摘要
本文提出了一种基于蒙特卡洛方法的汽车碰撞预警系统。本系统可以自动连续测量行驶车辆前方障碍物的速度和方位等数据,经过估计产生车体和目标的姿态,利用蒙特卡洛方法计算碰撞概率,发出适当的警报给驾驶员。仿真结果表明此算法能够比较精确地估计车辆的安全级别,产生相对准确的警报,为开展快速的碰撞预警系统的研究提供了一种可行方案。
This paper proposes an algorithm of vehicle collision warning system based on a Monte Carlo approach. The system can automatically continuous measure speed and azimuth data of the obstacles in front of vehicle, estimate the poses of vehicle and the object, then calculate the probability of collision and give a suitable warning to the driver. The simulation results show that the algorithm can accurately estimate the safety level of vehicle. and have a relativel accurate warning, this dissertation provides a method to the research of fast collision warning system .
出处
《微计算机信息》
2009年第4期197-198,26,共3页
Control & Automation
基金
基金申请人:何波项目名称:"复杂动态环境下的智能车辆安全辅助驾驶"
基金资助:山东省科学技术厅:山东省博士基金(2005BS01009)
关键词
蒙特卡洛方法
碰撞概率
车辆碰撞预警系统
安全辅助驾驶
Monte Carlo Approach（MCA）
Probability of Collision
Vehicle Collision Warning System
Safety Aid Driving
