Optimal management of park-and-ride points and shared parking spaces in the context of autonomous driving

This paper studies how to set the location of park-and-ride and the pricing of shared parking spaces to achieve the desired goals in the context of autonomous vehicles (AV). Assuming that a linear city does not allow single-occupancy private cars to enter the city center, travelers can only choose to park and ride or take a shared autonomous vehicle to reach the city center. Under the condition of autonomous driving, since the car can park autonomously, there are three ways to park: park the car home, park the car in a free parking space near the transfer point, and park the car in a shared parking space provided by residents near the transfer point. Starting from the two goals of profit maximization and social cost minimization, this paper explores the optimal parameter settings under the two goals respectively. The results show that the optimal park-and-ride point and the optimal shared parking space pricing under the two goals are both obtained when the supply of shared parking spaces is equal to the demand. This study can provide theoretical reference and decision-making basis for the optimal allocation of resources in the era of autonomous driving.