Shared bicycles have played an active role in solving the “last mile” problem of urban transportation and alleviating urban traffic congestion. However, if the parking facilities of shared bicycles are not properly selected, it will not only affect urban traffic, but also reduce service satisfaction. Based on the actual running data of shared bicycles, this paper analyzes different characteristics of the shared bicycle travel. The DBSCAN density clustering method is selected as the identification method of shared bicycle travel demand points. The DSR model is introduced to build the evaluation model of the parking point supply of the shared bicycle. This article will help shared bicycle companies in the construction of shared bicycle supply and demand facilities, and appropriately optimize urban slow traffic. Keywords: shared bicycle; demand point identification; DSR model; evaluation model

CICTP