Modeling on Scale of Public Parking Lot Based on Parking Choice Behavior

Most past researches on determining parking scale did not consider individual driver's different parking choice behavior. This paper focuses on how to optimize parking scale while taking driver's parking choice behavior into account. Firstly, the main factors of individual driver are analyzed, including parking service radius, length of parking time, trip purpose. With analysis of data from stated preference and revealed preference parking survey, the authors conclude that service radius is a key factor influencing parking scale. Then, optimization model on parking scale is put forward in which parking choice probability is quantified by adopting logit model. In the model, parking choice probability is a main measurement of parking choice behavior. Finally, unknown parameters of the model are calibrated based on data survey and analysis. The result of the model shows parking choice probability is much higher when service radius is shorter. And parking choice probability is higher when length of parking time is longer.