Using GPS Trajectories to Adaptively Plan Bus Lanes

被引:3
|
作者
Sun, Yanjie [1 ,2 ]
Wu, Mingguang [1 ,2 ,3 ,4 ]
Li, Huien [5 ]
机构
[1] Nanjing Normal Univ, Key Lab Virtual Geog Environm, Minist Educ, Nanjing 210023, Jiangsu, Peoples R China
[2] Nanjing Normal Univ, Coll Geog Sci, Nanjing 210023, Jiangsu, Peoples R China
[3] State Key Lab Cultivat Base Geog Environm Evolut, Nanjing 210023, Jiangsu, Peoples R China
[4] Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China
[5] Jiangsu Inst Geog Informat Ind, Nanjing 210023, Jiangsu, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2021年 / 11卷 / 03期
基金
中国国家自然科学基金;
关键词
traffic congestion; bus lane planning; GPS trajectory; multiobjective optimization;
D O I
10.3390/app11031035
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Since bus prioritization policies can help mitigate urban traffic jams, the planning of bus lanes has drawn considerable attention. Existing methods suffer from a common limitation, which is that the limited spatial adaptability resulting from certain road condition information cannot be directly specified. Many bus GPS trajectories have been accumulated and can be contiguously gathered if needed. This paper proposes a trajectory-based bus lane planning method. First, we formulize the bus lane planning problem as a multiobjective optimization problem in which the road conditions, traffic flow, connectivity of bus lanes, and construction cost are organized as four constraints, and road utilization and bus punctuality are modeled as two objectives. Then, an evolutionary algorithm-based method is presented to solve the problem. We tested the model in the Nanshan District, Shenzhen City, China. Through a comparison with existing survey-based methods, the parameters associated with road conditions in this method are directly extracted from GPS trajectories, and this method is more effectively deployed than other methods. Since GPS trajectories can cover a wide area if needed, and because the proposed method can be effectively executed, this method can be adapted to large urban scales.
引用
收藏
页码:1 / 16
页数:16
相关论文
共 50 条
  • [1] Mining Bus Stops from Raw GPS Data of Bus Trajectories
    Garg, Nandani
    Ramadurai, Gitakrishnan
    Ranu, Sayan
    [J]. 2018 10TH INTERNATIONAL CONFERENCE ON COMMUNICATION SYSTEMS & NETWORKS (COMSNETS), 2018, : 583 - 588
  • [2] Unblock the bus lanes
    Blakeley, B
    [J]. PROFESSIONAL ENGINEERING, 2001, 14 (18) : 19 - 19
  • [3] BUS LANES IN LONDON
    RIDLEY, G
    RUSHTON, P
    CRACKNEL.JA
    [J]. HIGHWAY ENGINEER, 1973, 20 (07): : 8 - 30
  • [4] BUS LANES IN CAIRO
    ELREEDY, TY
    ELHAWARY, MA
    [J]. HIGHWAY ENGINEER, 1981, 28 (06): : 2 - 9
  • [5] Learning GPS Point Representations to Detect Anomalous Bus Trajectories
    Cruz, Michael
    Barbosa, Luciano
    [J]. IEEE ACCESS, 2020, 8 : 229006 - 229017
  • [6] Integrated Analysis of Toll Lanes and Bus Priority Lanes
    Kim, Dongwook
    Schonfeld, Paul
    [J]. TRANSPORTATION RESEARCH RECORD, 2008, 2076 (2076) : 70 - 80
  • [8] BUS LANES - THEIR PROBLEMS AND ADVANTAGES
    HUDDART, KW
    [J]. HIGHWAY ENGINEER, 1976, 23 (07): : 19 - 28
  • [9] Widening the scope for bus priority with intermittent bus lanes
    Viegas, J
    Lu, BC
    [J]. TRANSPORTATION PLANNING AND TECHNOLOGY, 2001, 24 (02) : 87 - 110
  • [10] Detection and classification of highway lanes using vehicle motion trajectories
    Melo, Jose
    Naftel, Andrew
    Bernardino, Alexandre
    Santos-Victor, Jose
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2006, 7 (02) : 188 - 200