• Title/Summary/Keyword: Intelligent cruise control(ICC)

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DESIGN AND EVALUATION OF INTELIGENT VEHICLE CRUISE CONTROL SYSTEMS USING A VEHICLE SIMULATOR

  • Han, D.H.;Yi, K.S.;Lee, J.K.;Kim, B.S.;Yi, S.
    • International Journal of Automotive Technology
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    • v.7 no.3
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    • pp.377-383
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    • 2006
  • This paper presents evaluation and comparisons of manual driving and driving with intelligent cruise control(ICC) systems. An intelligent vehicle cruise control strategy has been designed to achieve natural vehicle behavior of the controlled vehicle that would make human driver feel comfortable and therefore would increase driver acceptance. The evaluation and comparisons of the ICC and manual driving have been conducted using real-world vehicle driving data and an ICC vehicle simulator.

A Modeling and Control of Intelligent Cruise Control Systems (지능형 순항 제어 시스템 모델링 및 제어)

  • Lee, Se-Jin;Hong, Jin-Ho;Lee, Gyeong-Su
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.25 no.2
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    • pp.283-288
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    • 2001
  • A throttle/brake control law for the intelligent cruise control(ICC) systems has been proposed in this paper. The ICC system consists of a vehicle detection sensor, the control algorithm and a throttle/brake actuators. For the control of a throttle/brake system, we introduced a solenoid-valve-controlled electronic vacuum booster and a step-motor controlled throttle actuator. Nonlinear computer model for the electronic vacuum booster has been developed and the simulations were per formed using a complete nonlinear vehicle model. The results indicate the proposed throttle/brake control law can provide the ICC system with an optimized performance.

An intelligent cruise control system using a self-tuning fuzzy algorithm (자기조절 퍼지 알고리듬을 이용한 지능순항제어시스템 개발)

  • Jung, Seung-Hyun;Lee, Gu-Do;Kim, Sang-Woo;Park, Poo-Gyeon
    • Journal of Institute of Control, Robotics and Systems
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    • v.4 no.1
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    • pp.68-75
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    • 1998
  • The Intelligent Cruise Control system, ICC, is a driver assisting system for controlling relative speed and distance between two vehicles in the same lane. The ICC may be considered as an extension of a traditional cruise control, not only keeping a fixed speed of the vehicle, but correcting the speed also to that of a slower one ahead. This paper presents a real-time self-tuning fuzzy control algorithm to develop ICC. The self-tuning fuzzy control law is adopted to reduce the effects of nonlinearities of the vehicle and various road environments. In the self-tuning algorithm an interior penalty method is applied to preserve the inherent order of membership functions and is modified as an on-line algorithm for real time application. Via simulations, the performance of the suggested control algorithm is compared with a PID and a fuzzy control without self-tuning. The suggested control algorithm is implemented on PRV III and the results of the test driving on a local road are given.

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Vehicle-Driving-Load-Adaptive Control of Intelligent Vehicle (차량 주행부하 추정기법을 이용한 지능화 차량의 적응제어)

  • 이세진;이경수
    • Transactions of the Korean Society of Automotive Engineers
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    • v.9 no.5
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    • pp.115-121
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    • 2001
  • A driving load estimation method for intelligent cruise control(ICC) vehicles has been proposed in this paper. Vehicle driving load is one of the most important factors of perturbations in vehicle control and can affect the control performance critically. The effect of the control with driving load estimation on vehicle-to-vehicle distance control has been presented and investigated via computer simulations and vehicle tests. The results show that vehicle-driving-load-adaptive control can provide an ICC system with a good acceleration tracking performance. In addition, the results show that driving load estimation can compensate not only the variation of driving load but also the modeling errors.

