GreenSwirl: Combining Traffic Signal Control and Route Guidance for Reducing Traffic Congestion

被引:0
|
作者
Xu, Jiaxing [1 ]
Sun, Weihua [2 ]
Shibata, Naoki [1 ]
Ito, Minoru [1 ]
机构
[1] Nara Inst Sci & Technol, 8916-5 Takayama, Ikoma City, Nara, Japan
[2] Shiga Univ, Banba, Hikone 5228522, Japan
关键词
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Serious traffic congestion is a major social problem in large cities. Inefficient setting of traffic signal cycles, especially, is one of the main causes of congestion. GreenWave is a method for controlling traffic signals which allows one-way traffic to pass through a series of intersections without being stopped by a red light. GreenWave was tested in several cities around the world, but the results were not satisfactory. Two of the problems with GreenWave are that it still stops the crossing traffic, and it forms congestion in the traffic turning into or out of the crossing streets. To solve these problems, we propose a method of controlling traffic signals, GreenSwirl, in combination with a route guidance method, GreenDrive. GreenSwirl controls traffic signals to enable a smooth flow of traffic through signals times to turn green in succession and through non-stop circular routes through the city. The GreenWave technology is extended thereby. We also use navigation systems to optimize the overall control of the city ' s traffic. We did a simulation using the traffic simulator SUMO and the road network of Manhattan Island in New York. We confirmed that our method shortens the average travel time by 10%-60%, even when not all cars on the road are equipped to use this system.
引用
收藏
页数:8
相关论文
共 50 条
  • [11] Combined traffic signal control and route guidance: Multiple User Class Traffic Assignment Model versus Discrete Choice Model
    Yang, Zhaosheng
    Lu, Shoufeng
    Liu, Ximin
    [J]. 2006 IMACS: MULTICONFERENCE ON COMPUTATIONAL ENGINEERING IN SYSTEMS APPLICATIONS, VOLS 1 AND 2, 2006, : 1957 - +
  • [12] Traffic and congestion control
    [J]. Technical Report: Ser. Electrical Engineering, 1993, (EE02):
  • [13] Visualization of Traffic Bottlenecks: Combining Traffic Congestion with Complicated Crossings
    Keler, Andreas
    Krisp, Jukka M.
    Ding, Linfang
    [J]. ADVANCES IN CARTOGRAPHY AND GISCIENCE, 2017, : 493 - 505
  • [14] Reducing a congestion with introduce the greedy algorithm on traffic light control
    Siswipraptini, Puji Catur
    Martono, Wisnu Hendro
    Hartanti, Dian
    [J]. INTERNATIONAL CONFERENCE ON MATHEMATICS: PURE, APPLIED AND COMPUTATION, 2018, 974
  • [15] Based on hybrid genetic algorithm and cellular automata combined traffic signal control and route guidance
    Lu Shoufeng
    Liu Ximin
    [J]. PROCEEDINGS OF THE 26TH CHINESE CONTROL CONFERENCE, VOL 6, 2007, : 53 - +
  • [16] Optimal Traffic Signal Control for Alleviation of Congestion based on Traffic Density Prediction by Model Predictive Control
    Nakanishi, Hiroaki
    Namerikawa, Toru
    [J]. 2016 55TH ANNUAL CONFERENCE OF THE SOCIETY OF INSTRUMENT AND CONTROL ENGINEERS OF JAPAN (SICE), 2016, : 1273 - 1278
  • [17] PersianGulf: An Autonomous Combined Traffic Signal Controller and Route Guidance System
    Khanjary, Mohammad
    Faez, Karim
    Meybodi, Mohammad Reza
    Sabaei, Masoud
    [J]. 2011 IEEE VEHICULAR TECHNOLOGY CONFERENCE (VTC FALL), 2011,
  • [18] Combined control and route assignment in traffic signal networks
    Gartner, NH
    Al-Malik, M
    [J]. TRANSPORTATION SYSTEMS 1997, VOLS 1-3, 1997, : 615 - 620
  • [19] INDIVIDUAL DRIVER ROUTE GUIDANCE SYSTEMS AND THEIR IMPLICATIONS FOR TRAFFIC CONTROL
    VANAERDE, M
    CASE, ER
    [J]. CANADIAN JOURNAL OF CIVIL ENGINEERING, 1988, 15 (02) : 152 - 156
  • [20] Review of models combining traffic assignment and signal control
    Meneguzzer, C
    [J]. JOURNAL OF TRANSPORTATION ENGINEERING-ASCE, 1997, 123 (02): : 148 - 155