Technical Papers
Sep 10, 2022

Estimation of Joint Activity–Travel Benefit with Metro Smart Card Data

Publication: Journal of Transportation Engineering, Part A: Systems
Volume 148, Issue 11

Abstract

With the rapid development of information and telecommunication technology, joint activity–travel constitutes an ever-increasing share of an individual’s daily activity–travel pattern. In recent years, joint activity–travel pattern (JATP) scheduling models have been developed to investigate individuals’ independent and joint activity–travel choice behavior. The additional benefit resulting from joint activity–travel, related to the length of the joint episode, is identified as a significant concern in individuals’ JATP scheduling. In previous JATP scheduling models, joint activity–travel benefit generally is modeled with simulated parameters. As a pioneering endeavor, this study quantified the relationship between joint activity–travel benefit and JATP utility, considering the joint episode’s length. A rule-based method is used to infer individuals’ joint activity–travel behaviors. A two-stage framework is proposed to estimate joint activity–travel benefit in the JATP scheduling model. The joint activity–travel benefit is estimated in the first stage. In the second stage, the Kalman filter is used to reduce the influence of deviation of network flow on the accuracy of estimating joint activity–travel benefit. The proposed method was examined with the metro smart card data collected in Suzhou, China. The results showed that the proposed method effectively estimates joint activity–travel benefit for the JATP scheduling model.

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Data Availability Statement

Some data, models, or code generated or used during the study are proprietary or confidential and may only be provided with restrictions, including a sample smart card data set collected in Suzhou, China.

Acknowledgments

The work described in this paper was supported by Humanities and Social Science Fund of Ministry of Education of the People’s Republic of China (No. 21YJC790030) and the “Zhishan” Scholars Programs of Southeast University (No. 2242021R41162).

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Go to Journal of Transportation Engineering, Part A: Systems
Journal of Transportation Engineering, Part A: Systems
Volume 148Issue 11November 2022

History

Received: Dec 2, 2021
Accepted: Jun 24, 2022
Published online: Sep 10, 2022
Published in print: Nov 1, 2022
Discussion open until: Feb 10, 2023

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Authors

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Ph.D. Candidate, Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast Univ., Nanjing 211189, China; School of Economics and Management, Tongji Univ., Shanghai 201804, China. Email: [email protected]
Associate Professor, Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast Univ., Nanjing 211189, China (corresponding author). ORCID: https://orcid.org/0000-0003-0446-0971. Email: [email protected]
Zhiyuan Liu [email protected]
Professor, Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast Univ., Nanjing 211189, China. Email: [email protected]

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Cited by

  • A metro smart card data-based analysis of group travel behaviour in Shanghai, China, Journal of Transport Geography, 10.1016/j.jtrangeo.2023.103764, 114, (103764), (2024).
  • An Integrated Framework for Real-Time Intelligent Traffic Management of Smart Highways, Journal of Transportation Engineering, Part A: Systems, 10.1061/JTEPBS.TEENG-7729, 149, 7, (2023).

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