人工智能和物聯網的進步使得自動駕駛汽車的商用化越來越有可能。隨著自駕車的普及，當前的交通問題，如油耗、擁堵、和高事故率都能夠得到解決。自治交叉口管理（AIM）就是一個例子，利用自動駕駛汽車的高精準度來提高自動駕駛汽車在單一交叉口的效率。然而，在一個由多個相互關聯的交叉口組成的系統中，只是通過改進單個交叉口並不能達到系統的最佳化。因此，我們延伸單個交叉口到複數路口的場景，並提出一種新的車輛繞線方法。此方法結合了自駕車的特性和傳統的繞線演算法來實作自駕車的路徑規劃，並且通過模擬未來的路況來智能地避免擁塞從而實現系統最優化。

Advancements in artificial intelligence and Internet of Things indicates the realization of commercial autonomous vehicles is almost ready. With autonomous vehicles comes new approaches in solving some of the current traffic problems such as fuel consumption, congestion, and high incident rates. \textit{Autonomous Intersection Management} (AIM)\cite{dresner2008multiagent} is an example that utilizes the unique attributes of autonomous vehicles to improve the efficiency of a single intersection. However, in a system of interconnected intersections, just by improving individual intersections does not guarantee a system optimum. Therefore, we extend from a single intersection to a grid of intersections and propose a novel vehicle routing method for autonomous vehicles that can effectively reduce the travel time of each vehicle. With dedicated short range communications and the fine-grained control of autonomous vehicles, we are able to apply wire routing algorithms with modified constraints to vehicle routing. Our method intelligently avoids congestions by simulating the future traffic and thereby achieving a system optimum.

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