Optimal allocation and adjustment mechanism of shared parking slots considering combined parking resources
Minghui Xie, Siyu Lin, Zhouhao Wu, Xinying Zhang, Yuanqing Wang
Abstract
This paper establishes a rolling shared parking allocation model to optimize the matching of supply and demand in parking-dense districts by maximizing platform revenue and minimizing parking users’ travel costs. An adjustment mechanism that dynamically adjusts the allocated parking slots is developed to be embedded in the model. Considering multi-candidate adjacent parking lots, combined sharing and individual sharing patterns are compared to verify the benefits of resource combination. Numerical experiments indicate that the proposed model works well for changing parking demands and achieves more successful matches than the first-book-first-serve model. The combination of adjacent parking resources improves the platform revenue, the parking slot utilization, and the acceptance rate of parking requests, as well as reduces the average walking distance. The direct parking revenue of the parking lot with fewer slots is remarkably increased under combined sharing. The findings provide managerial insights for local collaborative shared parking.