Volume 39 Issue 4
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Article Navigation >  Journal of Transport Information and Safety  > 2021  >  39(4): 143-150
WEN Dong, ZHANG Mengmeng. A Hierarchical Spatiotemporal Optimization Model of Customized Bus Routes Considering Time Windows[J]. Journal of Transport Information and Safety, 2021, 39(4): 143-150. doi: 10.3963/j.jssn.1674-4861.2021.04.018
Citation: WEN Dong, ZHANG Mengmeng. A Hierarchical Spatiotemporal Optimization Model of Customized Bus Routes Considering Time Windows[J]. Journal of Transport Information and Safety, 2021, 39(4): 143-150. doi: 10.3963/j.jssn.1674-4861.2021.04.018
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A Hierarchical Spatiotemporal Optimization Model of Customized Bus Routes Considering Time Windows

doi: 10.3963/j.jssn.1674-4861.2021.04.018

  • School of Transportation and Logistics Engineering, Shandong Jiaotong University, Jinan 250357, China

  • Received Date: 2021-02-04
    Abstract
  • Studying the layout and scheduling optimization of a customized bus line network has important implications, enhancing the attractiveness of the public transport system and passenger travel. However, the distribution of customized bus passengers' demand points in time and space is discrete, which hinders the bus line design. A timespace hierarchical optimization model of customized buses considering time windows is constructed to solve this problem, and a genetic algorithm is designed to solve the model. The hot spots of demand points are identified in time and space by analyzing the fishing net and kernel density, with the cluster analysis of hot spots and the classification of bus pooling realized. Based on the set of bus pooling, a space optimization model of bus lines is constructed by the bus capacity, line length, and passenger travel distance. A time optimization model of bus lines is constructed by the minimum time cost of passengers. Jinan customized bused are used to evaluate the performance of the model. The results show that the routing scheme is optimized by the model, with an average service coverage rate of passengers of 96%, the average travel time saved by the single passenger in each period of the service area of 15 minutes, and an average load factor of public transport of 90%.

     

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    • References(19)
  • [1]
    HARMS S, TRUFFER B. The emergence of a nationwide carsharing coperative in Switzerland[R]. Holland: University of Twente, 1998.
    [2]
    TSUBOUCHI K, YAMATO H, HIEKATA K. Innovative on-demand bus system in Japan[J]. IET Intelligent Transport Systems, 2010, 4(4): 270-279. doi: 10.1049/iet-its.2009.0113
    [3]
    NEVEN A, BRAEKERS K, DECLERCQ K, et al. Assessing the impact of different policy decisions on the resource requirements of a demand responsive transport system for persons with Disabilities[J]. Transport Policy, 2015(44): 48-57. http://www.sciencedirect.com/science/article/pii/S0967070X15300305
    [4]
    FENG Q, LI W, JIAn Z. A dynamic station strategy to improve the performance of flex-route transit services[J]. Transportation Research Part C: Emerging Technologies, 2014, 48(12): 229-240. http://www.onacademic.com/detail/journal_1000036711989510_362a.html
    [5]
    CHANG S K, YU W J. Comparison of subsidized fixed and flexible-route bus systems[J]. Transportation Research Record, 1996(1557): 15-20.
    [6]
    郭戎格. 基于IC卡数据的定制公交线路优化[D]. 北京: 北京交通大学, 2017.

    GUO Rongge. Optimal routing design of customized bus based on bus ic data[D]. Beijing: Beijing Jiao Tong University, 2017. (in Chinese).
    [7]
    张鹤鹏. 基于GPS定位数据的出行行为研究[D]. 北京: 北京交通大学, 2019.

    ZHANG Hepeng. Study on the travel behavior based on GPSdata[D]. Beijing: Beijing Jiao Tong University, 2019. (in Chinese).
    [8]
    陈亚玲. 基于出租车GPS轨迹数据的公交路线优化[D]. 绵阳: 西南科技大学, 2019.

    CHEN Yaling. bus route optimization based on taxi gps trajectory data[D]. Mianyang: Southwest University of Science and Technology, 2019. (in Chinese).
    [9]
    曾勋. 基于IC卡和GPS数据的公交服务能力评估[D]. 西安: 长安大学, 2019.

