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Chapter 13 On Low Complexity Predictive Approaches to Control of Autonomous Vehicles

机译:第十三章自主车辆控制的低复杂度预测方法

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摘要

In this chapter we present low complexity predictive approaches to the control of autonomous vehicles. A general hierarchical architecture for fully autonomous vehicle guidance systems is presented together with a review of two control design paradigms. Our review emphasizes the trade off between performance and computational complexity at different control levels of the architecture. In particular, experimental results are presented, showing that if the controller at the lower level is properly designed, then it can handle system nonlinearities and model uncertainties even if those are not taken into account at the higher level.
机译:在本章中,我们介绍了用于自动驾驶车辆控制的低复杂度预测方法。提出了一种用于全自动车辆导航系统的通用分层体系结构,并回顾了两种控制设计范例。我们的审查强调了在体系结构的不同控制级别上性能和计算复杂性之间的权衡。尤其是,实验结果表明,如果较低级别的控制器经过适当设计,则即使在较高级别上未将其考虑在内,它也可以处理系统非线性和模型不确定性。

著录项

  • 来源
  • 会议地点 Feldkirchen(AT)
  • 作者单位

    Chalmers University of Technology, Department of Signals and Systems, Goeteborg, SE-41296, Sweden;

    rnUniversity of California at Berkeley, Department of Mechanical Engineering, Berkeley, CA 94720-1740, USA;

    rnFord Research Laboratories, Research and Innovation Center, 2101 Village Road, Dearborn, MI, 48121, USA;

    rnFord Research Laboratories, Research and Innovation Center, 2101 Village Road, Dearborn, MI, 48121, USA;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 汽车工程;
  • 关键词

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