A Matching And Pricing Mechanism For Sharing Parking Platform Under Incomplete Information Setting

Parking has become an urgent problem in many metropolitans,public parking slots resource can no longer meet the growing parking demand.The development of various advanced technologies in the past few years,such as mobile-Internet,RFID,parking sensor,provide supports for private parking slots service.How to utilize the private parking slots efficiently and determine the parking price for driver and the corresponding subsidy for slots owner are two key issues.According to the relevant enterprise survey,most parking sharing platform provide only available slots information for drivers around their destinations rather than perform the exact match between drivers and slots,which impair the travel efficiency of drivers seriously.In the aspect of pricing,these platforms adopt time-based linear pricing method without considering the utilities of drivers and owners,which may induce information misreporting of participants and further lead to optimization target loss.In academic research,most earlier studies about parking slots management based on the improvement of land usage or perfecting the parking facilities,many scholars have studied the public parking slots management problem,but there are few researches on private parking slots sharing with the rise of shared economy.Motivated by industrial and academic interests,this study focusses on the matching-scheduling and pricing mechanism of shared private parking slots.According to the characteristics of sharing slots platform,this research designs an efficient real-time shared parking reservation system which not only proposes driversslots matching and suggested drivers' travel scheme but also decides a parking price to incentive drivers to report parking demands to platform truthfully.In the aspect of matching and scheduling,both of drivers' travel time requirement and slots' available time interval provided by owners are considered,moreover,one-driver-to-one-slot and multi-drivers-to-one-slot matching models are built respectively which could generate drivers-slots matching and suggested drivers' travel scheme.A polynomial time complexity algorithm is proposed for one-driver-to-one-slot matching model.For the case of multi-drivers-to-one-slot,this study prove that it belongs to NP-complete problem and then develop a two-stage heuristic algorithm to obtain an approximately optimal matching-scheduling solution within polynomial time.In the aspect of pricing,drivers' misreporting behaviors under the incomplete information assumptions is analyzed based on a Nash equilibrium game.The analysis reveals that the existing parking-time-based pricing method widely used in curbside and garage parking services leads some drivers to delay and even intentionally misreport their demand information,which results platform inefficiency.With parking heterogeneous use and slot no split assumptions,a novel truth-telling mechanism based on VCG is proposed.This study also demonstrates that the designed mechanism well satisfied also some important economic properties: allocation efficiency(AE),Incentive-compatibility(IC),individual rationality(IR),and budget balance(BB).In summary,the proposed matching rule and pricing mechanism jointly guarantee the sharing slots platform' efficiency.This research also constructs a simulation bed based on real operational data from Dingding Parking application in Beijing.The experimental results show the efficiency of the two-stage heuristic algorithm and the effectiveness of the truth-telling pricing mechanism.