Autonomous vehicle parking policies: A case study of the City of Toronto

Autonomous Vehicles (AVs) can eliminate the burden of finding a parking spot upon arrival to destination. AVs park at strategic location or cruise until summoned by their users. In this study, we investigate AV users’ decision considering cost and time constraints. Each has impacts on congestion which change feasible options other Hence, use an agent-based simulation model study policies. Results show that travelers consider sending vehicles home if they have pay facility. Also, our analysis for downtown Toronto shows would travel average 12 min maximum 47 in cheaper lots. We also find assigning same price across all facilities exacerbate motiving more instead choosing closest lot. However, toll zero-occupant leads tradeoff between distance decrease VKT 3.5% Toronto.