vehicle emission sources were separated using eight temperature-resolved organic and elemental carbon fractions. Application of PMF to both datasets also differentiated the sulfate rich source from the vegetative burning source, which are combined in a single factor by UNMIX modeling. Calculated ECAT and ECAD values at different locations indicated that traffic source impacts depend on factors such as traffic volumes, meteorological parameters, and the mode of vehicle operation apart from the proximity of the sites to highways. The difference in ECAT and ECAD, however, was less than one standard deviation. Thus, a cost benefit consideration should be used when deciding on the benefits of an eight or two carbon approach. Published by Elsevier B.V.

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

Dey, Ritu; Ghosh, Joydeep; Chowdhuri, M. B.

Neutral particle behavior in Aditya tokamak, which has a circular poloidal ring limiter at one particular toroidal location, has been investigated using DEGAS2 code. The code is based on the calculation using Monte Carlo algorithms and is mainly used in tokamaks with divertor configuration. This code has been successfully implemented in Aditya tokamak with limiter configuration. The penetration of neutral hydrogen atom is studied with various atomic and molecular contributions and it is found that the maximum contribution comes from the dissociation processes. For the same, H α spectrum is also simulated which was matched with the experimental one. Themore » dominant contribution around 64% comes from molecular dissociation processes and neutral particle is generated by those processes have energy of ~ 2.0 eV. Furthermore, the variation of neutral hydrogen density and H α emissivity profile are analysed for various edge temperature profiles and found that there is not much changes in H α emission at the plasma edge with the variation of edge temperature (7 to 40 eV).« less

Diagnosis diagrams for passing signals on an automatic block signaling railway section

NASA Astrophysics Data System (ADS)

Spunei, E.; Piroi, I.; Chioncel, C. P.; Piroi, F.

2018-01-01

This work presents a diagnosis method for railway traffic security installations. More specifically, the authors present a series of diagnosis charts for passing signals on a railway block equipped with an automatic block signaling installation. These charts are based on the exploitation electric schemes, and are subsequently used to develop a diagnosis software package. The thus developed software package contributes substantially to a reduction of failure detection and remedy for these types of installation faults. The use of the software package eliminates making wrong decisions in the fault detection process, decisions that may result in longer remedy times and, sometimes, to railway traffic events.

Traffic Flow Management Wrap-Up

NASA Technical Reports Server (NTRS)

Grabbe, Shon

2011-01-01

Traffic Flow Management involves the scheduling and routing of air traffic subject to airport and airspace capacity constraints, and the efficient use of available airspace. Significant challenges in this area include: (1) weather integration and forecasting, (2) accounting for user preferences in the Traffic Flow Management decision making process, and (3) understanding and mitigating the environmental impacts of air traffic on the environment. To address these challenges, researchers in the Traffic Flow Management area are developing modeling, simulation and optimization techniques to route and schedule air traffic flights and flows while accommodating user preferences, accounting for system uncertainties and considering the environmental impacts of aviation. This presentation will highlight some of the major challenges facing researchers in this domain, while also showcasing recent innovations designed to address these challenges.

Evaluation of traffic responsive control on the Reston Parkway arterial network.

DOT National Transportation Integrated Search

2009-01-01

Traffic responsive plan selection (TRPS) control is considered an effective operational mode in traffic signal systems. Its efficiency stems from the fact that it can capture variations in traffic patterns and switch timing plans based on existing tr...

A real-time MTFC algorithm of space remote-sensing camera based on FPGA

NASA Astrophysics Data System (ADS)

Zhao, Liting; Huang, Gang; Lin, Zhe

2018-01-01

A real-time MTFC algorithm of space remote-sensing camera based on FPGA was designed. The algorithm can provide real-time image processing to enhance image clarity when the remote-sensing camera running on-orbit. The image restoration algorithm adopted modular design. The MTF measurement calculation module on-orbit had the function of calculating the edge extension function, line extension function, ESF difference operation, normalization MTF and MTFC parameters. The MTFC image filtering and noise suppression had the function of filtering algorithm and effectively suppressing the noise. The algorithm used System Generator to design the image processing algorithms to simplify the design structure of system and the process redesign. The image gray gradient dot sharpness edge contrast and median-high frequency were enhanced. The image SNR after recovery reduced less than 1 dB compared to the original image. The image restoration system can be widely used in various fields.

