摘要
提出了一种基于车辆行为识别的汽车前方碰撞预警方法.利用单目视觉,首先采用基于梯度方向直方图特征和支持向量机的方法识别前方车辆,并结合卡尔曼滤波进行车辆跟踪;然后使用隐马尔科夫模型对车辆行为进行建模,识别前方车辆行为,并根据行为识别结果计算对应的风险评估因子;最后将风险评估因子引入碰撞风险评估系统,使碰撞预警时间比未加入风险评估因子平均提前2.04s.实车实验验证了本方法的有效性.
A collision warning system was proposed based on the forward vehicle behavior recognition method.Based on the monocular vision,the support vector machine (SVM)classifier was applied based on histogram of oriented gradients (HOG)feature for vehicle detection,and the Kalman filter was applied for vehicle tracking.Then the hidden Markov model (HMM)was used for vehicle behav-ior recognition.According to the vehicle behavior recognition result,the corresponding risk assess-ment factor was calculated,which was considered in the risk assessment system,and the performance of the collision warning system was improved by 2.04 s compared without the corresponding risk as-sessment factor.Finally,the effectiveness of this forward vehicle behaviors recognition system was verified using real-word on-road data.
出处
《华中科技大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2015年第S1期117-121,共5页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金
国家自然科学基金重大研究计划资助项目(91420101)
国家自然科学基金资助项目(61174178
51178268)
关键词
汽车
碰撞预警
行为识别
风险评估
隐马尔科夫
vehicle
collision warning
behavior recognize
risk assessment
hidden Markov model
