Research On The Supply And Demand Analysis And Allocation Model Of Motor Vehicle Shared Berths

Nowadays,the general status of parking users “seeking difficulties” reflects the problems in urban parking management.With limited parking resources,parking supply and parking demand are seriously out of balance.This not only increases the search for invalid parking by the seeking user,but also increases the added value of economic and environmental pollution caused by blindly searching around.Sharing parking service mode can break the parking information asymmetry barrier to a certain degree,to a certain extent ease the difficulties of urban parking.This article first analyzes and studies shared parking,elaborates the concept of berth sharing,and analyzes shared parking demand characteristics from the point of view of the traveler and nature of the site.By matching the nature of land use where daytime parking demand is greater than the demand for parking at night and the nature of land use where daytime parking demand is less than the demand for nighttime parking,the preconditions for sharing parking are clearly defined,and analyze the predicament of the implementation of sharing berths in the actual promotion.Second,the berth shared supply and demand characteristics are analyzed.After analyzing the personal attributes,parking attributes,and shared attributes of parked users,the influencing factors affecting the willingness to participate in sharing are studied through the structural equation model,and a berthing sharing selection behavior model is established using the SEMLogit combination model.In the aspect of supply of shared berths,the use of BP neural network and SVM to predict the supply capacity of the parking lot in the area,and through the comparison of the prediction results of the two prediction methods by examples,the forecasting method with higher prediction accuracy is used as a the data support for the shared berth service platform.Thirdly,on the basis of the analysis of supply and demand of shared berths,through the user's walking endurance limit and the shared berth supply situation in the area,the alternative shared parking lot set is determined.Through the investigation,the decision indicators for shared parking allocation are obtained.Based on the traditional decision indicators,the parking lot sharing capability index is introduced,and a grey relational-TOPSIS method-based shared parking lot is established to allocate optimal parking for shared users.Then,a shared berth allocation model is constructed from the standpoint of a shared berth service platform.Based on the objective function of sharing berth service total revenue and berth turnover rate(that is the matching pair total),consider the local user's accidental return and sharing user history rejection ratio in real-life use,introduce the local vehicle priority principle,and establish a multi-objective allocation model based on multi-user and multipleshared berths.The shared berth allocation model was solved by using the binary multi-objective particle swarm optimization algorithm to obtain the distribution result of the shared berth service platform.Finally,taking the parking lot near Lijia Village in Xi'an as the research object,through the case analysis,the utility model of shared parking allocation model and shared berth allocation model is verified.