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面向常发拥堵点的主动交通诱导方法

罗舒琳 张存保 张泰文 曹雨

罗舒琳, 张存保, 张泰文, 曹雨. 面向常发拥堵点的主动交通诱导方法[J]. 交通信息与安全, 2021, 39(5): 68-72. doi: 10.3963/j.jssn.1674-4861.2021.05.009
引用本文: 罗舒琳, 张存保, 张泰文, 曹雨. 面向常发拥堵点的主动交通诱导方法[J]. 交通信息与安全, 2021, 39(5): 68-72. doi: 10.3963/j.jssn.1674-4861.2021.05.009
LUO Shulin, ZHANG Cunbao, ZHANG Taiwen, CAO Yu. Active Traffic Guidance Method for Recurrent Congestion Points[J]. Journal of Transport Information and Safety, 2021, 39(5): 68-72. doi: 10.3963/j.jssn.1674-4861.2021.05.009
Citation: LUO Shulin, ZHANG Cunbao, ZHANG Taiwen, CAO Yu. Active Traffic Guidance Method for Recurrent Congestion Points[J]. Journal of Transport Information and Safety, 2021, 39(5): 68-72. doi: 10.3963/j.jssn.1674-4861.2021.05.009

面向常发拥堵点的主动交通诱导方法

doi: 10.3963/j.jssn.1674-4861.2021.05.009
基金项目: 

国家重点研发计划项目 2018YFB1601000

详细信息
    作者简介:

    罗舒琳(1995—),硕士研究生.研究方向:交通管理与控制. E-mail: 964230482@qq.com

    通讯作者:

    张存保(1976—),博士,研究员. 研究方向:交通信息工程及控制、交通安全. E-mail: zhangcunbao@163.com

  • 中图分类号: U491.4

Active Traffic Guidance Method for Recurrent Congestion Points

  • 摘要:

    基于动态用户均衡、系统最优分配的诱导方法,侧重路网需求的宏观预测和调节,难以准确辨识道路拥堵点的关联车流,制约了诱导效果。为精准调控致堵车流,有效缓解常发性拥堵,研究基于需求溯源的主动交通诱导方法。遵循靶向诱导的思路,分析车辆行驶轨迹和常发拥堵点的交通流关联性,运用卡尔曼滤波对关联车流进行短时预测,在此基础上,结合流量占比、路径饱和度等指标,对诱导目标车流进行优选。同时,从负荷均衡的角度出发,基于路段与路径交通流的时空关联更新路网交通状态,建立以饱和度均衡为目标的主动诱导优化模型。仿真结果表明:相比反应型诱导与基于路径偏好的主动型诱导,所提方法使常发拥堵点的车均延误、停车次数等下降30%~60%,路网车均延误、停车次数等下降10%~15%,模型收敛速度提高,交通效益提升,验证了该方法的有效性。

     

  • 图  1  基于需求溯源的主动交通诱导思路

    Figure  1.  Thoughtof active traffic guidance based on traceable demand

    图  2  拥堵点交通流溯源示意图

    Figure  2.  Schematic diagram of traffic flow traceability at congestion points

    图  3  无效路径示意图

    Figure  3.  Invalid path diagram

    图  4  路网结构示意图

    Figure  4.  Schematic diagram of road network structure

    图  5  交通运行状态对比图

    Figure  5.  Comparison diagram of traffic operation state

    图  6  诱导前后交通效益对比图

    Figure  6.  Comparison of traffic benefits before and after guidance

    图  7  主动型诱导运算效率对比

    Figure  7.  Comparison of active inducement operation efficiency

    表  1  路径交通流优先度输出值

    Table  1.   Traffic-guidance priority of traffic flow of paths

    路径交通流 xk, t yk, t zk, t Hk, t
    f2-7-8-17-18-23 0.43 0.34 0.76 0.54
    f6-14-15-16-17-18-19-20 0.73 0.82 1.00 0.87
    f14-15-16-17-18-19-20 0.92 1.00 0.00 0.00
    f15-16-17-18-19-20 1.00 0.57 0.00 0.00
    f21-14-15-16-17-18-19-20 0.71 0.65 0.23 0.50
    f22-16-17-18-19-20 0.76 0.73 0.47 0.64
    f26-22-16-17-18-19-20 0.64 0.81 0.62 0.68
    $ \vdots $ $ \vdots $ $ \vdots $ $ \vdots $ $ \vdots $
    下载: 导出CSV
  • [1] 李妍峰, 高自友, 李军. 基于实时交通信息的城市动态网络车辆路径优化问题[J]. 系统工程理论与实践, 2013, 33(7): 1813-1819. doi: 10.3969/j.issn.1000-6788.2013.07.022

