My master thesis was accepted by 2017 NCS
For the past few years, many well-known companies and automakers have put a lot of effort into developing selfdriving
cars (SDCs). The SDC is undoubtedly a future trend for driving and needs various kinds of sensors to detect the nearby environment.
Additionally, it uses sensing data in order to plan actions. On most SDCs, LiDAR acts as the main sensor. However, we discovered
that the current approach to resolving a LiDAR malfunction is very passive and causes the SDC advantage to be lost. In this paper,
we propose two strategies in order to deal with LiDAR failure through V2V Communication. The aim is to recover from the
breakdown and safely drive the SDCs to their destination without human support. Finally, we validated
the performance of both strategies through simulation and provide insights for wireless networks.
Keywords: V2V communication, self-driving car, LiDAR
近年來隨著各種科技發展的成熟，自駕車不再被視為科幻電影和小
說中的幻想，許多知名公司及車商像是Google，Intel，Apple，Tesla，
BMW 等皆已積極投入自駕車研發的市場，其牽涉到人工智慧、深度
學習、先進視覺、感測、雲端處理、物聯網等多項複雜的技術，所以
要實現自駕車普及化仍需至少十年以上甚至更長的時間，然而自駕車
仍是未來汽車發展的趨勢。在運作上自駕車需要多種感測器協助偵測
周遭環境，並運用偵測的數據分析決策及行為，大部分自駕車最主要
的感測器為光學雷達(LiDAR)，但現階段對光學雷達(LiDAR) 故障的
應對方式為緊急停車並等待支援，相當被動且喪失自駕車的優勢，此
篇提出兩種機制並運用車對車傳輸(V2V Communication) 來進行修復，
目的是讓發生故障的自駕車無須人未支援便能安全的抵達目的地，最
後透過模擬, 驗證兩種機制對故障自駕車修復的效果皆能達到目標，並
分析它們對無線網路的影響。
關鍵字：車對車通訊、自駕車、光學雷達