Yazdani, D, Omidvar, MN, Deplano, I et al. (4 more authors) (2019) Real-time seat allocation for minimizing boarding/alighting time and improving quality of service and safety for passengers. Transportation Research Part C: Emerging Technologies, 103. pp. 158-173. ISSN 0968-090X
Abstract
Rail is considered as one of the most important ways of transferring passengers. High passenger loads has implications on train punctuality. One of the important parameters affecting punctuality is the average boarding/alighting time. Organizing boarding/alighting flows not only reduces the risk of extended dwell time, but also minimizes the risk of injuries and improves the overall service quality. In this paper, we investigate the possibility of minimizing the boarding/alighting time by maintaining a uniform load on carriages through systematic distribution of passengers with flexible tickets, such as season or anytime tickets where no seat information are provided at the time of reservation. To achieve this, the proposed algorithm takes other information such as passenger final destination, uniform load of luggage areas, as well as group travelers into account. Moreover, a discrete event simulation is designed for measuring the performance of the proposed method. The performance of the proposed method is compared with three algorithms on different test scenarios. The results show the superiority of the proposed method in terms of minimizing boarding/alighting time as well as increasing the success rate of assigning group of seats to group of passengers.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Keywords: | Seat allocation; Discrete event simulation; Heuristics; Optimization; Rail system; Transportation |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Business (Leeds) > Accounting & Finance Division (LUBS) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 17 Oct 2019 15:26 |
Last Modified: | 18 Oct 2019 08:24 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.trc.2019.03.014 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:152233 |