Modeling the Spatiotemporal Implications of Autonomous Vehicles’ Empty Cruising on Parking Dynamics and Traffic Flow

This is the authors' abstract. We don't add key points for this paper.

Autonomous vehicles’ (AVs) ability to reposition themselves can transform parking dynamics. We focus on empty cruising as an alternative to short-term parking. This capability affects parking space occupancy and traffic flow because AVs use road space instead of parking spaces. This research models the spatiotemporal implications of empty cruising on parking dynamics and traffic flow in a mixed environment of AVs and conventional vehicles (CVs). The contributions of this research compared with existing research include: (1) analyzing how empty cruising influences parking dynamics and traffic flow across diverse urban zones; (2) examining its temporal effect on parking search and traffic congestion; and (3) assessing how CVs are affected when this strategy is adopted by varying numbers of AVs. The methodological framework of this research is based on agent-based modeling to investigate the spatiotemporal implications of AVs empty cruising at different adoption rates, compared with a full CV environment. The findings of this research show that when empty cruising is performed to address short-term parking demand of up to 45 min, it can reduce overall parking search by approximately 2.5%, with central business district (CBD) zones experiencing around 33% higher reduction compared with suburban Traffic Analysis Zones. However, this reduction in parking search ratio exacerbates congestion, increasing travel time in the CBD zones by around 56% and in suburban zones by around 21%. The insights of this research can guide policy formulation for balanced use of road and parking infrastructure in the age of AVs.