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An Application of a Deep Q-Network Based Dynamic Fare Bidding System to Improve the Use of Taxi Services during Off-Peak Hours in Seoul

Author

Listed:
  • Yunji Cho

    (National Transport Safety and Disaster Prevention Research Center, Korea Transport Institute, Sejong 30147, Korea)

  • Jaein Song

    (Research Institute of Science and Technology, Hongik University, Seoul 04066, Korea)

  • Minhee Kang

    (Department of Smart City, Hongik University, Seoul 04066, Korea)

  • Keeyeon Hwang

    (Department of Urban Planning, Hongik University, Seoul 04066, Korea)

Abstract

The problem of structural imbalance in terms of supply and demand due to changes in traffic patterns by time zone has been continuously raised in the mobility market. In Korea, unlike large overseas cities, the waiting time tolerance increases during the daytime when supply far exceeds demand, resulting in a large loss of operating profit. The purpose of this study is to increase taxi demand and further improve driver’s profits through real-time fare discounts during off-peak daytime hours in Seoul, Korea. To this end, we propose a real-time fare bidding system among taxi drivers based on a dynamic pricing scheme and simulate the appropriate fare discount level for each regional time zone. The driver-to-driver fare competition system consists of simulating fare competition based on the multi-agent Deep Q-Network method after developing a fare discount index that reflects the supply and demand level of each region in 25 districts in Seoul. According to the optimal fare discount level analysis in the off-peak hours, the lower the OI Index, which means the level of demand relative to supply, the higher the fare discount rate. In addition, an analysis of drivers’ profits and matching rates according to the distance between the origin and destination of each region showed up to 89% and 65% of drivers who actively offered discounts on fares. The results of this study in the future can serve as the foundation of a fare adjustment system for varying demand and supply situations in the Korean mobility market.

Suggested Citation

  • Yunji Cho & Jaein Song & Minhee Kang & Keeyeon Hwang, 2021. "An Application of a Deep Q-Network Based Dynamic Fare Bidding System to Improve the Use of Taxi Services during Off-Peak Hours in Seoul," Sustainability, MDPI, vol. 13(16), pages 1-17, August.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:16:p:9351-:d:618143
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    References listed on IDEAS

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    1. Guillermo Gallego & Garrett van Ryzin, 1994. "Optimal Dynamic Pricing of Inventories with Stochastic Demand over Finite Horizons," Management Science, INFORMS, vol. 40(8), pages 999-1020, August.
    2. Jörg Firnkorn & Martin Müller, 2012. "Selling Mobility instead of Cars: New Business Strategies of Automakers and the Impact on Private Vehicle Holding," Business Strategy and the Environment, Wiley Blackwell, vol. 21(4), pages 264-280, May.
    3. Wedad Elmaghraby & P{i}nar Keskinocak, 2003. "Dynamic Pricing in the Presence of Inventory Considerations: Research Overview, Current Practices, and Future Directions," Management Science, INFORMS, vol. 49(10), pages 1287-1309, October.
    4. Adnan, Muhammad & Nahmias Biran, Bat-hen & Baburajan, Vishnu & Basak, Kakali & Ben-Akiva, Moshe, 2020. "Examining impacts of time-based pricing strategies in public transportation: A study of Singapore," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 127-141.
    5. Gabriel R. Bitran & Susana V. Mondschein, 1997. "Periodic Pricing of Seasonal Products in Retailing," Management Science, INFORMS, vol. 43(1), pages 64-79, January.
    6. Pueboobpaphan, Suthatip & Indra-Payoong, Nakorn & Opasanon, Sathaporn, 2019. "Experimental analysis of variable surcharge policy of taxi service auction," Transport Policy, Elsevier, vol. 76(C), pages 134-148.
    7. Rambha, Tarun & Boyles, Stephen D., 2016. "Dynamic pricing in discrete time stochastic day-to-day route choice models," Transportation Research Part B: Methodological, Elsevier, vol. 92(PA), pages 104-118.
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