Study On Lane Detecting Technique In Intelligent Vehicle

Aiming at the safety problem of vehicle driving, this thesis focuses on the following topics in a vehicle initiative safety system using information processing technologies and smart agent technologies: the dynamic model of safety during steering, the components and models, the information acquisition in real-time and avoiding collision in steering.At the aspect of vehicle safety, the vehicles safety related problems are explored briefly. The intelligent traffic system and the safety system to preventing collision are discussed also. In addition, the research content of vehicle initiative safety system is analyzed.This paper mainly discusses the road recognition technique based on monocular vision in detail. There are two ways for road recognition. One is whole road method and the other is lane detecting method. For the whole road method we introduce a technique using region growing to locate the road, and we have discussed the problem of choosing seed and the rule of growing.For highway vision navigation, we give more attention to the lane detecting method. Firstly, we present a direct method based on edge tracking, based on chain code and trend of the lane slope. And then we do some research on the statistics way assited with Hough transform to get the lane edge and curve direction which does a good performance on lane detecting.On the other hand, we also do some research on the model ways to describe the lane. And we do some processing to it considering the real circumstance In the end, after absorbing the advantages of the model and searching way, we give out a method with combining the Median of the Intercepts and spline to construct the lane separately. This way has some advantage to overcome the hydrocele, shadow, low contrast and it is able to fit any kind road type. It is a way with high accuracy, real-times and robustness, which ensure the navigation.