A System for Risk Identification of Pedestrian-vehicular Collisions and Intelligent Control
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摘要: 为了减少道路行人与车辆碰撞,智能辅助驾驶系统采用行人检测与预警方式提醒驾驶人,从而降低人车碰撞风险.但在驾驶人意识模糊时,这种方式存在一定的不可靠性.以行人检测和碰撞风险预警为基础,基于车辆动力学模型提出一种智能车辆制动控制系统.在该系统中,通过视频传感器和图像的方向梯度直方图(HOG)特征,结合SVM识别算法,在大量图像样本量的前提下对行人进行目标识别与跟踪;运用碰撞风险识别与预警算法对最危险目标碰撞态势进行实时判断;采用车辆动力学模型开发的车速分级控制器实现车辆速度的自适应控制,实现不同风险状态下的车速智能控制.实车实验结果表明,基于该方法开发的系统能够快速并精准地检测行人,动态情况下行人识别准确率达到89%;基于风险预警判断进行车辆安全平稳的紧急制动,实现危险碰撞态势下的辅助操作,从而降低车辆与行人之间的碰撞概率.Abstract: To avoid pedestrian-vehicular collision,systems for pedestrian detection and collision warning are used in intelligent driver assistance systems.However,the warning systems can be useless under impaired driving.In this study,based on a pedestrian detection system,an intelligent control system for vehicles is proposed to avoid pedestrian-vehicular collisions.First,Histogram of Oriented Gradient (HOG) and Support Vector Machine (SVM) are applied to detect pedestrians.Risk of pedestrian-vehicular collisions is predicted by using an algorithm of risk identification.Then,based on a vehicle dynamics model,speed of vehicles is adaptively controlled under different risk levels.The results show that the developed system can detect pedestrians quickly and accurately,its accuracy can reach 89% in real-time under dynamic scenes.The risk warning system can control the vehicle to take a safe and stable brake under emergencies,thus pedestrian-vehicular collisions can be effectively avoided.
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Key words:
- traffic safety /
- pedestrian detection /
- risk identification /
- speed control /
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