| At present,the autonomous vehicles(AVs)industry develops rapidly at home and abroad,and gradually from the assistant driving stage to the self-driving stage,which has become an important trend in the development of the automobile industry.However,the development of AVs has also given rise to many complex issues,especially the parking management of AVs.In recent years,with the development of mobile internet technology and sharing economy,urban parking space sharing has gradually become possible.The integration of autonomous driving and shared parking will constitute a new mobility model of the future.Therefore,this paper focuses on the operation and management of shared parking under different development stages of AVs,studying its reservation allocation mechanism and pricing scheme,and analyzing the impact of AVs on the operation and management of shared parking at different development stages,providing a theoretical reference for the future operation and management of shared parking in cities,which has practical significance for alleviating the problem of urban parking difficulties.The specific research content of this paper is as follows.First,based on the characteristics possessed by AVs under different stages of development,we analyze the parking modes of AVs covered by different stages.From the perspective of travelers’ costs,the parking choice behaviors of AVs is analyzed,and a comparative analysis of the advantages of the shared parking choice of AVs is made.Second,aiming at the problem of optimal allocation of urban shared parking spaces in the phase of assistant driving,firstly,the parking users are subdivided into long-term and short-term parking users,pricing different types of parking users with the idea of differential pricing.Combined with the information on the supply and demand of shared parking spaces,a shared parking space allocation and pricing model considering differentiated pricing is proposed,and a sensitivity analysis of the model is carried out.The case study shows that the segmentation of parking users can improve the utilization rate and turnover rate of the platform,and further increase the operating revenue of the platform.In addition,the model can regulate parking demand and effectively curb the amount of long-term parking demand in city centers.Therefore,parking management measures need to be designed according to the temporal characteristics of the platform’s service users in order to improve the service level of the shared parking platform.Then,a shared parking space allocation model for fully self-driving vehicles is proposed for the optimal allocation of urban shared parking spaces in the fully autonomous phase,taking advantage of the fact that AVs are capable of valet parking under unsupervised conditions,and allowing a single parking demand to be served by multiple parking spaces in sequence during the allocation process.From the point of view of minimizing the times of changing parking spaces,the penalty term of changing parking spaces is introduced in the model,which can also be understood as differential pricing of platform.The case study shows that the operational revenue and space utilization of the shared parking platform reaches a maximum at a faster rate compared to the assisted driving phase in Chapter 4,and the request acceptance rate of parking users is significantly improved.Finally,an optimal allocation model of urban shared parking spaces for the transition phase of autonomous driving is further constructed to explore the optimal allocation of shared parking spaces under different penetration rates of fully self-driving vehicles.The case study shows that the penetration rate of AVs is positively related to the space utilization rate,platform revenue and request acceptance rate of the shared parking platform.In addition,an excessively high value of change of parking space penalty will reduce the platform’s operational revenue and parking request acceptance rate.Figures: 31;Tables: 18;References: 67. |
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