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Open AccessArticle

The Depth-First Optimal Strategy Path Generation Algorithm for Passengers in a Metro Network

by 1,2,3,*, 1,2 and 3
1
School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100404, China
2
National Engineering Laboratory for Urban Rail Transit Communication and Operation Control, Beijing 100044, China
3
Traffic Control Technology Co., Ltd., Beijing 100070, China
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(13), 5365; https://doi.org/10.3390/su12135365
Received: 11 June 2020 / Revised: 28 June 2020 / Accepted: 1 July 2020 / Published: 2 July 2020
(This article belongs to the Special Issue Sustainable Transport Economics, Behaviour and Policy)
Passenger behavior analysis is a key issue in passenger assignment research, in which the path choice is a fundamental component. A highly complex transit network offers multiple paths for each origin–destination (OD) pair and thus resulting in more flexible choices for each passenger. To reflect a passenger’s flexible choice for the transit network, the optimal strategy was proposed by other researchers to determine passenger choice behavior. However, only strategy links have been searched in the optimal strategy algorithm and these links cannot complete the whole path. To determine the paths for each OD pair, this study proposes the depth-first path generation algorithm, in which a strategy node concept is newly defined. The proposed algorithm was applied to the Beijing metro network. The results show that, in comparison to the shortest path and the K-shortest path analysis, the proposed depth-first optimal strategy path generation algorithm better represents the passenger behavior more reliably and flexibly. View Full-Text
Keywords: passenger behavior; optimal strategy; strategy node; depth-first optimal strategy path generation algorithm passenger behavior; optimal strategy; strategy node; depth-first optimal strategy path generation algorithm
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MDPI and ACS Style

Lu, K.; Tang, T.; Gao, C. The Depth-First Optimal Strategy Path Generation Algorithm for Passengers in a Metro Network. Sustainability 2020, 12, 5365. https://doi.org/10.3390/su12135365

AMA Style

Lu K, Tang T, Gao C. The Depth-First Optimal Strategy Path Generation Algorithm for Passengers in a Metro Network. Sustainability. 2020; 12(13):5365. https://doi.org/10.3390/su12135365

Chicago/Turabian Style

Lu, Kai; Tang, Tao; Gao, Chunhai. 2020. "The Depth-First Optimal Strategy Path Generation Algorithm for Passengers in a Metro Network" Sustainability 12, no. 13: 5365. https://doi.org/10.3390/su12135365

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