Shared Autonomous Vehicle Modeling Considering System Optimization and Simulation
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 150, Issue 4
Abstract
This paper optimizes the assignment of shared automated vehicles under users’ uncertain departure times. Automated vehicles can drive themselves, so no staff are needed to relocate vehicles in the one-way carsharing system. To optimize fleet placement and use, a two-phase solution method was established. Phase 1 strategically distributes vehicles across stations using a system optimization approach, while Phase 2 tracks vehicle movements via an agent-based simulation model. Phase 1 solutions serve as inputs to Phase 2 simulations. Using a fleet size of roughly 10,000 vehicles, case study applications were run across the Austin, Texas region's six-county network. In the base case setting, results suggest that system profits are optimized when vehicle rental is priced at (). The number of proactive vehicle relocations falls 9.8% if the relocation operation cost rises from () to (). Average per-trip profit is $10.60 when using high-cost vehicles, and $11.60 when using low-cost vehicles. Results from a 3-h simulation show an average person-trip length of 25 km (15.6 mi), with 29.6 min of average driving time. When a 24-h day was simulated, the vehicle-occupied time and vehicle-distance traveled were 4 h and 200 km (125 mi) per vehicle-day, respectively. The low coefficient of variation of satisfied demand across 30 demand scenarios suggests the robustness of the two-phase solution method.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This research was financially supported by NSF Industry/University Cooperative Research Project UT12S20T and the National Natural Science Foundation of China Youth Program (No. 72301066). The authors thank Zhiyuan Liu for his early discussions in this paper, and Maizy Jeong and Aditi Bhaskar for their excellent editing and submission support.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 150 • Issue 4 • April 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Oct 9, 2022
Accepted: Sep 15, 2023
Published online: Feb 6, 2024
Published in print: Apr 1, 2024
Discussion open until: Jul 6, 2024
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