TY - JOUR
T1 - Planning charging stations for mixed docked and dockless operations of shared electric micromobility systems
AU - Liu, Yining
AU - Ouyang, Yanfeng
N1 - The authors sincerely thank the editors and three anonymous reviewers for sharing valuable insights and constructive suggestions. The first author was financially supported in part by a project from the Illinois Department of Transportation.
PY - 2025/2
Y1 - 2025/2
N2 - Dockless electric micro-mobility services (e.g., shared e-scooters and e-bikes) have been increasingly popular in the recent decade, and a variety of charging technologies have emerged for these services. The use of charging stations, to/from which service vehicles are transported by the riders for charging, poses as a promising approach because it reduces the need for dedicated staff or contractors. However, unique challenges also arise, as it introduces docked vehicles at these stations to the existing dockless systems, and now riders can pick up and drop off e-scooters at both random locations and fixed charging stations. This requires incentives for riders to drop off vehicles at the stations and management strategies to efficiently utilize the vehicles at the stations. This paper focuses on such mixed operations of docked and dockless e-scooters as an example. It develops a new aspatial queuing network model for vehicle sharing and charging to capture the steady-state e-scooter service cycles, battery consumption and charging processes, and the associated pricing and management mechanisms in a region with uniform demand. Building upon this model, a system of closed-form equations is formulated and incorporated into a constrained nonlinear program to optimize the deployment of the service fleet, the design of charging stations (i.e., number, location, and capacity), user-based charging price promotions and priorities, and repositioning truck operations (i.e., headway and truck load). The proposed queuing network model is found to match very well with agent-based simulations. It is applied to a series of numerical experiments to draw insights into the optimal designs and the system performance. The numerical results reveal strong advantages of using charging stations for shared dockless electric micro-mobility services as compared to state-of-the-art alternatives. The proposed model can also be used to analyze other micromobility services and other charging approaches.
AB - Dockless electric micro-mobility services (e.g., shared e-scooters and e-bikes) have been increasingly popular in the recent decade, and a variety of charging technologies have emerged for these services. The use of charging stations, to/from which service vehicles are transported by the riders for charging, poses as a promising approach because it reduces the need for dedicated staff or contractors. However, unique challenges also arise, as it introduces docked vehicles at these stations to the existing dockless systems, and now riders can pick up and drop off e-scooters at both random locations and fixed charging stations. This requires incentives for riders to drop off vehicles at the stations and management strategies to efficiently utilize the vehicles at the stations. This paper focuses on such mixed operations of docked and dockless e-scooters as an example. It develops a new aspatial queuing network model for vehicle sharing and charging to capture the steady-state e-scooter service cycles, battery consumption and charging processes, and the associated pricing and management mechanisms in a region with uniform demand. Building upon this model, a system of closed-form equations is formulated and incorporated into a constrained nonlinear program to optimize the deployment of the service fleet, the design of charging stations (i.e., number, location, and capacity), user-based charging price promotions and priorities, and repositioning truck operations (i.e., headway and truck load). The proposed queuing network model is found to match very well with agent-based simulations. It is applied to a series of numerical experiments to draw insights into the optimal designs and the system performance. The numerical results reveal strong advantages of using charging stations for shared dockless electric micro-mobility services as compared to state-of-the-art alternatives. The proposed model can also be used to analyze other micromobility services and other charging approaches.
KW - Charging station
KW - Dockless
KW - E-bike
KW - E-scooter
KW - Micromobility
KW - Price incentive
KW - State-of-charge
UR - http://www.scopus.com/inward/record.url?scp=85214782379&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85214782379&partnerID=8YFLogxK
U2 - 10.1016/j.trc.2024.104989
DO - 10.1016/j.trc.2024.104989
M3 - Article
AN - SCOPUS:85214782379
SN - 0968-090X
VL - 171
JO - Transportation Research Part C: Emerging Technologies
JF - Transportation Research Part C: Emerging Technologies
M1 - 104989
ER -