進行都市規劃、運輸規劃時，需藉由觀察及分析活動、使用情形，了解議題癥結點，以建立有效且較低環境衝擊之策略。近年隨著各種智慧裝置、定位系統和偵測器的發展，透過這些裝置可詳盡地記錄都市中的活動與旅運行為，解決傳統調查方式成本過高的問題。
公共自行車系統以自動化方式提供使用者可快速地於租借站借、還自行車，進行中短程的旅運行為；亦可用於整合都市中不同的運輸系統，尤其綠色運具，如軌道運輸、公車等。系統自動化除了便民外，同時可記錄系統中每次租借的資訊，包含借、還車時間與地點。過去亦有許多文獻利用租借資料探討公共自行車使用者行為及影響因子。
本研究以高雄市公共自行車系統（C-bike）2016年作為研究範疇，利用巨量之租賃資料進行分析彙整，結合土地使用，將各租借站分類，並歸納行為規則，藉此建立公共自行車系統使用者旅運行為之多主體模擬模型。進行10日之模擬後，模擬結果顯示，模擬模型能夠反映與實際高雄市公共自行車系統使用行為，總使用量於模擬結果與實際情形僅相差1.5%內，各站租借量與歸還量亦達到正確率92%與70%，租借型態分別有97%與70%達到高度相關。
本研究所建置之模擬模型將能夠有效幫助模型操作者直接觀察、了解公共自行車之使用分布與活動情形。操作者亦可設定不同情境，嘗試不同政策之情境模擬，並可記錄及匯出模擬之使用紀錄，以供分析與進行比較。

The bike-sharing systems(BSS) provide users with the ability to pick up and return bikes quickly from docking stations, and also be used to integrate different transportation systems in the city. BSS not only provides more convenient services, it also records rental information in the system. There has been some literature to explore the travel behavior and the factors that affect the users’ behavior of BSS.
After inducting the rule of travel behavior of users based on operation data of BSS in Kaohsiung city (C-bike), this study establishes the simulation model with agent-based model. After simulating 10 days’ data, the results show that the simulation model can properly reflect the actual users' behavior. The difference in total amount in simulation results and actual situation is only 1.5%. In the simulation results, 92% and 70% of the docking stations are comparable to the actual pickup and return amount. The pattern of pickups and returns are also high correlated with actual situation.
The simulation model built in this study can help planners to observe and understand the distribution and activity of public bicycle. Planners can also test different policy scenarios, and record and export the simulation records for further analysis and comparison.

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