Study On The User-oriented Before-trips Urban Parking Choice Model

In recent years, the car ownership in large and medium cities in China growsrapidly, at the same time, parking problems are increasingly prominent. Unimpededurban traffic needs coordinated development between static transport and dynamictransport, and static traffic’s reasonable guidance have a well auxiliary effect on thedynamic traffic’s smooth running. Parking Guidance Information System which leadsthe solution of parking problems to a intensive development of improving the overallrate of urban parking facilities, as an important part of an Intelligent Transport System,plays an increasingly important role.in static transport.Through the current situation of domestic and international PGIS’ s application andits development of the future trend, The construction of active guidance’s before-tripssubsystem with the many of the parking will, which makes travelers’ parking moreconvenient and feasible, is a main area of the future study; However, the existing studyaiming at the related theory of parking choice model which is an important link inbefore-trips subsystem is very limited and the further study on indexes’ election withrespect to the model’s construction and its simplication algorithm is needed.Based on rational analyses and primary selections which is got by F clusteringmethodology resulted from the evaluation indexs of parking facilities’ selection,travelers’ parking choice behavior is obtained to decide the parking choice’s evaluationindex through specific parking intention questionnaire survey.Having analysed calculation ideas of specific influence factors(evaluation indexs)on parking choice and its role in parking choice model. We build a before-trips parkingchoice model orienting the users with the purpose of optimally comprehensive wishes.Taking the solution of the model as a decision process of multi-attributes and basing onstudying each evaluation index’s optimization algorithm, the passage which usesobjective and subjective synthetic approach to determine weights method based onnegative ideal solution’s objective to assign the weight to each evaluation index andreplaces grey relation with weighted deviate degree based on negative ideal solutionsimplify and improve gray entropy decision method to apply to the choice of preferredparking scheme. Using BP neural network to predict the parking space share, theparking programme is finally selected. Comparing the before-trips parking choicemodel with other parking choice models in the ways of model’s construction andalgorithm, we evaluate advantages of this model. Taking Chongqing Northern New District’s parking choice progress as an example,the pratical value of this model is proved. Comparing gray entropy decision method’scalculated results before and after improvement, the feasibility of the model’s algorithmis demonstrated. Aiming at the research of before-trips parking choice model, a kind ofthought on Before-trips subsystem’s user oriented parking decision is provided, whichhave a theoretical value to the study of parking choice behavior.