关键词: 贝叶斯网络, 停车收费, 停车行为, K2算法

Abstract:

In this paper,first,a Bayesian network for parking behavior analysis is constructed based on the structure and parameter learning by means of K2 algorithm and Bayesian evaluation. Then,with the help of junction-tree propagation algorithm,the variations of parking starting time,parking duration and parking lot type with the parking fee are analyzed. Finally,the effect of parking pricing policy is predicted and the feasibility of the policy is evaluated. The results indicate that high parking fee may shorten the parking duration,that a disequilibrium pricing policy,that is,high parking fee for peak-period parking and on-road parking,may result in non-peak and off-road parking.

Key words: Bayesian network, parking pricing, parking behavior, K2 algorithm