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Simulation support tool for real-time dispatching control in public transport

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  • Adamski, Andrzej
  • Turnau, Andrzej

Abstract

In practice punctuality of transit service has been a chronic operational problem mainly due to the random environment and very high complexity of the public transport processes. This challenging problem affects both travellers (reliability of service) as well as operators (productivity and efficiency of resources utilization). The potential of new information and communication technologies and existing hardware possibilities offer great opportunities for the development of effective and flexible management and control tools for public transport. In this paper the simulation decision-support tool for dynamic optimal dispatching control purposes have been developed, with the use of the SIMULINK package with Toolboxes. The following optimal dispatching control problems have been solved: punctuality control (which compensates deviations from schedule), regularity control (which compensates deviations from regular headway) and synchronizing control with linear (LQ, dead-beat) feedback and control and system state constraints; LQG stochastic control with real-time estimation of the model parameters; and bus route zone control for synchronising passenger transfers or the operation of different lines on common segments of the route. The results presented are illustrated by 15 numerical examples.

Suggested Citation

  • Adamski, Andrzej & Turnau, Andrzej, 1998. "Simulation support tool for real-time dispatching control in public transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 32(2), pages 73-87, February.
    • Handle: RePEc:eee:transa:v:32:y:1998:i:2:p:73-87
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    References listed on IDEAS

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    Cited by:

    1. Sánchez-Martínez, G.E. & Koutsopoulos, H.N. & Wilson, N.H.M., 2016. "Real-time holding control for high-frequency transit with dynamics," Transportation Research Part B: Methodological, Elsevier, vol. 83(C), pages 1-19.
    2. Chen, Zhiwei & Li, Xiaopeng & Zhou, Xuesong, 2019. "Operational design for shuttle systems with modular vehicles under oversaturated traffic: Discrete modeling method," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 1-19.
    3. Xuan, Yiguang & Argote, Juan & Daganzo, Carlos F., 2011. "A Dynamic Holding Strategy to Improve Bus Schedule Reliability and Commercial Speed," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt0jp7c8k8, Institute of Transportation Studies, UC Berkeley.
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    6. Liang Gong & Yinzhen Li & Dejie Xu, 2019. "Combinational Scheduling Model Considering Multiple Vehicle Sizes," Sustainability, MDPI, vol. 11(19), pages 1-14, September.
    7. Xuan, Yiguang & Argote, Juan & Daganzo, Carlos F., 2011. "Dynamic bus holding strategies for schedule reliability: Optimal linear control and performance analysis," Transportation Research Part B: Methodological, Elsevier, vol. 45(10), pages 1831-1845.
    8. Mark D. Hickman, 2001. "An Analytic Stochastic Model for the Transit Vehicle Holding Problem," Transportation Science, INFORMS, vol. 35(3), pages 215-237, August.
    9. Gkiotsalitis, K. & Cats, O., 2021. "At-stop control measures in public transport: Literature review and research agenda," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    10. Mohammad-Reza Namazi-Rad & Michelle Dunbar & Hadi Ghaderi & Payam Mokhtarian, 2015. "Constrained Optimization of Average Arrival Time via a Probabilistic Approach to Transport Reliability," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-15, May.
    11. Wu, Cheng-Lung & Caves, Robert E., 2002. "Towards the optimisation of the schedule reliability of aircraft rotations," Journal of Air Transport Management, Elsevier, vol. 8(6), pages 419-426.

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