Effect of using route information sharing to reduce traffic congestion

被引:0
|
作者
Yamashita, T [1 ]
Izumi, K [1 ]
Kurumatani, K [1 ]
机构
[1] AIST, CARC, Koto Ku, Tokyo 1350064, Japan
来源
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this research, our aim is to increase the utility of road transportation systems by reducing traffic congestion for the benefit of both individuals and society as a whole. To attain our purpose, we propose a simple route guidance mechanism based on mass user support. Through multiagent simulation, we examine the ability of our proposed mechanism for improving traffic efficiency of both individual drivers and whole systems. Our simulation results that i) our proposed mechanism improves efficiency for the drivers who use it and the entire transportation system, and ii) the social dilemmas in route choice behaviors occur in a radial and ring network.
引用
收藏
页码:86 / 104
页数:19
相关论文
共 50 条
  • [21] Dynamic information sharing using a distributed traffic surveillance infrastructure
    Zhang, Ying
    Huang, Qingfeng
    2007 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE, VOLS 1 AND 2, 2007, : 222 - 227
  • [22] Staggered working hours in order to reduce traffic congestion
    Mutlu, Ozcan
    Durak, Zehra
    Akyer, Hasan
    PAMUKKALE UNIVERSITY JOURNAL OF ENGINEERING SCIENCES-PAMUKKALE UNIVERSITESI MUHENDISLIK BILIMLERI DERGISI, 2020, 26 (04): : 730 - 736
  • [23] A route choice model with traffic information using fuzzy logic
    Zhu, Z
    Wang, W
    Qu, DY
    TRAFFIC AND TRANSPORTATION STUDIES, VOLS 1 AND 2, PROCEEDINGS, 2002, : 953 - 958
  • [24] Using stated preference data for studying the effect of advanced traffic information on drivers' route choice
    AbdelAty, MA
    Kitamura, R
    Jovanis, PP
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 1997, 5 (01) : 39 - 50
  • [25] Dynamic Vehicular Route Guidance Using Traffic Prediction Information
    Kim, Kwangsoo
    Kwon, Minseok
    Park, Jaegeun
    Eun, Yongsoon
    MOBILE INFORMATION SYSTEMS, 2016, 2016 : 1 - 11
  • [26] GreenSwirl: Combining Traffic Signal Control and Route Guidance for Reducing Traffic Congestion
    Xu, Jiaxing
    Sun, Weihua
    Shibata, Naoki
    Ito, Minoru
    2014 IEEE VEHICULAR NETWORKING CONFERENCE (VNC), 2014,
  • [27] Understanding the Effect of Traffic Congestion on Accidents Using Big Data
    Sanchez Gonzalez, Santiago
    Bedoya-Maya, Felipe
    Calatayud, Agustina
    SUSTAINABILITY, 2021, 13 (13)
  • [28] Analyzing the Cascading Effect of Traffic Congestion Using LSTM Networks
    Basak, Sanchita
    Dubey, Abhishek
    Bruno, Leao
    2019 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2019, : 2144 - 2153
  • [29] A Unified Framework for Vehicle Rerouting and Traffic Light Control to Reduce Traffic Congestion
    Cao, Zhiguang
    Jiang, Siwei
    Zhang, Jie
    Guo, Hongliang
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2017, 18 (07) : 1958 - 1973
  • [30] Effective information provision for relieving traffic congestion
    Shiose, T
    Onitsuka, T
    Taura, T
    ICCIMA 2001: FOURTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND MULTIMEDIA APPLICATIONS, PROCEEDINGS, 2001, : 138 - 142