隨著殘障人口旅行需求的增加，需求反應式運輸（DRT）已成為近年來流行的研究主題。目前為止，許多 DRT 服務仍透過人工調度，這導致服務效率低下，並且無法處理動態事件。本研究使用了一種代理人模擬的方法，該方法透過定義了車輛的決策行為及乘客代理人的互動以模擬動態撥召問題。我們應用基於代理的模擬來分析不同的分區設定方案，選擇策略和乘車共享條件等。結果證實我們的模擬可以找到有效的策略組合。此外，我們提出的分區設定方案提供了與沒有分區限制的情境下相近的表現，可供營運單位參考。

As the travel needs of people with disabilities increase, demand response transit (DRT) has become a popular research topic in recent years. Currently, many DRT service is still using manual scheduling, which leads to inefficient and is not able to deal with dynamic events. This study proposes an agent-based method that defines the vehicle's decision-making behavior and passenger interaction to simulate dynamic DARP. We apply agent-based simulation to analyze different zonal restrictions, selection strategies, and ride-sharing conditions, etc. The results confirm that our model can find the efficient strategy combination. Our proposed zoning restriction scheme also presents a performance close to the scenario without zonal constraint, providing operators with a reference.

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