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  • 學位論文

基於站點相依性之公共自行車調度策略研究

Logistics Strategies for Public Bike Sharing Systems based on Dependency of Rental Stations

指導教授 : 張學孔

摘要


近年來環境變遷一直是全球共同關心的焦點,各國積極推動利用低碳、高能源效率、以及新能源的交通方式,期能降低交通運輸部門的溫室氣體排放。在這樣的背景下,許多國家致力推動綠色交通(Green Transport)與生態行動力(Eco-Mobility),而在法國、荷蘭、德國、丹麥等,開始於都會區設置公共自行車系統,不僅具城市休閒與娛樂功能,更提供都市公共運輸之第一里及最後一里接駁服務。自2007年開始,台灣許多城市也開始建置公共自行車系統,並改善騎乘環境,近年來在使用率的卓越成果已經獲得國際肯定。 隨著公共自行車系統蓬勃發展,自行車路網的擴大以及使用人數的增加,熱門時段容易出現「無車可借」以及「無位可還」的狀況。因此,如何進行適切的調度以平衡各站自行車數量與空位數,讓整體使用率與服務品質提升,實為公共自行車與整體綠色交通發展的重要課題。 本研究發展一套以同區車輛借還高相依站點為基礎的調度策略,並以台北市「微笑單車」開放資料庫數據為應用範例,利用資料探勘中關聯規則的分析技術,找出具高度借還車相依特性之租賃站群並作為調度群集的劃分方式。接著對此群體內站點使用特性進行數據分析,並對現階段營運服務狀態與調度機制進行比較研究。基於上述分析結果,本研究擬定「原始公共自行車調度原則」、「車輛流向比例原則」、以及「車輛流向與集群補償原則」等三類調度策略,並建置最佳化數學模型進行評估。模式評估結果顯示,本研究擬定之調度策略具有顯著成效,可供於未來業者調度策略之參考。

並列摘要


Over this past couple of years, environmental changes has long been controversial issue for many countries. Many countries contribute a lot in promoting transportation with high energy efficiency and low carbon emission, or even new energy source. For this reason, many advanced countries make efforts in promoting Green Transport and Eco-Mobility as well as providing public bicycle system like France, Netherland, Germany and Denmark. This not only provides first mile and last mile interchange for public transport but also acts as recreation. Since 2007, Taiwan has started the public bicycle system and kept improving the road condition. Up to now, the high turnover rate has been recognized all over the world. With rapid development of public bicycle system, the bicycle network is expanding with increasing users. However, “Insufficient amount of bicycle to be borrowed” and “Insufficient Parking Space” occurs frequently during the rush hours. To solve with this difficulty, Reposition Strategy is necessary in balancing the bicycle amount and parking space which becomes a main issue developing the green transport. This research utilizes Taipei Youbike open source, developing biking reposition strategies for public bicycle system based on high dependency, especially for high turnover stations. The next step uses data mining approach for finding high turnover rate of rental station as adoption of repositioning strategy. The analysis is based on the riding habit with parking pattern and review the existing operation and reposition strategy. Based on the aforementioned results, the research adopts 3 repositioning approaches: (1) Improvement on existing reposition approach, (2) Reposition strategy based on bicycle flows, (3) Reposition based on bicycle flows with collective compensation. The final step utilizes optimization model for further evaluation works. The final result proves that the approaches make great improvement in repositioning, which can be act as reference for future operators.

參考文獻


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