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A First Step Towards Dynamic Hybrid Traffic Modeling
[article]
2015
arXiv
pre-print
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variables: traffic density, mean speed and traffic volume. ...
The work conducted in this paper presents a first step allowing simulation of wide area traffic network on the basis of dynamic hybrid modeling, where the representation associated to a network section ...
Such models characterize the traffic state at any given time by the positions and speeds of all simulated vehicles. In case of multi-lane traffic, the lane index complements the state description. ...
arXiv:1505.07257v1
fatcat:gnnrpi5jwbgblbfcuxkfat7i2y
Vehicle Interaction Behavior Prediction with Self-Attention
2022
Sensors
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Firstly, a five-vehicle based cluster structure is designed to extract the interactive features between ego-vehicle and target vehicle, such as Deceleration Rate to Avoid a Crash (DRAC) and the lane gap ...
Finally, target vehicle's future behavior will be predicted by a sub-network consists of a fully connected layer and SoftMax module. ...
The lane gap can intuitively reflect the dense traffic of the current lane and the target lane. When the speed is allowed, the driver tends to drive in the sparse lane of the vehicle. ...
doi:10.3390/s22020429
pmid:35062390
pmcid:PMC8779130
fatcat:gcens233cze27myfvba6mu2dli
Dynamic Hybrid Traffic Flow Modeling
[article]
2014
arXiv
pre-print
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In 2013 we started the development of a multi-level agent-based simulator called JAM-FREE within the ISART project. ...
It allows to simulate large road networks efficiently using a dynamic level of detail. This simulator relies on a multi-level agent-based modeling framework called SIMILAR. ...
Acknowledgments This work has been supported by International Campus on Safety and Intermodality in Transportation (CISIT), the Nord-Pas-de-Calais Region, the European Community, the Regional Delegation ...
arXiv:1401.6773v1
fatcat:2rdislhflbelfap6truftaakdy
Survey on Road Traffic System and Violation Using Sensor Networks
2017
International Journal of Recent Trends in Engineering and Research
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Road Traffic in crowded cities like Tokyo, ...
Improved multi-objective weighted clustering algorithm in Wireless Sensor Network Objectives A well-designed clustering algorithm, WSN's energy consumption can be decreased evidently. ...
Types of clustering • Static: local topology control • Dynamic: changing network parameters • Single hop and multi hop • Homogeneous and heterogeneous
Learning Outcome In this work we have proposed an ...
doi:10.23883/ijrter.2017.3134.idxz0
fatcat:fwnosnzdxfewpp3ajpand7ql34
A Coordination Algorithm for Signalized Multi-intersection to Maximize Green Wave Band in V2X Network
2020
IEEE Access
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The urban traffic network is composed of hundreds of intersections, some of which are adjacent. The vehicle clusters are highlighted, especially when going through the multiplex traffic network. ...
Note that the moving vehicles merely share the traffic information with RSU, whereas only the vehicles stopped in the lane can be grouped into the cluster. ...
Monitoring Area (a) Lane WE4 VOLUME XX, 2017 9 [31] K. Gao ...
doi:10.1109/access.2020.3039263
fatcat:e5k5kgecnzdlll76i6ojbisq3q
A clustering-based multi-channel Vehicle-to-Vehicle (V2V) communication system
2009
2009 First International Conference on Ubiquitous and Future Networks
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In this thesis, we propose a clustering-based multi-channel V2V communication system to provide traffic accident avoidance mechanism. ...
In the proposed system, vehicles are self-organized into different clusters, and the traditional single common medium in a MANET has been divided into multiple control channels and a single data channel ...
What is more, with the deployment of clustering technique and contention-free MAC protocols in wireless networks, the huge overheads also Due to the advantages of multi-channel technique, a number of multi-channel ...
doi:10.1109/icufn.2009.5174290
fatcat:tosdqikornewrjk77mn5gfq7ke
Expressive Real-Time Intersection Scheduling
2019
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
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Traffic congestion is a widespread annoyance throughout global metropolitan areas. It causes increases in travel time, increases in emissions, inefficient usage of gasoline, and driver frustration. ...
Inefficient signal patterns at traffic lights are one major cause of such congestion. ...
ERIS' Executor first calculates a prediction of vehicle clusters in each lane using nearby vehicle broadcasts of position, speed, and heading as well as information shared from neighboring intersections ...
doi:10.1609/aaai.v33i01.33019882
fatcat:3ohoxkt3abeabozazyxoxh6pwq
Multi-lane Detection Using Instance Segmentation and Attentive Voting
[article]
2020
arXiv
pre-print
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In this paper, we propose a novel solution to multi-lane detection, which outperforms state of the art methods in terms of both accuracy and speed. ...
Most of these architectures are trained in a traffic constrained environment. ...
