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清华大学学报(自然科学版)  2015, Vol. 55 Issue (10): 1093-1097    DOI: 10.16511/j.cnki.qhdxxb.2015.22.019
  汽车工程 本期目录 | 过刊浏览 | 高级检索 |
基于支持向量机的汽车转向与换道行为识别
杨殿阁, 何长伟, 李满, 何奇洸
清华大学 汽车工程系, 汽车安全与节能国家重点实验室, 北京 100084
Vehicle steering and lane-changing behavior recognition based on a support vector machine
YANG Diange, HE Changwei, LI Man, HE Qiguang
State Key Laboratory of Automotive Safety and Energy, Department of Automotive Engineering, Tsinghua University, Beijing 100084, China
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摘要 汽车驾驶行为是影响燃油消耗和安全驾驶的重要因素,驾驶行为识别是对汽车安全驾驶和节能进行优化的基础。该文针对汽车转向和换道行为,通过加装汽车转向盘转角传感器,结合车载总线通信技术获取汽车行驶状态信息,基于汽车转向运动学推导车辆行驶状态与汽车行驶轨迹之间的映射关系,进一步建立汽车行驶方向向量模型,提出以车身轴线转角和最大转向盘转角为特征量的支持向量机线性分类器,并运用Lagrange数乘法和二次规划算法求解该最优分类问题。通过设计实车实验验证了该方法的有效性。实验结果表明: 该方法识别汽车的转向与换道驾驶行为的准确度达98%以上。该技术可用于汽车行驶安全预警与控制系统, 提升行驶安全。
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杨殿阁
何长伟
李满
何奇洸
关键词 驾驶行为行驶方向向量支持向量机最优分类    
Abstract:Driving behavior plays an important role in fuel consumption and safe driving. Thus, driving behavior recognition can improve driving safety and optimize energy use. This study presents a steering and lane-changing behavior recognition system based on the vehicle status obtained from a steering wheel angle sensor. A support vector machine linear classifier is then used to analyze the vehicle body transfer angle and maximum steering angle given by a moving direction vector model. Lagrange number multiplication and quadratic programming are used in an optimal classifier for recognizing steering and lane-changing behavior. Real vehicle tests show that this methodology has 98% accuracy for steering and lane-changing behavior recognition. This system can be integrated into a warning and control system to improve driving safety.
Key wordsdriving behavior    moving direction vector    support vector machine    optimal classification
收稿日期: 2014-07-12      出版日期: 2015-10-15
ZTFLH:  U491  
基金资助:国家“八六三”高技术项目(2012AA111901);国家留学基金项目(201406215015);清华大学汽车安全与节能国家重点实验室开放基金项目(KF14142)
作者简介: 杨殿阁(1973-),男(汉),山东,教授,E-mail:ydg@tsinghua.edu.cn
引用本文:   
杨殿阁, 何长伟, 李满, 何奇洸. 基于支持向量机的汽车转向与换道行为识别[J]. 清华大学学报(自然科学版), 2015, 55(10): 1093-1097.
YANG Diange, HE Changwei, LI Man, HE Qiguang. Vehicle steering and lane-changing behavior recognition based on a support vector machine. Journal of Tsinghua University(Science and Technology), 2015, 55(10): 1093-1097.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2015.22.019  或          http://jst.tsinghuajournals.com/CN/Y2015/V55/I10/1093
  图1 汽车转向运动关系
  图2 汽车转向与换道行为方向向量
  图3 换道行为车身轴线转角算例
  图4 转向行为车身轴线转角算例
  图5 转向与换道行为平面
  表1 行为识别算法步骤
  图6 转向盘转角测量实验系统
  图7 SVM 行为训练结果
  图8 SVM 行为测试结果
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