Balloon-borne air traffic management (ATM) as a precursor to space-based ATM

NASA Astrophysics Data System (ADS)

Brodsky, Yuval; Rieber, Richard; Nordheim, Tom

2012-01-01

The International Space University—Balloon Air traffic control Technology Experiment (I-BATE ) has flown on board two stratospheric balloons and has tracked nearby aircraft by receiving their Automatic Dependent Surveillance-Broadcast (ADS-B) transmissions. Air traffic worldwide is facing increasing congestion. It is predicted that daily European flight volumes will more than double by 2030 compared to 2009 volumes. ADS-B is an air traffic management system being used to mitigate air traffic congestion. Each aircraft is equipped with both a GPS receiver and an ADS-B transponder. The transponder transmits an equipped aircraft's unique identifier, position, heading, and velocity once per second. The ADS-B transmissions can then be received by ground stations for use in traditional air traffic management. Airspace not monitored by these ground stations or other traditional means remains uncontrolled and poorly monitored. A constellation of space-based ADS-B receivers could close these gaps and provide global air traffic monitoring. By flying an ADS-B receiver on a stratospheric balloon, I-BATE has served as a precursor to a constellation of ADS-B-equipped Earth-orbiting satellites. From the ˜30 km balloon altitude, I-BATE tracked aircraft ranging up to 850 km. The experiment has served as a proof of concept for space-based air traffic management and supports a technology readiness level 6 of space-based ADS-B reception. I-BATE: International Space University—Balloon Air traffic control Technology Experiment.

Performance of chip seals using local and minimally processed aggregates for preservation of low traffic volume roadways.

DOT National Transportation Integrated Search

2013-07-01

This report documents the performance of two low traffic volume experimental chip seals constructed using : locally available, minimally processed sand and gravel aggregates after four winters of service. The projects : were constructed by CDOT maint...

The burden of road traffic injuries in Nigeria: results of a population-based survey.

PubMed

Labinjo, M; Juillard, C; Kobusingye, O C; Hyder, A A

2009-06-01

Mortality from road traffic injuries in sub-Saharan Africa is among the highest in the world, yet data from the region are sparse. To date, no multi-site population-based survey on road traffic injuries has been reported from Nigeria, the most populated country in Africa. To explore the epidemiology of road traffic injury in Nigeria and provide data on the populations affected and risk factors for road traffic injury. Data from a population-based survey using two-stage stratified cluster sampling. SUBJECTS/ SETTING: Road traffic injury status and demographic information were collected on 3082 respondents living in 553 households in seven of Nigeria's 37 states. Incidence rates were estimated with confidence intervals based on a Poisson distribution; Poisson regression analysis was used to calculate relative risks for associated factors. The overall road traffic injury rate was 41 per 1000 population (95% CI 34 to 49), and mortality from road traffic injuries was 1.6 per 1000 population (95% CI 0.5 to 3.8). Motorcycle crashes accounted for 54% of all road traffic injuries. The road traffic injury rates found for rural and urban respondents were not significantly different. Increased risk of injury was associated with male gender among those aged 18-44 years, with a relative risk of 2.96 when compared with women in the same age range (95% CI 1.72 to 5.09, p<0.001). The road traffic injury rates found in this survey highlight a neglected public health problem in Nigeria. Simple extrapolations from this survey suggest that over 4 million people may be injured and as many as 200 000 potentially killed as the result of road traffic crashes annually in Nigeria. Appropriate interventions in both the health and transport sectors are needed to address this significant cause of morbidity and mortality in Nigeria.

Modeling and analyses for an extended car-following model accounting for drivers' situation awareness from cyber physical perspective

NASA Astrophysics Data System (ADS)

Chen, Dong; Sun, Dihua; Zhao, Min; Zhou, Tong; Cheng, Senlin

2018-07-01

In fact, driving process is a typical cyber physical process which couples tightly the cyber factor of traffic information with the physical components of the vehicles. Meanwhile, the drivers have situation awareness in driving process, which is not only ascribed to the current traffic states, but also extrapolates the changing trend. In this paper, an extended car-following model is proposed to account for drivers' situation awareness. The stability criterion of the proposed model is derived via linear stability analysis. The results show that the stable region of proposed model will be enlarged on the phase diagram compared with previous models. By employing the reductive perturbation method, the modified Korteweg de Vries (mKdV) equation is obtained. The kink-antikink soliton of mKdV equation reveals theoretically the evolution of traffic jams. Numerical simulations are conducted to verify the analytical results. Two typical traffic Scenarios are investigated. The simulation results demonstrate that drivers' situation awareness plays a key role in traffic flow oscillations and the congestion transition.

