• 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.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.2
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• pp.32-38
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• 2006

A vehicle adaptive cruise control strategy based on human drivers' driving characteristics has been investigated. Human drivers driving characteristics have been analyzed using vehicle test data obtained from 125 participants. The control algorithm has been designed to incorporate the driving characteristics of the human drivers and to achieve natural vehicle behavior of the controlled vehicle that would reduce the workload of the human driver. Vehicle following characteristics of the cruise controlled vehicle have been compared to real-world driving radar sensor data of human drivers using a validated vehicle simulator. and compare nominal cruise control and adaptive cruise control.

• 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.

• 한국ITS학회:학술대회논문집
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• 2002.11a
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• pp.88-91
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• 2002

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.1 s.232
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• pp.139-144
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• 2005

A vehicle cruise control algorithm using an Interacting Multiple Model (IMM)-based Multi-Target Tracking (MTT) method has been presented in this paper. The vehicle cruise control algorithm consists of three parts; track estimator using IMM-Probabilistic Data Association Filter (PDAF), a primary target vehicle determination algorithm and a single-target adaptive cruise control algorithm. Three motion models; uniform motion, lane-change motion and acceleration motion. have been adopted to distinguish large lateral motions from longitudinal motions. The models have been validated using simulated and experimental data. The improvement in the state estimation performance when using three models is verified in target tracking simulations. The performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. These simulations show system response that is more realistic and reflective of actual human driving behavior.

• Transactions of the Korean Society of Automotive Engineers
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• v.14 no.6
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• pp.82-88
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• 2006

The study investigated how an adaptive cruise control system induced behavioral adaptation in drivers using a full-scale driving simulator. Forty drivers with different driving styles participated in the study to compare headway-time, vehicle lateral position variation, and head and eye movement when driving with and without the adaptive cruise control system. Results showed that system induced positive behavioral adaptation by drawing consistency in driving speed and headway-time regardless of the driving styles. However, the results also showed that the drivers' reliance on the system induced negative adaptation including reduced lane keeping ability and reduced attention during driving. As a strategy to prevent negative adaptation, the study proposed information service to drivers with the adaptive cruise control system status and driving environment, and investigated effectiveness of the service. Twelve drivers participated in the experiment to compare headway-time, vehicle lateral position variation and subjective ratings when driving with and without the information service. Results showed that the information service assisted the drivers to maintain safer and more comfortable headway-time without impairing drivers' steering ability.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.9
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• pp.817-823
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• 2017

In the past, research has been conducted on the development of an adaptive cruise control algorithm considering fuel efficiency, and an adaptive cruise control system considering fuel efficiency have been developed. However, research on optimizing vehicle and adaptive cruise control parameters in order to maximize performances is insufficient. In this study, the design optimization of vehicle and control parameters considering fuel efficiency, trackability, ride comfort and safe distance is performed. This paper proposes performance measures of vehicle behavior and develops an adaptive cruise control system. In addition, based on the screening of vehicle parameters that significantly influence performances, kriging surrogate models are constructed through a sequential design of experiment, and kriging surrogate model-based design optimization is performed to maximize fuel efficiency and satisfy target performances.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.88.3-88
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• 2002

$\textbullet$ Introduction $\textbullet$ FUll-Scale Driving Simulator(KMU DS-3) $\textbullet$ Adaptive Cruise Control Implementation $\textbullet$ Driving Simulator Study $\textbullet$ Conclusions

• 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.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.7
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• pp.202-213
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• 1999

Adaptive Cruise Control (ACC) is one of key features on intelligent Transportation System(ITS). In ACC, the steering is done by a driver, but the engine throttle valve and the brake are controlled electronically. The relative velocity and distance from the preceeding vehicle are measured by radars or image processing units and relevant vehicular spacing is maintained in ACC control systems. In this study, vehicle longitudinal dynamics are modeled to simulate vehicle longitudinal maneuver and to design longtitudinal controllers for ACC vehicles. The control algorithm is designed based on the modeled vehicle longitudinal dynamics using a non-linear sliding mode control method. To verity the performance of the control algorithm, a real time numerical simulation program is developed on a Silicon Graphics workstation using C-language . A real time graphic program is alos develpe and integrated with the numerical simulation program.