基于视觉的缩微智能车车道检测与控制

针对智能车辆自主驾驶行为研究,提出并实现了一种基于视觉导航的缩微智能车系统.从软硬件架构、数据通信方式上介绍了缩微智能车系统的整体设计,并针对缩微道路交通环境中传统车道线检测技术易受光照变化影响的问题,提出一种灰度形态学Top-Hat变换与亮度轮廓扫描方法相结合的车道线检测算法.为分析智能车在缩微交通环境下的自主驾驶表现,设计了一种模拟驾驶员转向行为的舵机模糊控制算法.实验结果表明,该方法可以有效模拟车辆在真实道路交通环境中的自主驾驶行为,为智能交通系统研究提供了一种新思路.

Lane Detection and Steering Control of Vision-Based Micro-Intelligent Vehicle

Abstract： To study the autonomous driving behaviour of intelligent vehicles, a visual navigation based micro intelligent vehicle system was proposed and implemented in this paper. The frame of the proposed system was introduced from the aspects of the hardware/software architecture and the data communication scheme. The performance of the traditional lane detection method is very limited in the micro road traffic environment with illumination variations. In the proposed approach, a gray scale morphology top hat transformation and brightness profile scan based lane detection method was introduced to conquer this problem. To analyze the autonomous driving behaviour of intelligent vehicles in the small scale traffic environment, a fuzzy based steering control algorithm was designed for simulating the behaviour of drivers. The experimental results show that the proposed scheme is able to effectively simulate the autonomous driving behaviour of vehicles in the real environment, and provides a new approach for the research of intelligent transportation system.