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Steering control of automated vehicles using absolute positioning GPS and magnetic markers.

机译：使用绝对定位GPS和磁性标记的自动驾驶汽车的转向控制。

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摘要

These days, automated vehicle control technology has become one of the most promising approaches to provide significant benefits to the transportation system in terms of traffic safety and efficiency. In this dissertation, steering control for passenger cars on automated highways is analyzed. Feasibility of an automatic steering system based on an absolute positioning global positioning system (GPS) and a magnetic marker reference system has been evaluated using computer simulations. Its performance during emergency situations is considered, as it is a vital safety issue in highway automation. State estimation and control algorithm issues are examined for a simplified linear vehicle model as well as for a complex nonlinear vehicle model. By using GPS and a magnetic marker sensor, an accurate and real-time estimation of the vehicle's lateral displacements with respect to the road can be accomplished. A robust control technique in the form of a parameter space approach in an invariance plane is utilized for lateral controller design based on a higher order nonlinear vehicle model. In addition, the control system incorporates an algorithm based on road curvature preview for ride comfort enhancement. The proposed estimation and control system is shown, in computer simulations, to be effective in handling vehicles under normal and emergency situations.
机译：如今，自动车辆控制技术已成为在交通安全和效率方面为运输系统带来重大利益的最有前途的方法之一。本文分析了自动公路上客车的转向控制。已经使用计算机仿真评估了基于绝对定位全球定位系统（GPS）和磁性标记参考系统的自动转向系统的可行性。考虑到它在紧急情况下的性能，因为它是高速公路自动化中至关重要的安全问题。针对简化的线性车辆模型以及复杂的非线性车辆模型，研究了状态估计和控制算法问题。通过使用GPS和磁性标记传感器，可以准确，实时地估计车辆相对于道路的横向位移。在不变平面中采用参数空间方法形式的鲁棒控制技术被用于基于高阶非线性车辆模型的横向控制器设计。此外，控制系统还结合了基于道路曲率预览的算法，以提高乘坐舒适性。在计算机仿真中，所提出的估算和控制系统在正常和紧急情况下可有效地处理车辆。

著录项

  • 作者

    Hernandez-Sanchez, Jose Ignacio.;

  • 作者单位

    Arizona State University.;

  • 授予单位 Arizona State University.;
  • 学科 Engineering Automotive.
  • 学位 Ph.D.
  • 年度 2003
  • 页码 139 p.
  • 总页数 139
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术及设备;
  • 关键词

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