Optimization of Shared Autonomous Vehicles Routing Problem: From the View of Parking

Chi Feng and Zhenyu Mei ()
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Chi Feng: College of Mechanical Engineering, Quzhou University, Quzhou 324000, China
Zhenyu Mei: Institute of Intelligent Transportation, Zhejiang University, Hangzhou 310058, China

Sustainability, 2023, vol. 15, issue 16, 1-17

Abstract: Shared autonomous vehicles (SAVs) have great potential for achieving beneficial changes to the society. Although recent studies have explored the traffic safety, economic benefits and environmental impact, parking decisions of SAVs is rarely considered. SAVs need to park to avoid cruising during the interval between services. Appropriate parking decisions can contribute to reduce the vehicle kilometers traveled (VKT). This study synergistically considers routing and parking of SAVs for system optimization. Since the problem is NP-hard, we develop a variable neighborhood search (VNS) heuristic to solve it. The heuristic aims to minimize the VKT, the number of SAVs and the parking cost by systematic changes of neighborhood. A series of experiments based on the Anaheim network prove the high solving efficiency and quality of the heuristic. Results also indicate that the marginal cost of the system decreases with the increase in travel demand and the VKT increases with the increase in parking fees.

Keywords: shared autonomous vehicles; parking; route planning; optimization; heuristics (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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