NDLI: An Electric Fence-Based Intelligent Scheduling Method for Rebalancing Dockless Bike Sharing Systems

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An Electric Fence-Based Intelligent Scheduling Method for Rebalancing Dockless Bike Sharing Systems

Content Provider	MDPI
Author	Jia, Lulu Yang, Dezhen Ren, Yi Feng, Qiang Sun, Bo Qian, Cheng Li, Zhifeng Zeng, Chenchen
Copyright Year	2022
Description	With a new generation of bike sharing services emerging, the development of dockless bike sharing services results in considerable socioeconomic and environmental benefits but also creates new issues, such as inappropriate parking behaviors and bike imbalances. To solve the inappropriate parking problem, electric fences have been introduced to guide users to park bikes in designated zones. Considering the role of electric fences in restricting user parking behaviors, an electric fence-based intelligent scheduling method for rebalancing dockless bike sharing systems is proposed in this paper. As a dynamic method that considers the real-time usage of bike sharing systems, an electric fence adjusts its capacity based on real-time information, which guides users to return bikes to electric fences with greater urgency. Because existing approaches require prespecified models and are unable to consider all the intricacies in the dynamic optimization problem, a model-free intelligent scheduling approach based on deep Q-learning that can adapt to the changing distributions of customer arrivals, available bikes, bike locations, and user travel times is used to solve the problem. Finally, a case study involving Beihang University is employed, which shows that the method performs well in rebalancing the bike sharing system and improving the mean utilization (MU) and customer satisfaction (CS).
Starting Page	5031
e-ISSN	20763417
DOI	10.3390/app12105031
Journal	Applied Sciences
Issue Number	10
Volume Number	12
Language	English
Publisher	MDPI
Publisher Date	2022-05-16
Access Restriction	Open
Subject Keyword	Applied Sciences Transportation Science and Technology Bike Sharing System Dockless Bikes Electric Fence Deep Q-learning Intelligent Scheduling
Content Type	Text
Resource Type	Article

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