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A Travel Behavior-Based Skip-Stop Strategy Considering Train Choice Behaviors Based on Smartcard Data

Author

Listed:
  • Eun Hak Lee

    (Department of Civil and Environmental Engineering, Seoul National University, Seoul 08826, Korea)

  • Inmook Lee

    (Future Transport Policy Research Division, Korea Railroad Research Institute, Uiwang 16105, Korea)

  • Shin-Hyung Cho

    (Institute of Engineering Research, Seoul National University, Seoul 08826, Korea)

  • Seung-Young Kho

    (Department of Civil and Environmental Engineering and Institute of Construction and Environmental Engineering, Seoul National University, Seoul 08826, Korea)

  • Dong-Kyu Kim

    (Department of Civil and Environmental Engineering and Institute of Construction and Environmental Engineering, Seoul National University, Seoul 08826, Korea)

Abstract

This study analyzes a skip-stop strategy considering four types of train choice behavior with smartcard data. The proposed model aims to minimize total travel time with realistic constraints such as facility condition, operational condition, and travel behavior. The travel time from smartcard data is decomposed by two distributions of the express trains and the local trains using a Gaussian mixture model. The utility parameters of the train choice model are estimated with the decomposed distribution using the multinomial logit model. The optimal solution is derived by a genetic algorithm to designate the express stations of the Bundang line in the Seoul metropolitan area. The results indicate the travel times of the transfer-based strategy and the high ridership-based strategy are estimated to be 21.2 and 19.7 min/person, respectively. Compared to the travel time of the current system, the transfer-based strategy has a 5.8% reduction and the high ridership-based strategy has a 12.2% reduction. For the travel behavior-based strategy, the travel time was estimated to be 18.7 minutes, the ratio of the saved travel time is 17.9%, and the energy consumption shows that the travel behavior-based strategy consumes 305,437 (kWh) of electricity, which is about 12.7% lower compared to the current system.

Suggested Citation

  • Eun Hak Lee & Inmook Lee & Shin-Hyung Cho & Seung-Young Kho & Dong-Kyu Kim, 2019. "A Travel Behavior-Based Skip-Stop Strategy Considering Train Choice Behaviors Based on Smartcard Data," Sustainability, MDPI, vol. 11(10), pages 1-18, May.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:10:p:2791-:d:231565
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    References listed on IDEAS

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    Cited by:

    1. Mu Lin & Zhengdong Huang & Tianhong Zhao & Ying Zhang & Heyi Wei, 2022. "Spatiotemporal Evolution of Travel Pattern Using Smart Card Data," Sustainability, MDPI, vol. 14(15), pages 1-16, August.
    2. Maosheng Li & Hangcong Li, 2022. "Optimal Design of Subway Train Cross-Line Operation Scheme Based on Passenger Smart Card Data," Sustainability, MDPI, vol. 14(11), pages 1-17, May.
    3. Eun Hak Lee & Hosuk Shin & Shin-Hyung Cho & Seung-Young Kho & Dong-Kyu Kim, 2019. "Evaluating the Efficiency of Transit-Oriented Development Using Network Slacks-Based Data Envelopment Analysis," Energies, MDPI, vol. 12(19), pages 1-15, September.

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