即時道路監控影像串流是一種新類型的安全資料，這些資料可以透過車載網路傳送給其他終端。影像串流服務需要耗費相對大量的無線網路頻寬，因此許多車輛在同一時間內使用同一無線網路(wireless network)，將會造成無線網路壅塞(congestion)。分群技術透過限制傳送即時道路監控影像的車輛數量可以有效率的減輕網路壅塞的問題。可調式影像串流技術透過監控無線網路狀況去動態調整影像串流的輸出位元率(bit rate)，同樣也是解決上述問題的方法之一。
基於車內攝影機的有效視覺區域，在這篇論文內，我們提出基於有效視覺區域之分群與可適性影片機制之即時道路監控服務控制機制(Effective-Vision-Area-based Clustering algorithm with the Adaptive Video streaming technique)。基於有效視覺區域之分群演算法(Effective-Vision-Area-base Clustering)能夠將道路上的車輛做分群，駕駛者為了獲得即時道路監控服務所提供的額外視野，駕駛者可以加入其中合適的分群中並接收來自其分群領導者的即時道路監控資訊。接著我們根據監控的IEEE 802.11p的無線網路的使用狀況去動態的調整分群領導者所傳送的即時路況影像位元率(bit rate)，在網路壅塞(network congestion)的情況下調低即時路況影像的位元率(bit rate)。在這篇論文中，我們比較了基於有效視覺區域之分群與可適性影片機制之即時道路監控服務控制機制(Effective-Vision-Area-based Clustering algorithm with the Adaptive Video streaming technique)與其他不同的即時道路監控服務提供者的挑選機制來呈現我們提出方法的成效。

Live Road Surveillance (LRS) video streaming is a new type of safety data that can be transmitted in Vehicular Ad Hoc Networks (VANETs). Video streaming is a high-bandwidth-demanded service and causes network congestion if there are many vehicles that stream video in the wireless network at the same time. Clustering is an efficient technique to relieve network congestion because it can reduce the number of vehicles to transmit data. The adaptive video streaming technology can also relieve the aforementioned problems based on monitoring the wireless network’s utilization situation. Based on the effective-vision of the cameras in vehicles, an Effective-Vision–Area-based Clustering algorithm with the Adaptive Video streaming technique (EVAC-AV) for LRS service is proposed in this thesis. EVAC can construct clusters such that a driver X can join a suitable cluster to get the LRS service from the appropriate vehicle ahead of X to have additional vision. Additionally, based on the IEEE 802.11p wireless network’s utilization condition, the adaptive video streaming technique is adopted to have adaptive LRS video quality in EVAC-AV. In this thesis, we compare the proposed EVAC-AV control scheme for LRS service with other clustering algorithms and other LRS service schemes that do not adopt the clustering mechanism in term of different performance metrics to show the effectiveness of the proposed work.

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