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Vehicle-Driving-Load-Adaptive Control of Intelligent Vehicle (차량 주행부하 추정기법을 이용한 지능화 차량의 적응제어)

  • Lee, Se-Jin;Yi, Kyong-Su
    • Proceedings of the KSME Conference
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    • 2000.11a
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    • pp.653-658
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    • 2000
  • A driving load estimation method for intelligent cruise control(ICC) vehicles has been proposed in this paper. The driving load is one of the most important factors of perturbations in vehicle control and can affect the control performance critically. The Effect of the control with driving load estimation on vehicle-to-vehicle distance control has been presented and investigated via computer simulations and vehicle tests. The results show that the control with driving load estimation can provide ICC system with a good acceleration tracking performance. In addition, the results show that driving load estimation can compensate not only variation of driving load but also the modeling errors.

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Throttle/Brake Combined Control for Vehicle-to-vehicle Distance and Speed Control (찻간 속도/거리제어를 위한 구동력/제동력 통합제어)

  • 이세진;이경수
    • Transactions of the Korean Society of Automotive Engineers
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    • v.9 no.2
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    • pp.137-142
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    • 2001
  • A throttle/brake control law for the intelligent cruise control(ICC) systems has been proposed in this paper. The ICC system consists of a vehicle detection sensor, the control algorithm and a throttle/brake actuators. The control performance has been investigated through vehicle tests. The test vehicle is equipped with a MMW radar sensor, a solenoid-valve-controlled Electronic-Vacuum-Booster(EVB) and a step-motor controlled throttle actuator. The results indicate the proposed throttle/brake control laws can provide satisfactory vehicle-to-vehicle distance and velocity control performance.

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Estimation of Vehicle Driving-Load with Application to Vehicle Intelligent Cruise Control

  • Kyongsu Yi;Lee, Sejin;Lee, Kyo-Il
    • Journal of Mechanical Science and Technology
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    • v.15 no.6
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    • pp.720-726
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    • 2001
  • This paper describes a vehicle driving-load estimation method for application to vehicle Intelligent Cruise Control (ICC). Vehicle driving-load consists of aerodynamic force, rolling resistance, and gravitational force due to road slope and is unknown disturbance in a vehicle dynamic model. The vehicle driving-load has been estimated from engine and wheel speed measurements using a vehicle dynamic model a least square method. The estimated driving-load has been used in the adaptation of throttle/brake control law. The performance of the control law has been investigated via both simulation and vehicle tests. The simulation and test results show that the proposed control law can provide satisfactory vehicle-to-vehicle distance control performance for various driving situations.

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A SPEED CONTROLLER FOR VEHICLES USING FUZZY CONTROL ALGORITHM WITH SELF0LEARNING (자기 학습 능력을 가진 퍼지 제어기를 이용한 차량의 속력 제어기 개발)

  • 정승현;김상우
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.880-883
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    • 1996
  • This paper suggests a speed control algorithm for the ICC(Intelligent Cruise Controller) system. The speed controller is designed using the fuzzy controller which shows the good performance in nonlinear system having the complex mathematical model. The fuzzy controller was equipped with the capability of a self-learning in real time in order to maintain the good performance of the speed controller in a time-varying environment the self-learning properties and the performance of the fuzzy controller are showed via computer simulation. The suggested fuzzy controller will be applied to the PRV-III which is our test vehicle.

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Validation of Driver Steering Model with Vehicle Test (실차 실험을 통한 운전자 조향 모델의 검증)

  • Chung Taeyoung;Lee Gunbok;Yi Kyongsu
    • Transactions of the Korean Society of Automotive Engineers
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    • v.13 no.1
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    • pp.76-82
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    • 2005
  • In this paper, validation of Driver Steering Model has been conducted. The comparison between the simulation model and vehicle test results shows that the model is very feasible for describing combined human driver and actual vehicle dynamic behaviors. The 3D vehicle model is consisted of 6-DOF sprung mass and 4-quarter car model for vehicle body dynamics. Powertrain model including differential gear and Pacejka tire model are applied. The driver steering model is also validated with vehicle test result. The driver steering model is based on angle and displacement error from the desired path, recognized by driver.