IoT-Enabled Parking Space Sharing and Allocation Mechanisms

This paper is among the first proposing an integrated auction and market design method for the parking space sharing and allocation problem. Drivers (agents) who fail to exchange their own parking spaces can then rent them to the platform. The platform receives private parking spaces from agents and manages some public parking spaces. We first develop the urban parking management cloud platform through Internet of Things. Based on this systemic framework, parking spaces are shared among agents via a price-compatible top trading cycles and chains (PC-TTCCs) mechanism and the platform's parking spaces are reassigned via a one-sided Vickrey-Clarke-Groves (O-VCG) auction. Both the PC-TTCC mechanism with rule e (PC-TTCC [e]) and O-VCG auction are effective in terms of strategy-proofness and (allocative or Pareto) efficiency. In the PC-TTCC [e] mechanism, the platform's payment rule used in private parking space sharing is determined based on historical O-VCG auction prices. Our experimental results further show that the proposed mechanism results in system profitability of 20%-30% and ex post budget balance for the platform. Note to Practitioners - This paper was motivated by the problem of constantly climbing parking needs in major cities. This paper suggests a new approach for intelligent parking space sharing, allocation, and pricing from the integrated market design and auction perspective based on Internet of Things/cloud technological architecture. The proposed mechanisms are effective in terms of strategy-proofness and efficiency, leading to remarkable system profitability. Reasonable agents' cost saving, bidders' value, and ex post budget balance for the platform can also be guaranteed in a big city with larger population. Several key managerial implications have been gained. First, a public platform should choose the integrated mechanism that realizes higher agents' cost saving. Second, agents should be encouraged to rent their private parking slots to the platform for reaching more agents' welfare. Third, the platform should leverage his owned public parking spaces to achieve higher system profitability and agents' cost saving. Fourth, compared with Vickrey-Clarke-Groves auction, the simpler first-price auction may lead to higher cost saving for agents in some cases even if it cannot realize allocative efficiency and incentive compatibility. Finally, the platform's profit will increase and the agents' cost saving will decrease with the percentage of no show. Preliminary simulation experiments suggest that this approach is feasible but it has not yet been incorporated into a prototype system nor verified in real-world applications. Regarding future work, some other factors such as transaction costs, parking uncertainty, and release of traffic congestion can be included in the proposed mechanism. Our integrated price-compatible top trading cycles and chains [e] and one-sided Vickrey-Clarke-Groves mechanisms can exploit the allocation and pricing problems in B2B e-commerce logistics, on-demand traffic fleet management, and ridesharing optimization.