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Transit Vehicle Stopping Regimes and Spacings

Author

Listed:
  • Shinya Kikuchi

    (University of Delaware, Newark, Delaware)

  • Vukan R. Vuchic

    (University of Pennsylvania, Philadelphia, Pennsylvania)

Abstract

This study analyzes the optimum number of stops and the optimal vehicle stopping policy for operation of a transit route. Two optimality objectives are considered: minimum user travel time and minimum total cost (user cost plus vehicle operating cost). Three types of vehicle stopping schemes are incorporated in the model: all-stop, on-call stopping and demand stopping. These represent most of the existing fixed route transit stopping schemes. This study further identifies factors which influence the optimum number of stops and the stopping scheme. The sensitivities of the optima to the selected factors (passenger volume, headway, vehicle capacity and access speed) are examined. It is seen that the optimum number of stops is a function of the number of passengers for a one-way vehicle trip; for small passenger volume, the optimum number of stops is large; for large passenger volume, the number of stops decreases and approaches a constant value. Accordingly, the optimal stopping scheme changes from demand, to on-call and finally to all-stop operation. This study provides a theoretical basis for the selection for transit stopping policy and the number of stops under different operating conditions.

Suggested Citation

  • Shinya Kikuchi & Vukan R. Vuchic, 1982. "Transit Vehicle Stopping Regimes and Spacings," Transportation Science, INFORMS, vol. 16(3), pages 311-331, August.
    • Handle: RePEc:inm:ortrsc:v:16:y:1982:i:3:p:311-331
    DOI: 10.1287/trsc.16.3.311
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    Citations

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    Cited by:

    1. Tirachini, Alejandro, 2014. "The economics and engineering of bus stops: Spacing, design and congestion," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 37-57.
    2. Parbo, Jens & Nielsen, Otto A. & Prato, Carlo G., 2018. "Reducing passengers’ travel time by optimising stopping patterns in a large-scale network: A case-study in the Copenhagen Region," Transportation Research Part A: Policy and Practice, Elsevier, vol. 113(C), pages 197-212.
    3. Chen, Jingxu & Liu, Zhiyuan & Zhu, Senlai & Wang, Wei, 2015. "Design of limited-stop bus service with capacity constraint and stochastic travel time," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 83(C), pages 1-15.
    4. Jens Parbo & Otto Anker Nielsen & Carlo Giacomo Prato, 2016. "Passenger Perspectives in Railway Timetabling: A Literature Review," Transport Reviews, Taylor & Francis Journals, vol. 36(4), pages 500-526, July.
    5. Luigi Moccia & Duncan W. Allen & Eric C. Bruun, 2018. "A technology selection and design model of a semi-rapid transit line," Public Transport, Springer, vol. 10(3), pages 455-497, December.
    6. Lehe, Lewis J. & Pandey, Ayush, 2024. "A bathtub model of transit congestion," Transportation Research Part B: Methodological, Elsevier, vol. 181(C).
    7. Mohammad Sadrani & Ahmad Reza Jafarian-Moghaddam & Mohsen Aboutalebi Esfahani & Amir Masoud Rahimi, 2023. "Designing limited-stop bus services for minimizing operator and user costs under crowding conditions," Public Transport, Springer, vol. 15(1), pages 97-128, March.
    8. Mishra, Sushreeta & Mehran, Babak & Sahu, Prasanta K., 2020. "Assessment of delivery models for semi-flexible transit operation in low-demand conditions," Transport Policy, Elsevier, vol. 99(C), pages 275-287.
    9. Samanta, Sutapa & Jha, Manoj K., 2011. "Modeling a rail transit alignment considering different objectives," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(1), pages 31-45, January.

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