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Methodology for Extracting Potential Customized Bus Routes Based on Bus Smart Card Data

Author

Listed:
  • Jing Li

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Yongbo Lv

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Jihui Ma

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Qi Ouyang

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

Abstract

To alleviate traffic congestion and traffic-related environmental pollution caused by the increasing numbers of private cars, public transport (PT) is highly recommended to travelers. However, there is an obvious contradiction between the diversification of travel demands and simplification of PT service. Customized bus (CB), as an innovative supplementary mode of PT service, aims to provide demand-responsive and direct transit service to travelers with similar travel demands. But how to obtain accurate travel demands? It is passive and limited to conducting online surveys, additionally inefficient and costly to investigate all the origin-destinations (ODs) aimlessly. This paper proposes a methodological framework of extracting potential CB routes from bus smart card data to provide references for CB planners to conduct purposeful and effective investigations. The framework consists of three processes: trip reconstruction, OD area division and CB route extraction. In the OD area division process, a novel two-step division model is built to divide bus stops into different areas. In the CB route extraction process, two spatial-temporal clustering procedures and one length constraint are implemented to cluster similar trips together. An improved density-based spatial clustering of application with noise (DBSCAN) algorithm is used to complete these procedures. In addition, a case study in Beijing is conducted to demonstrate the effectiveness of the proposed methodological framework and the resulting analysis provides useful references to CB planners in Beijing.

Suggested Citation

  • Jing Li & Yongbo Lv & Jihui Ma & Qi Ouyang, 2018. "Methodology for Extracting Potential Customized Bus Routes Based on Bus Smart Card Data," Energies, MDPI, vol. 11(9), pages 1-15, August.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:9:p:2224-:d:165673
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    References listed on IDEAS

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    1. Shyue Koong Chang & Paul M. Schonfeld, 1991. "Optimization Models for Comparing Conventional and Subscription Bus Feeder Services," Transportation Science, INFORMS, vol. 25(4), pages 281-298, November.
    2. Liu, Tao & Ceder, Avishai (Avi), 2015. "Analysis of a new public-transport-service concept: Customized bus in China," Transport Policy, Elsevier, vol. 39(C), pages 63-76.
    3. Guihaire, Valérie & Hao, Jin-Kao, 2008. "Transit network design and scheduling: A global review," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(10), pages 1251-1273, December.
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    Cited by:

    1. Zhiling Han & Yanyan Chen & Hui Li & Kuanshuang Zhang & Jiyang Sun, 2019. "Customized Bus Network Design Based on Individual Reservation Demands," Sustainability, MDPI, vol. 11(19), pages 1-25, October.
    2. Qing Yu & Weifeng Li & Haoran Zhang & Dongyuan Yang, 2020. "Mobile Phone Data in Urban Customized Bus: A Network-based Hierarchical Location Selection Method with an Application to System Layout Design in the Urban Agglomeration," Sustainability, MDPI, vol. 12(15), pages 1-20, July.
    3. Jing Li & Yongbo Lv & Jihui Ma & Yuan Ren, 2019. "Factor Analysis of Customized Bus Attraction to Commuters with Different Travel Modes," Sustainability, MDPI, vol. 11(24), pages 1-13, December.

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