• Journal of Mechanical Science and Technology
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• v.19 no.11
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• pp.1998-2006
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• 2005

The lane departure avoidance systems have been considered promising to assist human drivers in AVCS (Advanced Vehicle Control System). In this paper, a lane departure monitoring and control system is developed and evaluated in the hardware-in-the-loop simulations. This system consists of lane sensing, lane departure monitoring and active steering control subsystems. The road image is obtained based on a vision sensor and the lane parameters are estimated using image processing and Kalman Filter technique. The active steering controller for avoiding the lane departure is designed based on the lane departure metric. The proposed lane departure avoidance system is realized in a steering HILS (hardware-in-the-loop simulation) tool and its performance is evaluated with a driver in the loop.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.932-937
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• 2003

In this paper, we will explain about the unmanned vehicle control and modeling for combined obstacle avoidance and lane tracking. First, obstacle avoidance is considered as one of the important technologies in the unmanned vehicle. It is consisted by two parts: the first part includes the longitudinal control system for the acceleration and deceleration and the second part is the lateral control system for the steering control. Each system uses to the obstacle avoidance during the vehicle moving. Therefore, we propose the method of vehicle control, modeling and obstacle avoidance. Second, we describe a method of lane tracking by means of vision system. It is important in the unmanned vehicle and mobile robot system. In this paper, we deal with lane tracking and image processing method and it is including lane detection method, image processing algorithm and filtering method.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.6
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• pp.213-221
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• 2003

This paper describes a method of lane tracking by means of a vision system which includes vehicle control and modeling. Lane tracking is considered one of the important technologies in an unmanned vehicle and mobile robot system. The current position and condition of the vehicle are calculated from an image processing method by a CCD camera. We deal with lane tracking as follows. First, vehicle control is included in the road model, and lateral and longitudinal controls. Second, the image processing method deals with the lane detection method, image processing algerian, and filtering method. Finally, this paper proposes a correct method for lane detection through a vehicle test by wireless data communication.

• International Journal of Automotive Technology
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• v.5 no.2
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• pp.69-76
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• 2004

This paper evaluates the effectiveness of four-wheel-steering system from the viewpoint of lane-keeping control theory. In this paper, the lane-keeping control system is designed on the basis of the four-wheel-steering automobiles whose desired steering response is realized with the application of model matching control. Two types of desired steering responses are presented in this paper. One is zero-sideslip response, the other one is steering response which realizes zero-phase-delay of lateral acceleration. Using simplified linear two degree-of-freedom bicycle model, simulation study and theoretical analysis are conducted to evaluate the lane-keeping control performance of active four-wheel-steering automobiles which have different desired steering responses. Finally, the evaluation is conducted on straight and curved roadway tracking maneuvers.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.5
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• pp.735-743
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• 2012

In this paper, we present model predictive control (MPC) applied to lane keeping system (LKS) based on a vision module. Due to a slow sampling rate of the vision system, the conventional LKS using single rate control may result in uncomfortable steering control rate in a high vehicle speed. By applying MPC using multi-rate Kalman filter to active steering control, the proposed MPC-based active steering control system prevents undesirable saturated steering control command. The effectiveness of the MPC is validated by simulations for the LKS equipped with a camera module having a slow sampling rate on the curved lane with the minimum radius of 250[m] at a vehicle speed of 30[m/s].

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.6
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• pp.222-228
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• 2003

Lane departure avoidance system is one of the key technologies for the future active-safety passenger cars. The lane departure avoidance system is composed of two subsystems; lane sensing algorithm and active-steering controller. In this paper, the road image is obtained by vision sensor and the lane parameters are estimated using image processing and Kalman Filter technique. The active-steering controller is designed to prevent the lane departure. The developed active-steering controller can be realized by steer-by-wire actuator. The lane-sensing algorithm and active-steering controller are implemented into the steering HILS(Hardware-In-the-Loop Simulation) and their performance is evaluated with a human driver in the loop.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.480-487
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• 2009

Autonomous Lane detection with vision is a difficult problem because of various road conditions, such as shadowy road surface, various light conditions, and the signs on the road. In this paper we propose a robust lane detection algorithm to overcome shadowy road problem using a statistical method. The algorithm is applied to the vision-based mobile robot system and the robot followed the lane with the lane following controller. In parallel with the lane following controller, the global position of the robot is estimated by the developed localization method to specify the locations where the lane is discontinued. The results of experiments, done in the region where the GPS measurement is unreliable, show good performance to detect and to follow the lane in complex conditions with shades, water marks, and so on.

• Journal of the Korean Professional Engineers Association
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• v.33 no.4
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• pp.63-67
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• 2000

Presently, Weekend Buses only lane system is in force in Gyung-Bu Highway causes traffic delay at the northern of Su-won IC and have reduced the efficiency of Highway. To solve this problems, Buses only lane system is working at the northern of Su-won IC should be charged over from Median Buses only lane system to Curb Buses only lane system. It makes good effects on reducing weaving occurs when cars change lane, traffic accidents, ease control on violation cars, improving Level of Service in the Ramp, etc.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.161-164
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• 1999

An effective approach to lane detection in driver assistance system (DAS) is proposed, based on the decomposition of lane markings. The properties of the decomposed lane markings are discussed, and analyses on lane curvature are given. The current lane on road is detected quickly, the neighboring lane regions are also extracted for lane planning of the vehicle, and the parameters of lane structure are accurately estimated.

• Journal of Advanced Navigation Technology
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• v.11 no.4
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• pp.359-370
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• 2007

Lane tracking and obstacle avoidance are considered two of the key technologies on an unmanned ground vehicle system. In this paper, we propose a method of lane tracking and obstacle avoidance, which can be expressed as vehicle control, modeling, and sensor experiments. First, obstacle avoidance consists of two parts: a longitudinal control system for acceleration and deceleration and a lateral control system for steering control. Each system is used for unmanned ground vehicle control, which notes the vehicle's location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control strategy of the vehicle can detect obstacle and perform obstacle avoidance on the road, which involves vehicle velocity. Second, we explain a method of lane tracking by means of a vision system, which consists of two parts: First, vehicle control is included in the road model through lateral and longitudinal control. Second, the image processing method deals with the lane tracking method, the image processing algorithm, and the filtering method. Finally, in this paper, we propose a method for vehicle control, modeling, lane tracking, and obstacle avoidance, which are confirmed through vehicles tests.