摘要
目前大多数已投入使用的汽车主动安全预警系统价格昂贵,而且停留在对汽车运动姿态的监测和报警功能上,缺乏对汽车未来时刻自身运动姿态作进一步预测。针对这些不足性,本文进行汽车运动姿态在线预测的研究,提前预测汽车未来时刻可能的行驶运行状态,对提高汽车的主动安全性,减少道路交通事故将起到十分重要的作用。采用最新的6轴运动处理组件MPU-6050实现汽车运动姿态参数的在线感知,设计卡尔曼滤波器,通过信号融合处理,获取汽车运动姿态参数的最优估计值,采用多层递阶模型来开展汽车运动姿态参数的预测。最后以纵向车速、侧倾角和横摆角为例开展感知与预测,进行实车道路试验,取得了很好的预测效果。实验结果表明所开展的汽车感知与预测技术的可行性和探索性。
Currently most automotive active safety warning system which has been put into use is expensive, but stays in the vehi- cle motion posture monitoring and alarm functions, lacking of further prediction of the vehicle＇ s own motion attitude for future time. Considering these shortcomings, launching vehicle motion prediction and predicting vehicle motion posture for future time in advance, can play a very important role to improve the vehicle＇ s active safety and reduce road traffic accidents. The latest 6-axis Motion Processing Unit （MPU） MPU-6050 can realize vehicle posture parameters online perception. The Kalman filter is de- signed, through signal fusion processing we can get the optimal estimate of the vehicle motion posture parameters, using multi-lev- el recursive model to carry out the prediction research. Finally, taking vertical speed, roll angle and yaw angle for example, we carry on perception and prediction. A good prediction effect is got by road test, which shows the feasibility and exploratory of the vehicle perception and prediction technology.
出处
《计算机与现代化》
2013年第8期38-42,共5页
Computer and Modernization
基金
江苏省普通高校研究生科研创新计划项目(CXLX11_0567)
关键词
车载感知
预测
卡尔曼滤波器
多层递阶
汽车主动安全
vehicle perception
forcasting
Kalman filter
multi-level recursive
vehicle active safety
