| Summary: | 碩士 === 國立臺灣大學 === 工程科學及海洋工程學研究所 === 97 === In recent years, Intelligent Transportation System (ITS) has drawn more and more attention in the world. The goal of ITS is to improve traffic safety and to reduce transportation times and fuel consumption of vehicles. Vehicle Active Safety System (VASS) is one subject of ITS. By different kinds of sensors mounted on vehicles, it can collect surrounding messages and notice drivers to avoid potential hazards. Our objective is to research and develop an intelligent Driver Assistance System (DAS), which is one kind of VASS. This system utilizes a monocular camera mounted on the experimental car, and applies computer vision and image processing techniques to detect lane markings and front vehicles. In the lane detection section, we combine three lane markings features: brightness, slenderness and continuity to design our algorithm. In the front car detection section, shadow beneath a car, vertical edges of car sides and taillight positions are used to recognize front car positions in daytime and nighttime respectively. In order to evaluate the relative distance of objects more exactly, we address an automatic camera calibration method based on the vanishing point location. The experimental results show that the recognition rate of lane detection approximate 99% and the recognition rate of front car detection is about 96%. It is concluded that the proposed recognition algorithm works effectively and very well.
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