ABSTRACT

A shared parking space optimization (SPSO) model is established to alleviate China’s parking problem considering travelers’ tiered credit risk. The SPSO model has the following characteristics: travelers’ possibilities for default are measured by credit value; travelers with different credit tiers are classified and managed; the success of the shared parking space will be affected by the traveler’s credit value. In order to solve the SPSO model, we transform it into a vertex coloring problem of an undirected graph and then modify the ant colony algorithm (ACA) by improving in two aspects of pheromone concentration and termination rule of the traditional ACA algorithm. Numerical experiments of different sizes are performed to evaluate the validity and efficiency of the proposed model. This study may cater for the deficiencies in the research of credit risk in the implementation of shared parking mechanism to a certain extent.