Estimating Wait Time and Passenger Load in a Saturated Metro Network: A Data-Driven Approach

The service quality of public transit, such as comfort and convenience, is an important factor influencing ridership and fare revenue, which also reflects the passengers’ perception to the transit performance. Passengers are frustrated while waiting to board a crowded train especially during the pea...

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Main Authors: Hezhou Qu, Xiaoyue Xu, Steven Chien
Format: Article
Language:English
Published: Hindawi-Wiley 2020-01-01
Series:Journal of Advanced Transportation
Online Access:http://dx.doi.org/10.1155/2020/4271871
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spelling doaj-977cbc2089904c19a498b6b0dfbe31462020-11-25T03:07:54ZengHindawi-WileyJournal of Advanced Transportation0197-67292042-31952020-01-01202010.1155/2020/42718714271871Estimating Wait Time and Passenger Load in a Saturated Metro Network: A Data-Driven ApproachHezhou Qu0Xiaoyue Xu1Steven Chien2School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, Sichuan 611756, ChinaSchool of Transportation and Logistics, Southwest Jiaotong University, Chengdu, Sichuan 611756, ChinaCollege of Transportation Engineering, Chang’an University, Xi’an, Shaanxi 710064, ChinaThe service quality of public transit, such as comfort and convenience, is an important factor influencing ridership and fare revenue, which also reflects the passengers’ perception to the transit performance. Passengers are frustrated while waiting to board a crowded train especially during the peak hours, while the fail-to-board (FtB) situation commonly exists. The service performance measures determined by deterministic passenger demand and service frequency cannot reflect the perceived service of passengers. With the automatic fare collection system data provided by Chengdu Metro, we develop a data-driven approach considering the joint probability of spatiotemporal passenger demand at stations based on posted train schedule to approximate passenger travel time (e.g., in-vehicle and out-of-vehicle times). It was found that the estimated wait time can reflect the actual situation as passengers FtB. The proposed modeling approach and analysis results would be useful and beneficial for transit providers to improve system performance and service planning.http://dx.doi.org/10.1155/2020/4271871
collection DOAJ
language English
format Article
sources DOAJ
author Hezhou Qu
Xiaoyue Xu
Steven Chien
spellingShingle Hezhou Qu
Xiaoyue Xu
Steven Chien
Estimating Wait Time and Passenger Load in a Saturated Metro Network: A Data-Driven Approach
Journal of Advanced Transportation
author_facet Hezhou Qu
Xiaoyue Xu
Steven Chien
author_sort Hezhou Qu
title Estimating Wait Time and Passenger Load in a Saturated Metro Network: A Data-Driven Approach
title_short Estimating Wait Time and Passenger Load in a Saturated Metro Network: A Data-Driven Approach
title_full Estimating Wait Time and Passenger Load in a Saturated Metro Network: A Data-Driven Approach
title_fullStr Estimating Wait Time and Passenger Load in a Saturated Metro Network: A Data-Driven Approach
title_full_unstemmed Estimating Wait Time and Passenger Load in a Saturated Metro Network: A Data-Driven Approach
title_sort estimating wait time and passenger load in a saturated metro network: a data-driven approach
publisher Hindawi-Wiley
series Journal of Advanced Transportation
issn 0197-6729
2042-3195
publishDate 2020-01-01
description The service quality of public transit, such as comfort and convenience, is an important factor influencing ridership and fare revenue, which also reflects the passengers’ perception to the transit performance. Passengers are frustrated while waiting to board a crowded train especially during the peak hours, while the fail-to-board (FtB) situation commonly exists. The service performance measures determined by deterministic passenger demand and service frequency cannot reflect the perceived service of passengers. With the automatic fare collection system data provided by Chengdu Metro, we develop a data-driven approach considering the joint probability of spatiotemporal passenger demand at stations based on posted train schedule to approximate passenger travel time (e.g., in-vehicle and out-of-vehicle times). It was found that the estimated wait time can reflect the actual situation as passengers FtB. The proposed modeling approach and analysis results would be useful and beneficial for transit providers to improve system performance and service planning.
url http://dx.doi.org/10.1155/2020/4271871
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