聯網車隊之邊緣服務選擇與排程

Abstract

本論文重點研究聯網自駕車隊的資源選擇與分配，我們的目標為最大化車隊中最慢車速。該研究開發了一個比較函式，將同一輛車發出的所有請求合併起來，以反映其實際駕駛狀況。之後，我們探索了各種類型的車輛調度演算法，以選擇合適的車輛並要求分配相應的服務。我們還提出了一種確保車隊運行安全的方法。車輛會根據各自的速度在整個模擬過程中動態調整車輛間距，從而保持彼此之間適當的安全距離。實驗結果顯示，在共享程度較低且計算資源有限的條件下，所提出的調度方法能夠實現更高的最小速度，同時在整個車隊中幾乎沒有平均速度損失。此外，所需的總時間均維持在可行範圍內，與實際運作約束條件良好契合。

In this thesis, we focus on the task selection and allocation in platoon cases for Connected and Autonomous Vehicles. Our objective is to maximize the speed of the slowest vehicle in a platoon. To achieve this objective, we develop a comparison function that unites all requests made by the same vehicle to reflect its actual driving condition. After that, we explore various types of vehicle scheduling algorithms that select the appropriate vehicle and request to allocate its corresponding services. We also propose a method to ensure safety during platoon operation. Vehicles dynamically adjust their inter-vehicle distances throughout the simulation based on their respective speeds, maintaining appropriate safe distances between one another. Experimental results demonstrate that the proposed scheduling method achieves higher minimum speeds with little average speed loss across the entire platoon under conditions of low sharing levels and limited computational resources. In addition, the total time required remains within a practical range, aligning well with real-world operational constraints.