Real-time rescheduling and disruption management for public transit
Real-time rescheduling and disruption management for public transit
This research is motivated by the operations of a public transit company in Hong Kong. We investigate how real-time information can be utilized in combination with historical data to improve routing and scheduling decisions practically. A dynamic integrated vehicle and crew scheduling problem is studied where travel times are stochastic and time-dependent. The objective is to maximize the route frequencies and mileage to provide good passenger service and simultaneously minimize crew overtime and meal-break delays. To mitigate unexpected delays due to uncertainties in operations, various mathematical models are proposed for revising the schedules in real time under a rolling-horizon framework. Their efficiency and effectiveness are evaluated via simulation using real-world data. The simulation results also identify the potential benefits of revising the schedule dynamically in real time using optimization models. The results show that the proposed approaches can significantly reduce motormen overtime and meal-break delays while maintaining coverage and route frequency requirements.
17-33
Lai, David S. W.
9e095afb-da7c-42e3-9e3e-a609bf12da57
Leung, Janny M. Y.
f37e71c0-e2fc-4f2c-9dd5-bb897b1311da
2 January 2018
Lai, David S. W.
9e095afb-da7c-42e3-9e3e-a609bf12da57
Leung, Janny M. Y.
f37e71c0-e2fc-4f2c-9dd5-bb897b1311da
Lai, David S. W. and Leung, Janny M. Y.
(2018)
Real-time rescheduling and disruption management for public transit.
Transportmetrica B: Transport Dynamics, 6 (1), .
(doi:10.1080/21680566.2017.1358678).
Abstract
This research is motivated by the operations of a public transit company in Hong Kong. We investigate how real-time information can be utilized in combination with historical data to improve routing and scheduling decisions practically. A dynamic integrated vehicle and crew scheduling problem is studied where travel times are stochastic and time-dependent. The objective is to maximize the route frequencies and mileage to provide good passenger service and simultaneously minimize crew overtime and meal-break delays. To mitigate unexpected delays due to uncertainties in operations, various mathematical models are proposed for revising the schedules in real time under a rolling-horizon framework. Their efficiency and effectiveness are evaluated via simulation using real-world data. The simulation results also identify the potential benefits of revising the schedule dynamically in real time using optimization models. The results show that the proposed approaches can significantly reduce motormen overtime and meal-break delays while maintaining coverage and route frequency requirements.
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More information
Accepted/In Press date: 18 July 2017
e-pub ahead of print date: 1 August 2017
Published date: 2 January 2018
Identifiers
Local EPrints ID: 457655
URI: http://eprints.soton.ac.uk/id/eprint/457655
ISSN: 2168-0566
PURE UUID: a3e976f5-4937-4517-9d7f-15ecdad757d3
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Date deposited: 14 Jun 2022 16:58
Last modified: 17 Mar 2024 04:12
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Author:
David S. W. Lai
Author:
Janny M. Y. Leung
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