Intelligent Management of On-street Parking Provision for the Autonomous Vehicles Era

摘要

The increasing degree of connectivity between vehicles and infrastructure, and the impending deployment of autonomous vehicles (AV) in urban streets, presents unique opportunities and challenges regarding the on-street parking provision for AVs. This study develops a novel simulation-optimisation approach for intelligent curbside management, based on a metaheuristic technique. The hybrid method balances curb lanes for driving or parking, aiming to minimise the average traffic delay. The model is tested using an idealised grid layout with a range of flow rates and parking policies. Results demonstrate delay decreased by 9%-27% from the benchmark case. Additionally, the traffic delay distribution shows the trade-offs between expanding road capacity and minimising traffic demand through curb management, indicating the interplay between curb parking and traffic management in the AV era.