Real-time rescheduling and disruption management for public transit

D.S.W. Lai, Janny M.Y. Leung

Research output: Contribution to JournalArticleAcademicpeer-review

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.
LanguageEnglish
Pages1-17
Number of pages17
JournalTransportmetrica B: Transport Dynamics
DOIs
StatePublished - 1 Aug 2017

Fingerprint

Scheduling
Travel time
overtime
management
meals
scheduling
Mathematical models
simulation
optimization model
Industry
Hong Kong
coverage
travel
time
Disruption management
Rescheduling
Public transit
uncertainty
efficiency
Schedule

Keywords

  • Real-time
  • rescheduling
  • RFID

Cite this

@article{5bc3f1614be64c1e8df04223560c80c0,
title = "Real-time rescheduling and disruption management for public transit",
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.",
keywords = "Real-time, rescheduling, RFID",
author = "D.S.W. Lai and Leung, {Janny M.Y.}",
year = "2017",
month = "8",
day = "1",
doi = "10.1080/21680566.2017.1358678",
language = "English",
pages = "1--17",
journal = "Transportmetrica B: Transport Dynamics",
issn = "2168-0566",
publisher = "Taylor& Francis",

}

Real-time rescheduling and disruption management for public transit. / Lai, D.S.W.; Leung, Janny M.Y.

In: Transportmetrica B: Transport Dynamics, 01.08.2017, p. 1-17.

Research output: Contribution to JournalArticleAcademicpeer-review

TY - JOUR

T1 - Real-time rescheduling and disruption management for public transit

AU - Lai,D.S.W.

AU - Leung,Janny M.Y.

PY - 2017/8/1

Y1 - 2017/8/1

N2 - 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.

AB - 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.

KW - Real-time

KW - rescheduling

KW - RFID

U2 - 10.1080/21680566.2017.1358678

DO - 10.1080/21680566.2017.1358678

M3 - Article

SP - 1

EP - 17

JO - Transportmetrica B: Transport Dynamics

T2 - Transportmetrica B: Transport Dynamics

JF - Transportmetrica B: Transport Dynamics

SN - 2168-0566

ER -