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Optimizing On-Demand Bus Services for Remote Areas

Author

Listed:
  • Xudong Li

    (Faculty of Maritime and Transportation, Ningbo University, Ningbo 315000, China)

  • Zhongzhen Yang

    (Faculty of Maritime and Transportation, Ningbo University, Ningbo 315000, China)

  • Feng Lian

    (Faculty of Maritime and Transportation, Ningbo University, Ningbo 315000, China)

Abstract

This study proposes on-demand bus services for remote areas with low transit demand, incorporating travelers’ willingness to pay and values of time. To jointly optimize the on-demand service of overlapping bus routes, we construct a bi-level model. The upper-level model (UM) optimizes bus departure frequency in different time windows and ticket prices of on-demand services to minimize the total generalized cost, subject to travelers’ willingness to pay for on-demand services. The lower-level model (LM) calculates the probability of travelers choosing on-demand stops. A numerical analysis based on Meishan Island data in Ningbo indicates that with on-demand bus services, the total generalized cost incurred by buses and travelers can be reduced by 30.36% and 15.35% during rush and off-rush hours, respectively. Additionally, the waiting time at an on-demand bus stop is only 4.3 min during rush hours and 6.8 min during off-rush hours.

Suggested Citation

  • Xudong Li & Zhongzhen Yang & Feng Lian, 2023. "Optimizing On-Demand Bus Services for Remote Areas," Sustainability, MDPI, vol. 15(9), pages 1-20, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:9:p:7264-:d:1134116
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