Mall Parking Lot Driverless Vehicle Service Quantity Optimization Setting

Providing travel services for unmanned vehicles in the future is a foreseeable form of transportation.Under the mode that people travel by buying travel services,the mall in order to attract more consumers,consumers must be guaranteed timely travel services.Under the circumstances,the shopping mall parking lot needs to provide suitable unmanned vehicles according to the consumers’ travel conditions,so as to guarantee the timely satisfaction of travel demand,especially during the peak period.Therefore,this article first comprehensively analyzes the differences between the provision of travel services by unmanned vehicles and existing taxis and car rental services.Based on this,it is assumed that after the driverless vehicles provide travel services,people will not When buying a private car,whether it will go to the shopping mall mainly depends on whether the self-driving vehicles owned by the mall’s owned parking lot can provide timely travel services.Then,taking the underground parking lot of Qiaobu Bay Shopping Center in the suburbs of Shanghai,Qingpu District,as an example,the vehicle parking data of the parking lot in June 2016 was analyzed.The comprehensive analysis of the data obtained the dynamic parking feature of the shopping mall parking lot.A parking operation index system was constructed,and a queuing theory method was used to establish a model of the vehicle arrival rate and export service rate of an underground parking lot for a shopping center dedicated to unmanned vehicles over time.Based on this model,the actual underground parking lot of the shopping center was integrated.The parking lot data shows the optimal number of vehicles that should be provided in each unit time during the peak period using the queuing model for different service time assumptions,and draws the corresponding peak arrival rate using MATLAB software.Arrival time and departure time,waiting time and dwell time chart under the premise of setting of service rate and export quantity.The main work and research results of the paper are:(1)Analyzed the data of the parking lot entering and leaving the parking lot of the underground parking lot in the suburbs of Shanghai,built the evaluation index system of the parking lot operation based on the parking lot big data,and obtained the regularityof the parking lot vehicle entering and leaving the parking lot,reflecting the index system Out of the problem of parking operations to propose feasible solutions;(2)Combine the shopping center with the driverless vehicle to analyze the existing rules for entering and leaving the parking lot in the parking lot of the shopping mall,and use the queuing theory to establish an underground parking lot for shopping centers dedicated to driverless vehicles.Models of vehicle arrival rates and export service rates over time;(3)Using the queuing model,based on the data of the underground parking lot out of the actual shopping center,the queuing model was used to study the relationship between the optimal number of vehicles that should be provided during the peak period and the arrival rate and service rate in the peak period.