車載網路可以透過車輛間訊息的交換，以提高駕駛的用路效率與行車安全。為了提升車載網路訊息傳遞的成功率，許多研究利用路側單元協助傳遞訊息。然而，路側單元佈署與維護的成本昂貴。因此，如何適當地使用路側單元並達到較佳的傳輸效能已成為新的研究議題。
在這篇論文中，我們將基因演算法(Genetic Algorithms, GA)應用在車載網路上的路側單元佈署。期望能透過基因化佈署問題，在佈署相同路側單元的數量下，找出封包傳輸效能最高的佈署位置。本論文使用真實城市地圖進行模擬實驗，藉由實驗證明演算法的效能。數據結果顯示，經由基因演算法運算出的路側單元佈署位置有效地降低封包遺失率。而比起其他路側單元佈署演算法，基因演算法的結果擁有較佳的封包傳輸效能。

The growing interest in wireless VANETs has prompted greater research in recent years. In order to enhance the VANETs connectivity in city scenarios, the infrastructure points known as Roadside Units (RSUs) may be used to assist the traffic packets. However, the RSUs’ deployments and maintenance have an associated cost. Identifying the optimal RSUs deployments becomes a novel issue.
In this paper we use Genetic Algorithms (GAs) to solve the problem of RSUs deployments on vehicular networks. Given a number of RSUs to be placed, our approach aims to find the optimal deployment. By means of simulation we assess the efficiency of GA. Experimental results show that optimal deployment can reduce the packet loss rate effectively. Compared with other deployment algorithm, GA has higher connectivity.

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