    LI Yanfeng, GAO Ziyou, LI Jun. Urban dynamic network vehicle routing optimization based on real-time traffic information[J]. System Engineering Theory and Practice, 2013, 33(7): 1813-1819(in Chinese) doi: 10.3969/j.issn.1000-6788.2013.07.022
    [2] 邓卫, 李峻利. 高速公路常发性与偶发性交通拥挤的判别[J]. 东南大学学报, 1994(2): 60-65. https://www.cnki.com.cn/Article/CJFDTOTAL-DNDX402.009.htm

    DENG Wei, LI Junli. Discrimination between frequent and occasional traffic congestion on expressway[J]. Journal of Southeast University, 1994(2): 60-65(in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DNDX402.009.htm
    [3] SUN Huijun, WU Jianjun, MA Dan, et al. Spatial distribution complexities of traffic congestion and bottlenecks in different network topologies[J]. Applied Mathematical Modelling, 2014, 38(2): 496-505. (in Chinese) doi: 10.1016/j.apm.2013.06.027
    [4] WEN Huimin, SUN Jianping, ZHANG Xi. Study on traffic congestion patterns of large city in China taking Beijing as an example[J]. Procedia-Social and Behavioral Sciences, 2014(138): 482-491. http://www.sciencedirect.com/science/article/pii/S1877042814041469/pdf?md5=8046434a6e6d6c6c77c6e971355d0124&pid=1-s2.0-S1877042814041469-main.pdf
    [5] DEFLORIO F P. Evaluation of a reactive dynamic route guidance strategy[J]. Transportation Research Part C: Emerging Technologies, 2003, 11(5): 375-388. doi: 10.1016/S0968-090X(03)00031-7
    [6] ZHANG R, LI Z, FENG C, et al. Traffic routing guidance algorithm based on backpressure with a trade-off between user satisfaction and traffic load[C]. 2012 Vehicular Technology Conference(VTC Fall), Piscataway, NJ, USA: IEEE, 2012.
    [7] LIANG Z, WAKAHARA Y. Real-time urban traffic amount prediction models for dynamic route guidance systems[J]. Eurasip Journal on Wireless Communications & Networking, 2014(8): 1018-1030. doi: 10.1186/1687-1499-2014-85
    [8] JAVED M, ZEADALLY S. RepGuide: Reputation-based route guidance using internet of vehicles[J]. IEEE Communications Standards Magazine, 2019, 2(4): 81-87. http://www.researchgate.net/profile/Muhammad_Awais_Javed3/publication/328283722_RepGuide_Reputation-based_Route_Guidance_using_Internet_of_Vehicles/links/5bc483df299bf1004c5f8c0b/RepGuide-Reputation-based-Route-Guidance-using-Internet-of-Vehicles.pdf
    [9] FRIESZ T L, KIM T, KWON C, et al. Approximate network loading and dual-time-scale dynamic user equilibrium[J]. Transportation Research Part B: Methodological, 2011, 45(1): 176-207. doi: 10.1016/j.trb.2010.05.003
    [10] LONG Jiancheng, CHEN Jiaxu, SZETO W Y, et al. Link-based system optimum dynamic traffic assignment problems with environmental objectives[J]. Transportation Research Part D: Transport & Environment, 2016, 60(6): 56-75. http://www.sciencedirect.com/science/article/pii/S1361920916303248
    [11] DABBAS H, FOURATI W, FRIEDRICH B. Using floating car data in route choice modelling-field study[J]. Transportation Research Procedia, 2021(52): 700-707. http://www.sciencedirect.com/science/article/pii/S2352146521001307
    [12] BI Y C, LAM W, SUMALEE A, et al. Vulnerability analysis for large-scale and congested road networks with demand uncertainty[J]. Transportation Research Part A: Policy and Practice, 2012, 46(3): 501-516. doi: 10.1016/j.tra.2011.11.018
    [13] 张宏雨, 寇玮华. 基于消圈算法的拥挤网络流分流研究[J]. 交通运输工程与信息学报, 2017, 15(3): 84-92+99. doi: 10.3969/j.issn.1672-4747.2017.03.012

