Online Scheduling and Route Planning for Shared Buses in Urban Traffic Networks

Zhaolong Ning, Shouming Sun, Meng Chu Zhou, Xiping Hu, Xiaojie Wang, Lei Guo, Bin Hu, Ricky Y.K. Kwok

Research output: Contribution to journalArticlepeer-review

Abstract

It is critical to reduce the operating cost of shared buses for bus companies and improve the user experience of passengers. However, existing studies focus on either bus scheduling or route planning, which cannot accomplish the above mentioned goals concurrently. In this paper, we construct a joint bus scheduling and route planning framework to maximize the number of passengers, minimize the total length of routes and the number of required buses, as well as guarantee good user experience of passengers. First, we establish a system model based on a real-world scenario and formulate a multi-objective combinational optimization problem. Then, based on the extracted traffic topology of urban traffic networks and the generated candidate line set, we propose an offline algorithm to cope with the similar passenger flow distributions, e.g., morning or evening peak of every day. In order to cope with dynamic real-time passenger flows, an online algorithm is designed. Experiments are carried out based on real-word scenarios. The results show that the proposed algorithms can greatly reduce the operating cost of bus companies and guarantee good user experience based on real-world scheduling data in comparison with several existing methods.

Original languageEnglish (US)
JournalIEEE Transactions on Intelligent Transportation Systems
DOIs
StateAccepted/In press - 2021

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

Keywords

  • Companies
  • Dynamic scheduling
  • Heuristic algorithms
  • Optimization
  • Schedules
  • Shared bus
  • User experience
  • Vehicle dynamics
  • bus scheduling
  • last mile
  • multi-objective optimization.
  • route planning

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