• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>IEEE Conference on Control Applications >Analysis of Vehicle Following Behavior of Human Driver Based on Hybrid Dynamical System Model
【24h】

Analysis of Vehicle Following Behavior of Human Driver Based on Hybrid Dynamical System Model

机译：基于混合动力系统模型的人司机行为分析

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper presents the development of the modeling of human driving behavior based on an expression as a hybrid dynamical system (HDS) focusing on the driver''s vehicle following task. The driving data are collected by using a driving simulator which can provide a stereoscopic immersive vision to the driver. In our modeling, the relationship between the measured sensory information and the output of the driver are expressed by the piecewise ARX (PWARX) model, which is a class of the HDS. As the sensory input, the range between vehicles, range rate, and time derivative of the area of the back of the preceding vehicle (called KdB) are considered. Furthermore, the pedal operation is considered as the output. The identification problem for the PWARX model is solved using the combination of the data clustering and support vector machine. By introducing the PWARX model, it becomes possible to find not only parameters appearing in the motion in each mode but also parameters in the logical switching (decision making) conditions among them from the measured driving data. From the obtained results, it is found that the driver appropriately switches some "control laws" according to the sensory information, in particular, the KdB plays an important role in the decision making, i.e., the switching between modes.
机译：本文基于表达式作为关注驾驶员的车辆的混合动态系统（HDS），介绍了人类驾驶行为建模的发展。通过使用驱动模拟器收集驱动数据，该驱动模拟器可以向驾驶员提供立体沉浸视觉。在我们的建模中，测量的感官信息与驱动器的输出之间的关系由分段ARX（PWARX）模型表示，这是一个类HDS。作为感觉输入，考虑车辆的车辆之间的范围，范围率和前车的背部面积（称为KDB）的区域之间的衍生物。此外，踏板操作被认为是输出。使用数据聚类和支持向量机的组合来解决PWARX模型的识别问题。通过引入PWARX模型，不仅可以在每个模式中出现在运动中出现的参数，而且可以从测量的驱动数据中的逻辑切换（决策）条件中的参数。从所获得的结果中，发现驾驶员根据感官信息适当地切换一些“控制法”，特别是KDB在决策中起重要作用，即模式之间的切换。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号