MSSE Thesis Defense: Hao Da (Kevin) Dong, "Servicing Logistics for Self-Driving E-Scooters"
Wednesday, April 14, 2021
MSSE Thesis Defense
Analysis and Optimization of Servicing Logistics for Self-Driving E-Scooters
Hao Da (Kevin) Dong
Dr. Derek A. Paley, Chair
Dr. Jeffrey Herrmann, Committee Member
Dr. Ilya O. Ryzhov, Committee Member
In recent years, the shared scooter market has seen tremendous growth along with other micromobility industries as the future means of urban transport. One particularly interesting innovation that companies have begun experimenting with in this field is that of self-driving e-scooters.
This thesis presents a study on one application of an autonomous or teleoperated scooter fleet that can benefit scooter operator companies by reducing costs: self-assembly for batch servicing. To this end, the application is tackled as two separate optimization problems in clustering and routing. The full algorithm pipeline is described and several metrics evaluated against independent variables and algorithm parameters using real-world GBFS scooter data collected over several months.
This thesis shows that self-assembly reduces total service times by as much as 50%, and can serve as a stepping stone for early adoption of the technology while more complex capabilities are being developed.