    ZENG Xun. Bus service capacity assessm entbased on IC card and GPS data[D]. Xi'an: Chang'an University, 2019. (in Chinese).
    [10]
    杨敬锋, 张南峰, 杨骥, 等. 基于公交站群的定制公交出行需求热力图分析模型[C]. 第5届中国卫星导航与位置服务年会暨展览会, 成都: 中国卫星导航定位协会, 2016. YANG Jingfeng, ZHANG Nanfeng, Yang Ji, et al. Thermal graph analysis model of customized bus travel demand based on bus station group[C]. 5thGNSS and LBS Annual Conference & amp; Exhibition, Chengdu: GNSS & amp; LBS Association of China, 2016. (in Chinese).
    [11]
    李莎. 定制公交线网的建模与智能优化算法研究[D]. 广州: 华南理工大学, 2017.

    LI Sha. A Dissertation submithed for the degree of master[D]. Guangzhou: South China University of Technology, 2017. (in Chinese).
    [12]
    靳文舟, 韩博文, 郝小妮, 等. 基于小波神经网络的定制公交目标乘客出行意愿预测[J]. 重庆交通大学学报(自然科学版), 2018, 37(8): 81-87. doi: 10.3969/j.issn.1674-0696.2018.08.14

    JIN Wenzhou, HAN Bowen, HAO Xiaoni, et al. Prediction of target passenger'travel intention of customized public transport based on wavelet neural network[J]. Journal of Chongqing Jiaotong University(Natural Science), 2018, 37(8): 81-87. (in Chinese). doi: 10.3969/j.issn.1674-0696.2018.08.14
    [13]
    LI Wenyong, YU Ziwei, WEI Shuo, et al. Custom bus optimization of docking stations based on partition path selection[J]. Advances in Mechanical Engineering, 2017, 9(10): 1-6. http://www.onacademic.com/detail/journal_1000040145143610_11c2.html
    [14]
    雷永巍, 林培群, 姚凯斌. 互联网定制公交的网络调度模型及其求解算法[J]. 交通运输系统工程与信息, 2017, 17(1): 157-163. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201701024.htm

    LEI Yongwei, LIN Peiqun, YAO Kaibin. The network scheduling model and its solution algorithm of internet customized shuttle bus[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(1): 157-163. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201701024.htm
    [15]
    李颖. 定制公交的决策与算法研究[D]. 南京: 南京林业大学, 2017.

    LI Ying. Research on custom public transport decision and algorithm[D]. Nanjing: Nanjing Forestry University, 2017. (in Chinese).
    [16]
    陶浪, 马昌喜, 朱昌锋, 等. 基于遗传算法的定制公交路线多目标优化[J]. 兰州交通大学学报, 2018, 37(2): 31-37. doi: 10.3969/j.issn.1001-4373.2018.02.006

    TAO Lang, MA Changxi, ZHU Changfeng, et al. Multiobjective optimization of customized bus routes based on genetic algorithm[J]. Journal of Lanzhou Jiaotong University, 2018, 37(2): 31-37. (in Chinese). doi: 10.3969/j.issn.1001-4373.2018.02.006
    [17]
    王健, 曹阳, 王运豪. 考虑出行时间窗的定制公交线路车辆调度方法[J]. 中国公路学报, 2018, 31(5): 143-150. doi: 10.3969/j.issn.1001-7372.2018.05.017

    WANG Jian, CAO Yang, WANG Yunhao. Customized bus route vehicle schedule method considering travel time windows[J]. China Journal of Highway and Transport, 2018, 31(5): 143-150. (in Chinese). doi: 10.3969/j.issn.1001-7372.2018.05.017
    [18]
    张宇宁, 武建平. 面向通勤需求的定制公交线路规划研究[J]. 黑龙江交通科技, 2019, 42(12): 147-148. doi: 10.3969/j.issn.1008-3383.2019.12.078

    ZHANG Yuning, WU Jianping. Research on customized bus route planning for commuting demand[J]. Communications Science and Technology Heilongjiang, 2019, 42(12): 147-148. (in Chinese). doi: 10.3969/j.issn.1008-3383.2019.12.078
    [19]
    陈汐, 王印海, 刘剑锋, 等. 多区域通勤定制公交线路规划模型及求解算法[J]. 交通运输系统工程与信息, 2020, 20(4): 166-172+186. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT202004024.htm

    CHEN Xi, WANG Yinhai, Liu Jianfeng, et al. Multi-region commuting bus route design model and solution method[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(4): 166-172+186. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT202004024.htm
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