    ZHANG Hongyu, KOU Weihua. Research on congestion network flow diversion based on circle elimination algorithm[J]. Journal of transportation engineering and information, 2017, 15(3): 84-92+99(in Chinese) doi: 10.3969/j.issn.1672-4747.2017.03.012
    [14] 韩直, 徐冲聪, 韩嵩乔. 基于短时交通流预测的广域动态交通路径诱导方法[J]. 交通运输系统工程与信息, 2020, 20 (1): 117-123+129. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT202001020.htm

    HAN Zhi, XU Chongcong, HAN Songqiao. Wide-area dynamic traffic route guidance method based on short-term traffic flow prediction[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(1): 117-123+129 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT202001020.htm
    [15] 王福建, 龚成宇, 马东方, 等. 采用交通出行量数据的多点联动瓶颈控制方法[J]. 浙江大学学报(工学版), 2017, 51(2): 273-278. https://www.cnki.com.cn/Article/CJFDTOTAL-ZDZC201702007.htm

    WANG Fujian, GONG Chengyu, MA Dongfang, et al. Signal coordination control for traffic bottleneck using OD data[J]. Journal of Zhejiang University(Engineering Science), 2017, 51(2): 273-278(in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZDZC201702007.htm
    [16] 杨兆升, 朱中. 基于卡尔曼滤波理论的交通流量实时预测模型[J]. 中国公路学报, 1999, 12(3): 63-67. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL199903008.htm

    YANG Zhaosheng, ZHU Zhong. A real-time traffic volume prediction model based on the Kalman filtering theory[J]. China Journal of Highway and Transport, 1999, 12(3): 63-67. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL199903008.htm
    [17] 黄裕乔. 动态交通诱导信息时空发布策略研究[D]. 北京: 北京交通大学, 2012.

    HUANG Yuqiao. Research on spatio-temporal release strategy of dynamic traffic guidance information[D]. Beijing: Beijing Jiaotong University, 2012(in Chinese)
    [18] 陈芳, 张卫华, 丁恒, 等. 基于出行者路径选择行为的VMS诱导策略研究[J]. 系统工程理论与实践, 2018, 38(5): 1263-1276. https://www.cnki.com.cn/Article/CJFDTOTAL-XTLL201805016.htm

    CHEN Fang, ZHANG Weihua, DING Heng, et al. Research on VMS induction strategy based on traveler path selection behavior[J]. Systems Engineering-Theory & Practice, 2018, 38(5): 1263-1276. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XTLL201805016.htm
    [19] 陈彦如, 蒲云. 用遗传算法解决固定需求交通平衡分配问题[J]. 西南交通大学学报, 2000, 35(1): 44-47. doi: 10.3969/j.issn.0258-2724.2000.01.011

    CHEN Yanru, PU Yun. Solving traffic equilibrium assignment problem with genetic algorithm[J]. Journal of Southwest Jiaotong University, 2000, 35(1): 44-47. (in Chinese) doi: 10.3969/j.issn.0258-2724.2000.01.011
    [20] 杨扬, 姚恩建, 潘龙, 等. 基于GPS数据的出租车路径选择行为研究[J]. 交通运输系统工程与信息, 2015, 15(1): 81-86. doi: 10.3969/j.issn.1009-6744.2015.01.015

    YANG Yang, YAO Enjian, PAN Long, et al. Study on taxi route selection behavior based on GPS data[J]. Journal of Transportation Systems Engineering and Information Technology, 2015, 15(1): 81-86. (in Chinese) doi: 10.3969/j.issn.1009-6744.2015.01.015
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  • 收稿日期:  2021-05-08

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