雪山隧道為宜蘭聯外的交通動脈，然而自開通以來，每逢假日便湧現大量旅遊旅次，交通需求量遠超過雪山隧道容量高達2倍，為舒緩雪山隧道壅塞問題，國道高速公路局曾針對最高及最低速限進行調整、精進疏導行為及舉辦競賽廣納民意等可行方案進行研擬，以期提升雪山隧道服務流量，使用路人旅程更為順暢。過去轉向行為相關研究因替代路線資料取得限制問題，多以問卷發放方式進行資料蒐集，故本研究期望以e-Tag實際偵測車流資料進行研究，提出舒緩雪山隧道壅塞方法，以供相關單位作為參考依據。 研究使用國道高速公路局提供之e-Tag實際車流資料搭配資訊可變標誌資料進行分析，針對主要路線國道5號及替代路線台9線進行轉向行為研究，再以二元羅吉特迴歸為研究方法對資料進行配適，探討在不同車流條件及資訊可變標誌顯示訊息下影響駕駛人轉向程度。 研究結果顯示主要路線旅行時間、轉向交通量及資訊可變標誌顯示旅行時間資訊與改道機率成正比關係；替代路線旅行時間及總通過量與改道機率成反比關係；在主要路線壅塞的情境下，變動可控制變數，如:轉向交通量、資訊可變標誌是否顯示旅行時間，改道最大機率為0.2605。 ;Hsuehshan tunnel is artery link with Yilan and Taipei, but since opening, there be a large number of tourist trips every holiday, the traffic demand is far more than 2 times capacity of Hsuehshan tunnel. In order to alleviate the congestion problem , Taiwan Area National Freeway Bureau has been adjusted the maximum and minimum speed, improved traffic relieving measures and held a contest to publicize and other feasible programs to develop, try to enhance the capacity of Hsuehshan tunnel and make driver’s journey more smoothly. In this study, it is expect that the e-Tag will use to detect the traffic data, and put forward for the relevant units. Based on the analysis of changeable message sign information and e-Tag data provided by Taiwan Area National Freeway Bureau, the paper chooses the route selection behavior for the main route of Chiang wei-shui memorial freeway and the alternate route of the 9th Taiwan provincial road. Then use the binary logistic as the research method to discuss driver′s path selection under different traffic conditions and changeable message sign display. The results show that the main route travel time, diversion traffic volume and changeable message sign displays information of travel time is proportional to the probability of diversion probability. The alternative travel time and total traffic volume are inversely proportional to the diversion probability. In the case of main route congestion, change controllable variables, such as diversion traffic volume, changeable message sign displays information of travel time, the maximum diversion probability is 0.2605.