Intelligent Traffic Light Based on PLC Control

NASA Astrophysics Data System (ADS)

Mei, Lin; Zhang, Lijian; Wang, Lingling

2017-11-01

The traditional traffic light system with a fixed control mode and single control function is contradicted with the current traffic section. The traditional one has been unable to meet the functional requirements of the existing flexible traffic control system. This paper research and develop an intelligent traffic light called PLC control system. It uses PLC as control core, using a sensor module for receiving real-time information of vehicles, traffic control mode for information to select the traffic lights. Of which control mode is flexible and changeable, and it also set the countdown reminder to improve the effectiveness of traffic lights, which can realize the goal of intelligent traffic diversion, intelligent traffic diversion.

Cooperative Vehicular Traffic Monitoring in Realistic Low Penetration Scenarios: The COLOMBO Experience

PubMed Central

Caselli, Federico; Corradi, Antonio

2018-01-01

The relevance of effective and efficient solutions for vehicle traffic surveillance is widely recognized in order to enable advanced strategies for traffic management, e.g., based on dynamically adaptive and decentralized traffic light management. However, most related solutions in the literature, based on the powerful enabler of cooperative vehicular communications, assume the complete penetration rate of connectivity/communication technologies (and willingness to participate in the collaborative surveillance service) over the targeted vehicle population, thus making them not applicable nowadays. The paper originally proposes an innovative solution for cooperative traffic surveillance based on vehicular communications capable of: (i) working with low penetration rates of the proposed technology and (ii) of collecting a large set of monitoring data about vehicle mobility in targeted areas of interest. The paper presents insights and lessons learnt from the design and implementation work of the proposed solution. Moreover, it reports extensive performance evaluation results collected on realistic simulation scenarios based on the usage of iTETRIS with real traces of vehicular traffic of the city of Bologna. The reported results show the capability of our proposal to consistently estimate the real vehicular traffic even with low penetration rates of our solution (only 10%). PMID:29522427

Virtual Induction Loops Based on Cooperative Vehicular Communications

PubMed Central

Gramaglia, Marco; Bernardos, Carlos J.; Calderon, Maria

2013-01-01

Induction loop detectors have become the most utilized sensors in traffic management systems. The gathered traffic data is used to improve traffic efficiency (i.e., warning users about congested areas or planning new infrastructures). Despite their usefulness, their deployment and maintenance costs are expensive. Vehicular networks are an emerging technology that can support novel strategies for ubiquitous and more cost-effective traffic data gathering. In this article, we propose and evaluate VIL (Virtual Induction Loop), a simple and lightweight traffic monitoring system based on cooperative vehicular communications. The proposed solution has been experimentally evaluated through simulation using real vehicular traces. PMID:23348033

Simulation and analysis of traffic flow based on cellular automaton

NASA Astrophysics Data System (ADS)

Ren, Xianping; Liu, Xia

2018-03-01

In this paper, single-lane and two-lane traffic model are established based on cellular automaton. Different values of vehicle arrival rate at the entrance and vehicle departure rate at the exit are set to analyze their effects on density, average speed and traffic flow. If the road exit is unblocked, vehicles can pass through the road smoothly despite of the arrival rate at the entrance. If vehicles enter into the road continuously, the traffic condition is varied with the departure rate at the exit. To avoid traffic jam, reasonable vehicle departure rate should be adopted.

A parallel finite element procedure for contact-impact problems using edge-based smooth triangular element and GPU

NASA Astrophysics Data System (ADS)

Cai, Yong; Cui, Xiangyang; Li, Guangyao; Liu, Wenyang

2018-04-01

The edge-smooth finite element method (ES-FEM) can improve the computational accuracy of triangular shell elements and the mesh partition efficiency of complex models. In this paper, an approach is developed to perform explicit finite element simulations of contact-impact problems with a graphical processing unit (GPU) using a special edge-smooth triangular shell element based on ES-FEM. Of critical importance for this problem is achieving finer-grained parallelism to enable efficient data loading and to minimize communication between the device and host. Four kinds of parallel strategies are then developed to efficiently solve these ES-FEM based shell element formulas, and various optimization methods are adopted to ensure aligned memory access. Special focus is dedicated to developing an approach for the parallel construction of edge systems. A parallel hierarchy-territory contact-searching algorithm (HITA) and a parallel penalty function calculation method are embedded in this parallel explicit algorithm. Finally, the program flow is well designed, and a GPU-based simulation system is developed, using Nvidia's CUDA. Several numerical examples are presented to illustrate the high quality of the results obtained with the proposed methods. In addition, the GPU-based parallel computation is shown to significantly reduce the computing time.

