公共自行車因甲租乙還的時段性不對稱需求，往往造成租賃站一車或一位難求。為有效掌握此現象，本研究構建時空分析模型，採六步驟與五指標界定缺車熱點與缺位熱點，並探討各該熱點之特性及自行車使用率與熱點間的關聯。本研究以台北市公共自行車系統為例，依據時空模型搜尋平日與假日缺車與缺位熱點，並以現況使用型態為基礎，分析不同自行車使用率下的熱點指標，發現使用率在 60%~70%時系統可維持最高的正常營運比例，使用率過高或過低皆會造成租賃站缺車或缺位的問題。文末提出相關營運建議及後續研究方向。

Due to imbalanced rental demand, public bike stations confront such issues as few bikes or few parking slots available. This study builds a temporal-spatial model to capture the above hot spots via 6 steps and 5 indicators. Operational characteristics of the hot spots were assessed based on a case study of Taipei U-bike. It was found the preferred bike utilization would be around 60%~70% to remain a well-functioning system. Conclusions and suggestions were made at the end for future research.