Time control point strategy coupled with transfer coordination in bus schedule design

Dou, Xueping; Yan, Yonggao; Guo, Xiucheng; Gong, Xiaolin

doi:10.1002/atr.1404

Cited by 11 publications

(8 citation statements)

References 33 publications

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“…e on-time arrival and departure characteristics of a bus station timetable were used to measure reliability. Dou et al [92] developed a novel time control point strategy to obtain the optimal slack time scheme and applied an MINLP model to improve schedule adherence and reduce transfer waiting time. Wang et al [93] proposed a joint strategy with bus holding and timetabling slack to optimize the locations of control points and formulate a bus timetable considering the uncertainty in the operational process.…”

Section: Operational Strategy For Bus System Servicesmentioning

confidence: 99%

Reliability Analysis of Bus Timetabling Strategy during the COVID-19 Epidemic: A Case Study of Yixing, China

Gao

Zheng

et al. 2021

Discrete Dynamics in Nature and Society

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How to meet the daily demand for resident transport while limiting the transmission of infectious diseases is a problem of social responsibility of urban transport systems during major public health emergencies. Considering the novel coronavirus pneumonia epidemic (COVID-19), a bus timetable system based on the “if early, wait, and if late, leave soon” strategy is proposed. Based on public transport vehicle constraints in this system, the concept of reliability is introduced to evaluate public transport timetable systems, and a model based on an event tree is built to calculate the failure rate of urban bus timetables. Then, the public transport situation in Yixing city is used as an example to perform confirmatory analysis, and the fluctuations in the reliability of the bus timetable during the novel coronavirus pneumonia epidemic are discussed. The research results show that the method proposed in this paper can obtain the overall failure rate of urban bus timetable by traversing the calculation of each round-trip interval and achieve an accurate evaluation of the reliability of bus timetables. During the early, middle, and more recent stages of the COVID-19 outbreak, the failure rate of bus timetables in Yixing city initially decreased and then increased. In the early stage of the outbreak, the failure rate of the Yixing bus timetable was 7.8142. However, the failure rate decreased to 4.3306 and 5.0160 in the middle and late stages of the epidemic, respectively. In other words, the failure rate of the public transport network in the middle and late stages decreased by 44.58% and 35.81%, respectively, compared with that in the early stage. Thus, during major health emergencies, such as the novel coronavirus pneumonia outbreak, the reliability of the urban bus timetable system can be improved by at least 35%, and cross-infection at bus stations can be prevented. The research results verify the feasibility and reliability of the implementation of bus timetabling strategies during major health emergencies.

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Section: Operational Strategy For Bus System Servicesmentioning

confidence: 99%

Reliability Analysis of Bus Timetabling Strategy during the COVID-19 Epidemic: A Case Study of Yixing, China

Gao

Zheng

et al. 2021

Discrete Dynamics in Nature and Society

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“…(19). Equations (20) and (21) ensure that every route starts and ends at the station. The developed model was coded in MATLAB.…”

Section: End If Step 15: Show Resultsmentioning

confidence: 99%

“…In recent years, studies have focused on the development of more realistic models and the use of new solution methods. Some researchers have developed models by adding passenger wait times at trunk and feeder stops as well as transfer wait times [21,22]. Wang [23] considered routing and scheduling in a Last Mile Transit (LMT) service and proposed a mixed-integer programming model.…”

Section: Trunk Service and Its Feeder Bus Systemmentioning

confidence: 99%

Development of an Algorithm for Optimal Demand Responsive Relocatable Feeder Transit Networks Serving Multiple Trains and Stations

et al. 2019

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Although demand responsive feeder bus operation is possible with human-driven vehicles, it has not been very popular and is mostly available as a special service because of its high operating costs due to intensive labor costs as well as requirement for advanced real-time information technology and complicated operation. However, once automated vehicles become available, small-sized flexible door-to-door feeder bus operation will become more realistic, so preparing for such automated flexible feeder services is necessary to take advantage of the rapid improvement of automated vehicle technology. Therefore, in this research, an algorithm for optimal flexible feeder bus routing, which considers relocation of buses for multiple stations and trains, was developed using a simulated annealing algorithm for future automated vehicle operation. An example was developed and tested to demonstrate the developed algorithm. The algorithm successfully handled relocation of buses when the optimal bus routings were not feasible using the buses available at certain stations. Furthermore, the developed algorithm limited the maximum degree of circuity for each passenger while minimizing the total cost, including total vehicle operating costs and total passenger in-vehicle travel time costs.

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“…The genetic algorithm was also implemented by Verma and Dhingra (13) and Shrivastava and O'Mahony (14,15) in sequential approaches that heuristically generated lines and subsequently coordinated these lines. Recently, for bus lines connecting with a fixed-schedule train service, Dou et al formulated a robust mixed-integer linear programming model (MINLP) to improve bus schedule adherence and reduce the waiting time for transferring from buses to trains (16). Sivakumaran et al proposed a continuous approximation approach to determine the frequency of feeder lines with a given trunk schedule to minimize passenger waiting times at feeder stops, transfer waiting times at the trunk stop, and feeder operating cost (17).…”

Section: Relevant Studiesmentioning

confidence: 99%

Coordination of Feeder Bus Schedule with Train Service at Integrated Transport Hubs

Dou

Gong

Guo

et al. 2017

Transportation Research Record: Journal of the Transportation R

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This paper proposes a schedule coordination method for transfer problems between an urban rail transit service and its feeder bus service. For given train schedules, a novel mixed-integer nonlinear programming (MINLP) model is formulated to obtain a coordinated bus schedule with the objective of minimizing the weighted sum of passenger transfer costs and bus operating costs. The queuing process for transfer passengers at the transport hubs, which is attributed to both high transfer volumes and limited bus capacity, is discussed and considered in the coordination problem. The vital decision variable is the terminal departure time of each target feeder bus trip within a certain time period. A hybrid solution method that integrates heuristic and enumerative algorithms was developed to solve the MINLP model, and numerical experiments were conducted for different scenarios. The results indicate that the feeder bus schedule coordinated by the developed model is capable of substantially reducing the transfer waiting time for train passengers with a slight increase in bus operating costs.

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Time control point strategy coupled with transfer coordination in bus schedule design

Cited by 11 publications

References 33 publications

Reliability Analysis of Bus Timetabling Strategy during the COVID-19 Epidemic: A Case Study of Yixing, China

Reliability Analysis of Bus Timetabling Strategy during the COVID-19 Epidemic: A Case Study of Yixing, China

Development of an Algorithm for Optimal Demand Responsive Relocatable Feeder Transit Networks Serving Multiple Trains and Stations

Coordination of Feeder Bus Schedule with Train Service at Integrated Transport Hubs

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