Traffic speed data imputation method based on tensor completion.

PubMed

Ran, Bin; Tan, Huachun; Feng, Jianshuai; Liu, Ying; Wang, Wuhong

2015-01-01

Traffic speed data plays a key role in Intelligent Transportation Systems (ITS); however, missing traffic data would affect the performance of ITS as well as Advanced Traveler Information Systems (ATIS). In this paper, we handle this issue by a novel tensor-based imputation approach. Specifically, tensor pattern is adopted for modeling traffic speed data and then High accurate Low Rank Tensor Completion (HaLRTC), an efficient tensor completion method, is employed to estimate the missing traffic speed data. This proposed method is able to recover missing entries from given entries, which may be noisy, considering severe fluctuation of traffic speed data compared with traffic volume. The proposed method is evaluated on Performance Measurement System (PeMS) database, and the experimental results show the superiority of the proposed approach over state-of-the-art baseline approaches.

Traffic Speed Data Imputation Method Based on Tensor Completion

PubMed Central

Ran, Bin; Feng, Jianshuai; Liu, Ying; Wang, Wuhong

2015-01-01

Traffic speed data plays a key role in Intelligent Transportation Systems (ITS); however, missing traffic data would affect the performance of ITS as well as Advanced Traveler Information Systems (ATIS). In this paper, we handle this issue by a novel tensor-based imputation approach. Specifically, tensor pattern is adopted for modeling traffic speed data and then High accurate Low Rank Tensor Completion (HaLRTC), an efficient tensor completion method, is employed to estimate the missing traffic speed data. This proposed method is able to recover missing entries from given entries, which may be noisy, considering severe fluctuation of traffic speed data compared with traffic volume. The proposed method is evaluated on Performance Measurement System (PeMS) database, and the experimental results show the superiority of the proposed approach over state-of-the-art baseline approaches. PMID:25866501

[Definition of hospital discharge, serious injury and death from traffic injuries].

PubMed

Pérez, Katherine; Seguí-Gómez, María; Arrufat, Vita; Barberia, Eneko; Cabeza, Elena; Cirera, Eva; Gil, Mercedes; Martín, Carlos; Novoa, Ana M; Olabarría, Marta; Lardelli, Pablo; Suelves, Josep Maria; Santamariña-Rubio, Elena

2014-01-01

Road traffic injury surveillance involves methodological difficulties due, among other reasons, to the lack of consensus criteria for case definition. Police records have usually been the main source of information for monitoring traffic injuries, while health system data has hardly been used. Police records usually include comprehensive information on the characteristics of the crash, but often underreport injury cases and do not collect reliable information on the severity of injuries. However, statistics on severe traffic injuries have been based almost exclusively on police data. The aim of this paper is to propose criteria based on medical records to define: a) "Hospital discharge for traffic injuries", b) "Person with severe traffic injury", and c) "Death from traffic injuries" in order to homogenize the use of these sources. Copyright © 2014. Published by Elsevier Espana.

A Turn-Projected State-Based Conflict Resolution Algorithm

NASA Technical Reports Server (NTRS)

Butler, Ricky W.; Lewis, Timothy A.

2013-01-01

State-based conflict detection and resolution (CD&R) algorithms detect conflicts and resolve them on the basis on current state information without the use of additional intent information from aircraft flight plans. Therefore, the prediction of the trajectory of aircraft is based solely upon the position and velocity vectors of the traffic aircraft. Most CD&R algorithms project the traffic state using only the current state vectors. However, the past state vectors can be used to make a better prediction of the future trajectory of the traffic aircraft. This paper explores the idea of using past state vectors to detect traffic turns and resolve conflicts caused by these turns using a non-linear projection of the traffic state. A new algorithm based on this idea is presented and validated using a fast-time simulator developed for this study.