TSM-SP: Time-Sharing Matching Shared Parking System Based on Time Window and Dynamic Pricing

With the continuous growth of urban parking demand, the difficulty of finding available parking spaces has become a prominent problem, primarily due to improper parking behavior of human drivers and limited parking resources. The rise of autonomous vehicles (AVs) offers new opportunities to alleviate traffic pressure caused by improper parking behavior, with intelligent navigation and autonomous scheduling expected to enhance the efficiency of transportation systems. Meanwhile, by optimizing private parking resources utilization, shared parking helps address the issue of limited parking resources. However, due to mismatches between requested parking durations and available shared parking time, existing shared parking systems often suffer from low utilization and high parking request rejection rates. To address these challenges, this paper proposes a shared parking space (SPS) allocation system with AVs based on time-sharing matching. This approach enables AV to utilize two different SPSs during parking, thereby maximizing the utilization of shared parking time. By adjusting the price of SPSs, the system guides the rational distribution of AVs, while maintaining the total parking cost of users across two-stage allocation. Simulation results show that TSM-SP increases the average SPS utilization by at least 16%, reduces the rejection rate of parking requests by more than 50%, and lowers the average total parking cost of users by at least 16%, compared with baseline methods.