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Zero bunching solution for a local public transport system with multiple-origins bus operation

Author

Listed:
  • S. Sajikumar

    (Government Polytechnic College)

  • D. Bijulal

    (Government Engineering College)

Abstract

Bus bunching in public transport is the concentration of similar buses having different schedules to a common time point. The reason for this phenomenon is variations existing in the bus operation as earliness and lateness. Bus bunching has the consequence of reduced service reliability concerning both passengers and operators. A zero bunching state is vital for enhancing the usage of public transport where the buses operate with utmost schedule adherence. Two generally adopted strategies for solving bus bunching are a schedule-based strategy which provides slack time in a timetable to address late running and fixed departure time for the early operations, and a headway-based strategy that maintains headway between buses. Bus bunching due to multiple origins is a special case in which common tactics cannot effectively control a bunching tendency that arises at the entry point. The operation schedules of multiple origins must be so designed that a state of zero bus bunching can be ensured while buses from different origins reach the entry points. This article presents a model of a multiple-origins public transport network as a combination of origins, routes and entry points, developed in the search for achieving a zero bunching state in the operation beyond an entry point. The origins are modelled based on the entry-point variables. The routes are modelled based on the running time, departure time, arrival time, and dwell time. The entry points are modelled based on route and entry-point variables. Redesigning route schedules based on the entry-point characteristics and an appropriate slack time implementation are proposed and observed to be suitable for overcoming bunching in a multiple-origins bus operation.

Suggested Citation

  • S. Sajikumar & D. Bijulal, 2022. "Zero bunching solution for a local public transport system with multiple-origins bus operation," Public Transport, Springer, vol. 14(3), pages 655-681, October.
    • Handle: RePEc:spr:pubtra:v:14:y:2022:i:3:d:10.1007_s12469-021-00273-1
    DOI: 10.1007/s12469-021-00273-1
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    References listed on IDEAS

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    Cited by:

    1. Stefan Voß, 2023. "Bus Bunching and Bus Bridging: What Can We Learn from Generative AI Tools like ChatGPT?," Sustainability, MDPI, vol. 15(12), pages 1-19, June.

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