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Driver Adaptive Control Algorithm for Intelligent Vehicle

운전자 주행 특성 파라미터를 고려한 지능화 차량의 적응 제어

  • 민석기 (한양대학교 대학원 자동차공학과) ;
  • 이경수 (한양대학교 기계공학부)
  • Published : 2003.07.01

Abstract

In this paper, results of an analysis of driving behavior characteristics and a driver-adaptive control algorithm for adaptive cruise control systems have been described. The analysis has been performed based on real-world driving data. The vehicle longitudinal control algorithm developed in our previous research has been extended based on the analysis to incorporate the driving characteristics of the human drivers into the control algorithm and to achieve natural vehicle behavior of the adaptive cruise controlled vehicle that would feel comfortable to the human driver. A driving characteristic parameters estimation algorithm has been developed. The driving characteristics parameters of a human driver have been estimated during manual driving using the recursive least-square algorithm and then the estimated ones have been used in the controller adaptation. The vehicle following characteristics of the adaptive cruise control vehicles with and without the driving behavior parameter estimation algorithm have been compared to those of the manual driving. It has been shown that the vehicle following behavior of the controlled vehicle with the adaptive control algorithm is quite close to that of the human controlled vehicles. Therefore, it can be expected that the more natural and more comfortable vehicle behavior would be achieved by the use of the driver adaptive cruise control algorithm.

Keywords

Intelligent Vehicle;Intelligent Cruise Control;Adaptive Cruise Control;Stop-and-Go Control System;Time-gap;Time-to-Collision

References

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Cited by

  1. Development of a Driving Behavior-Based Collision Warning System Using a Neural Network vol.19, pp.5, 2018, https://doi.org/10.1007/s12239-018-0080-6