Optimal Configuration of Reserved Parking Resources Based on Agent Simulation

To utilize the parking resources in a balanced way, an agent simulation model is constructed for the scenario where the reserved parking demand and temporary parking demand coexist. First, the users’ choice of parking lots is simulated under different parking reservation ratio strategies. Then, combined with the dynamic change characteristics of parking demand, the optimization target is adjusted in time. Finally, the genetic algorithm is used to solve the available reservation ratio considering the interests of users and the benefits of parking lots. Simulation experimental results show that the optimization model can reduce travel time by 21%, reduce the proportion of cruising vehicles by 71%, and increase parking revenue by 1.8% when the proportion of reservation demand is larger compared with the fixed-scale model. The optimization model is more adaptable to the dynamic changes in parking demand.