افزایش استفاده از سیستم های به اشتراک گذاری دوچرخه عمومی با استفاده از اطلاعات اضطراب بازگشت

To prevent the decline of the reference value of real-time bike information caused by large numbers of users, we collect the number of bikes near stations and real-time information in bike stations to form return anxiety information. When a station is nearly full or there are many bikes near the station, the return anxiety information value will increase. When users enquire about returning bikes to stations, they can refer to the return anxiety information. The higher the return anxiety information value, the lower the user’s tendency to return the bike. In the implementation, our study develops an android application to collect basic data and uses a Petri Net to simulate the PBSS scenario. Various rates of user trust are used to verify the reference value of return anxiety information.