Optimization of reservation parking space configurations in city centers through an agent-based simulation

Abstract

Parking demand is generally larger than parking supply in city centers. And uneven distribution of parking demand often leads to over-consumption in the popular places. To balance the existing conflicts, parking reservation system (PRS) is commonly adopted to manage and configure the reservation parking spaces. The aim of this paper is to optimize social benefits and parking lot revenue through configuring reasonable reservation proportion for each off-street public parking lot in the urban area, which can provide operation advice for parking management departments. Firstly, an agent-based simulation model which presents the coexistence of reservation and non-reservation parking vehicles was established, and parking selection used the predicted parking space occupancy rate of a target parking lot at a predicted vehicle arrival time. Then, genetic algorithm was used in simulations to optimize the solution of combining different reserved parking space proportion configurations. Finally, Wulin CBD, Hangzhou, China was applied as a case to analyze and optimize the reserved parking space proportion. The Single-objective optimization, such as social benefits, parking lot revenue, and multi-objective optimization were both discussed and analyzed. Results show that through optimizing parking reservation proportion configuration can directly and effectively improve social benefits or parking lot revenue. Further analysis indicated that optimizing social benefits and parking lot revenue are two conflicting objectives. The reserved parking space proportion in popular parking lots should be reduced as much as possible under the optimization of social benefits.