• Journal of Mechanical Science and Technology
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• v.19 no.9
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• pp.1742-1752
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• 2005

This paper presents a Multiple Target Tracking (MTT) Adaptive Cruise Control (ACC) system which consists of three parts; a multi-model-based multi-target state estimator, a primary vehicular target determination algorithm, and a single-target adaptive cruise control algorithm. Three motion models, which are validated using simulated and experimental data, are adopted to distinguish large lateral motions from longitudinally excited motions. The improvement in the state estimation performance when using three models is verified in target tracking simulations. However, the performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. The MTT-ACC system is tested under lane changing situations to examine how much the system performance is improved when multiple models are incorporated. Simulation results show system response that is more realistic and reflective of actual human driving behavior.

• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.7
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• pp.1146-1151
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• 2003

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.

• Journal of Mechanical Science and Technology
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• v.15 no.9
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• pp.1248-1256
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• 2001

In this study, a test bed for vehicle longitudinal control is developed using a chassis dynamometer and real time 3-D graphics. The proposed test bed system consists of a chassis dynamometer on which test vehicle can run longitudinally, a video system that shows virtual driver view, and computers that control the test vehicle and realize the real time 3-D graphics. The purpose of the proposed system is to test vehicle longitudinal control and warning algorithms such as Adaptive Cruise Control(ACC), stop and go systems, and collision warning systems. For acceleration and deceleration situations which only need throttle movements, a vehicle longitudinal spacing control algorithm has been tested on the test bed. The spacing control algorithm has been designed based on sliding mode control and road grade estimation scheme which utilizes the vehicle engine torque map and gear shift information.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.741-746
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• 2001

This paper presents an investigation of a vehicle-to-vehicle distance control using a Hardware-in-the-Loop Simulation(HiLS) system. Since vehicle tests are costly and time consuming, how to establish a efficient and low cost development tool is an important issue. The HiLS system consists of a stepper motor, an electronic vacuum booster, a controller unit and two computers which are used to form real time simulation and to save vehicle parameters and signals of actuator through a CAN(Controller Area Network). Adoption of a CAN for communication is a trend in the automotive industry. Since this environment is the same as that of a real vehicle, a distance control logic verified in laboratory can be easily transfered to a test vehicle.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.7
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• pp.1401-1407
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• 2002

This paper represents an investigation of the vehicle-to-vehicle distance control system using Hardware-in-the-Loop Simulation(HiLS). Control logic is primarily developed and tested with a specially equipped test vehicle. Establishment of an efficient and low cost development tool is a very important issue, and test vehicle approach is costly and time consuming. HiLS method is useful in the investigation of driver assistance and active safety systems. The HiLS system consists of a stepper motor for throttle control, a hydraulic brake system with an electronic vacuum booster, an electronic controller unit, a data logging computer which are used to save vehicle states and signals of actuator through a CAN and a simulation computer using mathematical vehicle model. Adaptation of a CAN instead of RS-232 Serial Interface for communication is a trend in the automotive industry. Since this environment is the same as a test vehicle, a control logic verified in laboratory can be easily transferred to a test vehicle.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.861-866
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• 2007

This paper presents development of a vehicle lateral and longitudinal control for autonomous driving control and test results obtained using an electric vehicle. Sliding control theory has been used to develop a vehicle speed and distance control algorithm. The longitudinal control algorithm that maintains safety and comfort of the vehicle consists of a cruise and STOP&GO control depending on traffic conditions. Desired steering angle is determined through the lateral position error and the yaw angle error based on preview optimal control. Motor control inputs have been directly derived from the sliding control law. The performance of the autonomous driving control which is integrated with a lateral and longitudinal control is investigated by computer simulations and driving test using an electric vehicle. Electric vehicle system consists of DC driving motor, an electric power steering system, main controller (Autobox)