Human-driven vehicles’ cruising versus autonomous vehicles’ back-and-forth congestion: The effects on traveling, parking, and congestion

• Explore the congestion interaction between human-driven vehicles (HVs) cruising for parking and autonomous vehicles (AVs) traveling back and forth. • Develop a continuous spatial model to capture the spatial distribution of parking. • Analyze the joint mode and parking-location choices, both without pricing and with the socially optimal pricing. • Analyze the effects on traveling, parking and congestion. This paper explores the congestion interaction between human-driven vehicles (HVs) cruising for parking and autonomous vehicles (AVs) driving back and forth: first going into the city and then traveling back to park. To capture the spatial distribution of parking, we develop a continuous spatial optimization model, with a discrete choice logit model governing the choice between the two modes. Various congestion externalities are considered in the proposed model, including HVs’ cruising and searching for parking, as well as AVs’ back-and-forth travel. We analyze the joint travel mode and parking location choice equilibrium in the absence of pricing and in the social optimum that maximizes welfare. The social optimum is derived using optimal control method under user-equilibrium constraints. The introduction of AVs reduces parking demand in the city and results in a smaller city with lower parking density. Without pricing, the introduction of AVs may increase or decrease congestion, depending on if the effects of HVs cruising or AVs’ back-and-forth travel dominate. Thus, AVs may be underused or overused. With optimal pricing, the introduction of AVs always improves welfare. A stronger effect of AVs’ back-and-forth travel on congestion tends to increase the number of AVs and reduce the size of the city. This surprising result is because the effect of back-and-forth congestion may be larger for HVs than for AVs.