research-article

Dynamic highway congestion detection and prediction based on shock waves

Authors:

Soyoung AhnAuthors Info & Claims

VANET '10: Proceedings of the seventh ACM international workshop on VehiculAr InterNETworking

Pages 11 - 20

https://doi.org/10.1145/1860058.1860061

Published: 24 September 2010 Publication History

Abstract

Existing highway traffic monitoring system requires to deploy a large number of sensors and video cameras to detect traffic congestions, which is costly and prone to errors and failures [1]. In this paper, we present a distributed traffic detection and prediction solution by using shock wave traffic model. We develop a Hello protocol to maintain the vehicle sequence on the same lane. Based on the measurements of velocity and distance between immediate leading and following vehicles, a vehicle can detect and compute shock wave velocity incurred by vehicle merges or obstacles on the highway. When velocity changes occur continuously, congestions will be formed, which can be detected and predicted by the vehicles through a shock wave detection procedure. Our solution is effective since we only require vehicles to communicate with its neighboring vehicles within its wireless communication range.

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Cited By

Dong SZhang HLi SJia NHe N(2024)A Study on Urban Traffic Congestion Pressure Based on CFDSustainability10.3390/su16241091116:24(10911)Online publication date: 12-Dec-2024
https://doi.org/10.3390/su162410911
Cao ZZhao DSong HYuan HWang QMa HTong JTan C(2024) F 3 VeTrac: Enabling Fine-grained, Fully-road-covered, and Fully-individual penetrative Vehicle Trajectory Recovery IEEE Transactions on Mobile Computing10.1109/TMC.2023.3301871(1-16)Online publication date: 2024
https://doi.org/10.1109/TMC.2023.3301871
Abdel-Halim IFahmy H(2021)Mobility Prediction in Vehicular Ad-Hoc Networks: Prediction Aims, Techniques, Use Cases, and Research ChallengesIEEE Intelligent Transportation Systems Magazine10.1109/MITS.2018.288970813:2(105-126)Online publication date: Oct-2022
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Index Terms

Dynamic highway congestion detection and prediction based on shock waves
1. Information systems
  1. World Wide Web
    1. Web applications
      1. Internet communications tools
2. Software and its engineering
  1. Software organization and properties
    1. Software system structures
      1. Distributed systems organizing principles
        Organizing principles for web applications

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Published In

cover image ACM Conferences

VANET '10: Proceedings of the seventh ACM international workshop on VehiculAr InterNETworking

September 2010

106 pages

ISBN:9781450301459

DOI:10.1145/1860058

General Chairs:
Timo Kosch
BMW, Germany
,
Andre Weimerskirch
escrypt Inc., USA
,
Program Chairs:
Marc Torrent-Moreno
Barcelona Digital Centre Tecnològic, Spain
,
Marco Gruteser
Rutgers University, USA

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing

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Association for Computing Machinery

New York, NY, United States

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Published: 24 September 2010

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MobiCom/MobiHoc '10

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SIGMOBILE

MobiCom/MobiHoc '10: The 16th Annual International Conference on Mobile Computing and Networking and The 11th ACM International Symposium on Mobile Ad Hoc Networking and Computing

September 24, 2010

Illinois, Chicago, USA

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Overall Acceptance Rate 26 of 64 submissions, 41%

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Cited By

Dong SZhang HLi SJia NHe N(2024)A Study on Urban Traffic Congestion Pressure Based on CFDSustainability10.3390/su16241091116:24(10911)Online publication date: 12-Dec-2024
https://doi.org/10.3390/su162410911
Cao ZZhao DSong HYuan HWang QMa HTong JTan C(2024) F 3 VeTrac: Enabling Fine-grained, Fully-road-covered, and Fully-individual penetrative Vehicle Trajectory Recovery IEEE Transactions on Mobile Computing10.1109/TMC.2023.3301871(1-16)Online publication date: 2024
https://doi.org/10.1109/TMC.2023.3301871
Abdel-Halim IFahmy H(2021)Mobility Prediction in Vehicular Ad-Hoc Networks: Prediction Aims, Techniques, Use Cases, and Research ChallengesIEEE Intelligent Transportation Systems Magazine10.1109/MITS.2018.288970813:2(105-126)Online publication date: Oct-2022
https://doi.org/10.1109/MITS.2018.2889708
Yang YXie XFang ZZhang FWang YZhang D(2020)VeMo: Enabling Transparent Vehicular Mobility Modeling at Individual Levels with Full PenetrationIEEE Transactions on Mobile Computing10.1109/TMC.2020.3044244(1-1)Online publication date: 2020
https://doi.org/10.1109/TMC.2020.3044244
Yang YXie XFang ZZhang FWang YZhang DAgarwal SGreenstein BBalasubramanian AGollakota SZhang X(2019)VeMoThe 25th Annual International Conference on Mobile Computing and Networking10.1145/3300061.3300130(1-16)Online publication date: 5-Aug-2019
https://dl.acm.org/doi/10.1145/3300061.3300130
Popescu OSha-Mohammad SAbdel-Wahab HPopescu DEl-Tawab S(2017)Automatic Incident Detection in Intelligent Transportation Systems Using Aggregation of Traffic Parameters Collected Through V2I CommunicationsIEEE Intelligent Transportation Systems Magazine10.1109/MITS.2017.26665789:2(64-75)Online publication date: Oct-2018
https://doi.org/10.1109/MITS.2017.2666578
Sha-Mohammed SPopescu DAbdel-Wahab H(2015)A new technique for automatic incident detection in intelligent transportation systems using aggregation of traffic parameters2015 IEEE Wireless Communications and Networking Conference (WCNC)10.1109/WCNC.2015.7127799(2144-2148)Online publication date: Mar-2015
https://doi.org/10.1109/WCNC.2015.7127799
Morino HInafune TWatanabe T(2015)Assisting solution of traffic congestion at sags using inter-vehicle communication with heterogeneous wireless systems2015 IEEE Vehicular Networking Conference (VNC)10.1109/VNC.2015.7385575(183-189)Online publication date: Dec-2015
https://doi.org/10.1109/VNC.2015.7385575
Bani Younes MBoukerche A(2015)A performance evaluation of an efficient traffic congestion detection protocol (ECODE) for intelligent transportation systemsAd Hoc Networks10.1016/j.adhoc.2014.09.00524:PA(317-336)Online publication date: 1-Jan-2015
https://dl.acm.org/doi/10.1016/j.adhoc.2014.09.005
Mian AFatima IBeraldi R(2013)Traffic Density Estimation Protocol Using Vehicular NetworksMobile and Ubiquitous Systems: Computing, Networking, and Services10.1007/978-3-642-40238-8_1(1-12)Online publication date: 2013
https://doi.org/10.1007/978-3-642-40238-8_1
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