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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