在大多數的都會地區，交通阻塞是一個重要的問題，使駕駛人需花費相對較長的時間到達其目的地。利用車用隨意網路技術，本篇論文提出了一個名為STN的動態導航協定，讓駕駛人能找到時間上有效率的路徑到達其目的地。當車輛欲規劃路徑時，其向距離最近的路側存取點發出需求封包。根據比對服務使用者所分享出的行駛軌跡資訊（Trajectory Information）以及行經路口時間資訊，中央伺服器可以預測所有可能行駛路徑上未來將遭遇的交通流量，並藉由流量及基本的路段特性資訊（如路段長度、最高速限、擁塞密度等），更進一步估測各路段上行駛的速度及所需的行駛時間，而得到最符合時間效率的路徑。除此之外，本篇論文亦提出調整、更新及重新規劃路徑的機制，來維護中央伺服器端的資料準確性，減少預測的偏差。模擬使用包含20 條道路的真實道路地圖來驗證其效能，結果顯示，STN 能以較短的行駛距離來達到比VAN 導航協定更短的行駛時間。

Nowadays, traffic congestion arises to be a very serious problem especially in metropolitan cities. It makes drivers to spend more time to their destinations. In this work, by leveraging the techniques of Vehicular Ad-hoc Networks (VANET) a dynamic navigation protocol, called STN, is proposed for individual vehicles to find time-efficient paths toward their given destinations. The trajectory information of vehicles is maintained in server to assist the planning of navigation path. In STN, a source vehicle sending a request message toward nearest access point to acquire the driving path. By comparing the trajectory and time information in the system, the future traffic load can be predicted. The traffic load information enables the server to estimate driving speed within different paths toward the destination and then further get a time-efficient path. In addition, adjustment, update and re-plan mechanisms are proposed to reduce the deviation of prediction. To evaluate its performance, the real road map of Shalu, including 20 road segments, is used. The simulation results demonstrate that STN, on average, could save around 14% driving time, compared to traveling along the vehicle-assisted shortest-time paths under density 40.

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