當今世界各大都市都建有便利的地鐵、捷運系統，民眾可在路網中各路線間相互轉乘抵達其目的地。然而旅客並不喜歡多花時間在等車及轉車上，尤其當轉乘旅客剛到站，銜接班次卻恰好離站而無法順利轉乘，導致旅客服務滿意水準下降。因此設法安排轉乘銜接列車，使旅客能順利轉乘，減少候車時間，提升旅客滿意度，對營運者是一項重要的課題。本研究將以高雄捷運紅、橘兩線實際運轉資料為分析依據，設計一列車時刻表排班模式，使轉乘等候時間最小化。另過去轉乘議題相關文獻多僅考慮到列車於轉乘站本身的停等策略，本研究進一步考量整體路網沿線各路段的運轉安排，來達到轉乘最佳化的目標。
然而對營運者而言，為改善轉乘銜接而加密列車班距或做其他調整，會增加相關成本支出。故本研究運用列車進出端點站時需通過轉轍器的特性限制，用以計算模式解出班表的所需列車成本，以求出旅客時間與業者成本間的權衡關係。最後將本模式套用不同旅運需求、路網型態與轉乘站體設計，分析各種情境下適當之轉乘安排策略，以期能建立一廣泛通用的轉乘最佳化排班模式，提供相關軌道運輸業者未來改善其服務品質、推動無縫轉乘接駁策略之建議與參考。
模式求解結果顯示，藉由端點站出發至轉乘站沿線路段，各班列車分別調整放慢行駛速率或是延長靠站時間，即可得最少等候時間的轉乘最佳化班表，相較高捷現行班表均有相當程度的改善，尖峰時段總等候時間可減少約35%，離峰時節省幅度更可達近六成。至於利用列車端點站進出轉轍器特性，計算在該班表下各路線方向所需營運總成本，並考量與旅客時間價值間權衡抵換關係後，其結果建議若朝縮短班距方面著手，在尖峰時可調降至4分，離峰時則是以8分為佳，並應儘可能使紅、橘兩線班距相互對稱以縮短兩線之間轉乘等候時間。接下來將模式套入轉乘旅運量需求變動、各類路網型態與站體結構設計組合類型等各種不同情境下進行求解比較。結果指出班表安排隨運量需求較高的路段方向，來調整沿線各站間減速行駛，或延長停靠站時間配合各方向轉乘，以減少旅客轉乘等候時間。並針對不同路網結構，考慮各端點站發車時間差距分配及沿線運轉安排。轉乘站體結構與轉乘通道的設計型態，則會影響旅客轉乘步行時間的差異特性，同樣需列入運轉排班考量，因應各項情況下做出適當之時刻表安排調整，以提供最佳化的轉乘服務。

Nowadays, many metropolitans have a convenient subway or MRT network system by which people can travel to their destinations through transferring between different lines. However, passengers would not like to spend too much time on waiting or transferring, especially for the case of “just miss” which may decrease service quality and custom satisfaction. Therefore, trying to arrange feeder and connecting trains for proper transfer, and to reduce waiting time, is a critical issue for operators. This research designed a timetable planning model for minimized transfer waiting time based on real operating data of Kaohsiung MRT system with two lines of red and orange. Transfer related analyses in past literatures mostly focus only on transfer station itself, so in this research, train operation planning on each segment of lines in whole network would be considered.
Besides, for operators, some adjustments such as headway reducing for better transfer service could cause more costs. Therefore, this study would apply terminal restrictions for train cost calculating to find the trade-off between passengers’ time and operator’s cost. Finally, the model is also used to analyze suitable transfer arrangement under different situations of trip demands, network types and station configurations. The findings from this transfer optimizing model could be generally applied to relative railway service operations as some suggestions for transfer improvements in the future.
The model solution indicates better improvements than current timetable used in Kaohsiung MRT system. The total transfer waiting time has around 35% savings in peak-hour periods, and almost 60% in off-peak hours. While considering the trade-off between passengers’ time value and operator’s cost, reducing headway from 5 to 4 minutes in peak hours and from 10 to 8 minutes in off-peak hours is suggested. Also, making the headway differences between red line and orange line smaller is better for passengers transferring between these two lines without waiting too long. Then the model is solved under different situations of transferring trip demands, route network and transfer station configuration design types. Situation analysis results show that trains running on sections or directions with larger transferring demand could be adjusted with lower running speed or longer stopping times at stations to make train connections smoother when arriving at transfer stations. Furthermore, train departure time at terminal stations of each line should be arranged with differences subject to kinds of route network types. The configuration and walking passageways design in transfer stations, which is relevant to passenger transfer walking time variations, should also be taken into consideration when planning the train timetable. In brief, train timetable with appropriate arrangements according to varieties of conditions could provide smoother connection between different trains of each line and better transfer services.

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