基于流量预测模型的共享单车动态定价策略研究

共享单车有利于解决城市居民“最后一公里”的出行难题,为居民出行提供了很多便利,近年来取得快速发展。但是由于共享单车交通出行存在“潮汐现象”,导致车辆分布不均衡,并且大多采用无桩式停放方式,使用者在设置的停放区域周边随意停放即可还车,这也带来了诸如共享单车“乱停乱放”“调度成本高”等一系列问题。本文通过调查问卷数据分析建立共享单车流量预测模型,从而根据流量预测结果设计动态定价策略。该策略在保证共享单车企业收益增加的情况下,可以调控共享单车出行分布,使得车辆分布更加均衡,一方面可以缓解在部分区域停放过多而有些区域则没有车辆停放而带来的“乱停乱放”问题,另外一方面,也可以提高共享单车的使用效益,降低车辆调度成本。

Shared bicycles help to solve the“last 1 km”travel problem of urban residents,providing a lot of convenience for residents to travel,and have achieved rapid development in recent years.However,due to the"tidal phenomenon"in the shared bicycle traffic,the distribution of vehicles is uneven.Most of shared bicycle companies adopt the dockless parking mode which allows users to park and return the bicycle around the set parking area at will,which causes a series of problems such as"random parking"and"high scheduling cost",etc.Through the analysis of questionnaire data,this paper establishes a shared bicycle traffic flow prediction model,and designs a dynamic pricing strategy according to the traffic flow prediction results.The strategy can guarantee the revenue increase of the shared bicycle companies while regulating and controlling the distribution of the shared bicycles to make them distributed more evenly.On the one hand,it can alleviate the"random parking"problem caused by excessive parking in some areas and no parking in other areas.On the other hand,it can also improve the use efficiency of shared bicycles and reduce the cost of shared bicycle scheduling.