利用魚眼攝影機預測後方車輛路線及碰撞可能性

Prediction of Approaching Vehicles to Blind Spots by Using a Rear-Mounted Fisheye Camera

周蘇剛(Su-Kang Chou)

指導教授 ： 林道通

國立臺北大學/電機資訊學院/多媒體與網路科技產業碩士專班/碩士(2016年)

摘要

駕駛在開車時需要一個安全及便利的開車環境。現代的車載安全系統已經有快速的進步也引起大眾的關注。而本研究提出的系統是從後置式的魚眼相機接收到實時的影像並且可以幫助駕駛避免許多危險的事件。研究顯示當駕駛開車時切換車道而發生的意外時常發生。因此本研究開發出用於預測車輛軌跡的系統提高駕駛的安全性。當事件或者是有風險時系統會提醒駕駛危險性。Adaboost及Kalman filter被當成是系統主要的技術。他是可以預測接近盲點的車輛以防止駕駛切換車道時後方車輛碰撞的情況。

關鍵字

卡爾曼濾波器 ； 自適應增強 ； 盲點區域 ； 碰撞預測

並列摘要

Drivers require a safe and convenient driving environment when they are driving. Contemporary vehicle safety systems have rapidly improved and gained public attention. The proposed system receives real-time images from a rear-mounted fisheye camera and assists drivers in avoiding many dangerous conditions. Research indicates that driving accidents often occur when drivers are switching lanes. Therefore, to improve driving safety, this study developed a system for predicting vehicle trajectory. When accidents are likely and risks are present, the system alerts the driver. An AdaBoost algorithm was employed for vehicle detection, and a Kalman filter was selected as the main component of the proposed system; it is an effective means for predicting the trajectories of approaching vehicles in the blind spots to prevent collisions from behind during lane switching.

並列關鍵字

Kalman filter ； AdaBoost ； blind spots ； collision prediction

參考文獻

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