It can be exploited by limiting the depth of the encoder, by increasing the inference speed and by decreasing learnable parameters in lane segmentation network. ...
arXiv:2001.00236v1
fatcat:xkgxfpi5nvf5tjrsrhdx2nksgm
Methods for division of road traffic network for distributed simulation performed on heterogeneous clusters
2013
Computer Science and Information Systems
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In this paper, we present two methods for road traffic network division for heterogeneous clusters. ...
In a macroscopic simulation, the traffic in particular traffic lanes is represented by traffic flows described by set of parameters (e.g. mean speed, vehicle density, etc.). ...
It employs a standard genetic algorithm for a multi-objective optimization [24] for the division of the road traffic network. The genetic algorithms mimic the natural genetic evolution in nature. ...
doi:10.2298/csis120601006p
fatcat:gul4tjgkkbentb3hy2wwiydl4e
Multi-Hop Broadcasting in Vehicular Ad Hoc Networks with Shockwave Traffic
2010
2010 7th IEEE Consumer Communications and Networking Conference
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In this paper, we investigate safety applications in highways with shockwave mobility and different lane configurations in vehicular ad hoc networks (VANET). ...
We evaluate the performance of multi-hop broadcast communication using the ns-2 simulator with vehicles following a shockwave mobility pattern in fully-connected traffic streams. ...
ACKNOWLEDGMENT This research is supported in part by a grant from University of California Transportation Center. ...
doi:10.1109/ccnc.2010.5421584
dblp:conf/ccnc/ChenJR10
fatcat:edrpu35b2bhylah7hkuzljwchy
A Massive Multilevel-parallel Microscopic Traffic Simulator with Gridlock Detection and Solving
2013
Studies in Informatics and Control
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Also, route restrictions can lead to gridlocks, a common problem in such simulations. In this paper, we propose a multi-level parallel architecture for the TrafficWeb microscopic traffic simulator. ...
This allows simulating metropolitan traffic 85 times faster than in real time. ...
for realistic multi-lane traffic flows. ...
doi:10.24846/v22i3y201304
fatcat:fh63b45auba6dbmawnx4mw64y4
CatCharger: Deploying wireless charging lanes in a metropolitan road network through categorization and clustering of vehicle traffic
2017
IEEE INFOCOM 2017 - IEEE Conference on Computer Communications
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It however brings up a challenge: how to deploy charging lanes in a metropolitan road network to minimize the deployment cost while enabling EVs' continuous operability. ...
From a metropolitan-scale dataset collected from multiple sources of vehicles, we observe the diversity of vehicle passing speed and daily visit frequency (called traffic attributes) at intersections ( ...
Then, the charging lane has the shortest length that can fully charge passing EVs.
2) Vehicle Visit Frequency and Multi-source Vehicle Traffic Matter: To keep the EVs operable at any location in the ...
doi:10.1109/infocom.2017.8057019
dblp:conf/infocom/YanSZXLQ17
fatcat:te4dvi6febgbhgsebjhlsyr2ji
Theory and Experiment of Cooperative Control at Multi-Intersections in Intelligent Connected Vehicle Environment: Review and Perspectives
2022
Sustainability
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control mechanism and multi-intersection coordinated control strategy for intelligent connected vehicle heterogeneous traffic flow. ...
A heterogeneous traffic flow consists of regular vehicles, and intelligent connected vehicles having interactive functions is updating the composition of the current urban-road network traffic flow. ...
Based on the traffic data of multiple road sections in a road network area, Zhang Yi's team at Tsinghua University clustered the traffic data into related clusters, using a self-organizing maps (SOMs) ...
doi:10.3390/su14031542
fatcat:byylecdzbfayve3lleqbid2nq4
Online Traffic Accident Spatial-Temporal Post-Impact Prediction Model on Highways Based on Spiking Neural Networks
2021
Journal of Advanced Transportation
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This work is the introduction of SNNs in the traffic accident prediction domain and also a complete description of post-impact in the whole accident lifetime. ...
To this end, we build a 3-stage TAPIP model on highways, using the technology of spiking neural networks (SNNs) and convolutional neural networks (CNNs). ...
Acknowledgments is work was supported in part by the NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization (U1709212) and "Research on frontiers of intelligent transport ...
doi:10.1155/2021/9290921
fatcat:bj636fo255etlhfezo3iqln6we
Modeling vanet deployment in urban settings
2007
Proceedings of the 10th ACM Symposium on Modeling, analysis, and simulation of wireless and mobile systems - MSWiM '07
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The VANET performance appears to be only marginally affected by the simulation of multiple lanes and careful synchronization at traffic signals. ...
The growing interest in wireless Vehicular Ad Hoc Networks (VANETs) has prompted greater research into simulation models that better reflect urban VANET deployments. ...
In particular, four variants of TLM can be obtained by enabling or disabling the accelerationdeceleration and multi-lane features. ...
doi:10.1145/1298126.1298154
dblp:conf/mswim/MahajanPGW07
fatcat:x2ykw5tmijg55fficgkomzcy7u
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