在一般的無線車載網路中，因為車子的移動速度較快，使得拓樸變化快速，接觸中斷常常發生，車流密度的變化也很大，造成車輛之間的多跳傳輸是非常具有挑戰性的問題。近年來隨著自動駕駛汽車的技術逐漸成熟，可預見將來車載網路當中大多數車輛將會是自動駕駛汽車，成功大學可靠計算實驗室因而推動自動車網路技術（ADVENT）計畫，研發相關的技術與應用。自動車網路的最重要的特性是可以很精確的預測未來車子的軌跡與位置。因此，在此篇論文當中提出了一個自動車網路中利用軌跡資訊預測未來鄰居以增進資料傳輸效率的傳輸協定，利用所有自動駕駛汽車的軌跡與時間預測資訊辨認出每台車子的未來鄰居，並分析這些未來鄰居的幫忙傳輸封包的能力，以產生一個傳輸序列。當這些車輛需要傳送封包給目標車輛時，便會依據其傳輸序列來轉送封包。模擬結果顯示TFNP在自動車網路當中相較於其他協定，能達到更高的傳輸成功率與更低的傳輸延遲。

In VANETs, vehicle-to-vehicle communication is challenging due to fast topology changing, frequent disconnections, and highly variable traffic densities. Some researchers have envisioned that most of the vehicles in the network will be autonomous vehicles in the near future. Dependable Computing Lab in National Cheng Kung University proposed a project, Autonomous Driving VEhicular Networking Technology (ADVENT), for related technologies and applications. The most important characteristic of autonomous driving vehicular environments is that nearly perfect future position prediction of vehicles may be achieved. In this paper, by leveraging the trajectory information of autonomous vehicles, a Trajectory-based data Forwarding scheme with future Neighbor Prediction (TFNP) in autonomous driving vehicular environments is proposed. With trajectory information of all autonomous vehicles, future neighbors of each vehicle are identified. Then the capability of each future neighbor to help forward packets is evaluated, and the forwarding sequences are thus constructed. Finally, when an autonomous vehicle has some packets to forward, it sends packets according to the forwarding sequence. The simulation results demonstrate the effectiveness and efficiency of the proposed scheme in autonomous driving vehicular environments.

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