• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.465-467
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• 1998

A lane change maneuver is a part of lateral control of an automated highway system. Assuming no direct measurement of its position during transition from one lane to another. A vehicle is controlled to follow the virtual desired trajectory using only on-board sensors. This paper investigates the development of a fuzzy controller for automated lateral control during emergencies. The performance of the fuzzy controller is presented at 20m/s for a step lane change and a double lane change. The robustness of fuzzy controller is investigated with respect to change in tire parameters and the number of passengers.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.179-186
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• 2015

In this paper, a novel lateral control system is proposed for the purpose of improving lane keeping performance which is independent from GPS signals. Lane keeping is a key function for the realization of unmanned driving systems. In order to obtain this objective, a vision sensor based real-time lane detection scheme is developed. Furthermore, we employ a data fusion along with a real-time steering angle of the test vehicle to improve its lane keeping performance. The fused direction data can be obtained by an IMU sensor and vision sensor. The performance of the proposed system was verified by computer simulations along with field tests using MOHAVE, a commercial vehicle from Kia Motors of Korea.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1130-1133
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• 2003

The goal of this research is developing advanced lane detecting algorithm for unmanned vehicle. Previous lane detecting method to bring on error become of the lane loss and noise. Therefore, new algorithm developed to get exact information of lane. This algorithm can be used to AGV(Autonomous Guide Vehicle) and LSWS(Lane Departure Warning System), ACC(Adapted Cruise Control). We used 1/10 scale RC car to embody developed algorithm. A CCD camera is installed on top of vehicle. Images are transmitted to a main computer though wireless video transmitter. A main computer finds information of lane in road image. And it calculates control value of vehicle and transmit these to vehicle. This algorithm can detect in input image marked by 256 gray levels to get exact information of lane. To find the driving direction of vehicle, it search line equation by curve fitting of detected pixel. Finally, author used median filtering method to removal of noise and used characteristic part of road image for advanced of processing time.

• Journal of Auto-vehicle Safety Association
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• v.15 no.3
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• pp.17-26
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• 2023

This paper presents extended state feedback control based on impulse response for lane change of autonomous driving vehicle. The triple characteristic root of path tracking system and longitudinal velocity determine feedback gains. We suggest a resemblance of impulse response curve of the system and lane change trajectory of the vehicle. The root affects the duration of lane change and lateral acceleration. The effect of limited lateral acceleration and saturation of steering angle will be analyzed and discussed. Finally, simulation results will show the trajectory of lane change based on impulse response under limitation of lateral acceleration.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.3
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• pp.9-23
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• 2015

A lane change maneuver which has a high driver cognitive workload and skills sometimes leads to severe traffic accidents. In this study, the Advanced Lane Change Assist System (ALCAS) was developed to assist with the automatic lane changes in merging sections which is mainly based on an automatic control algorithm for detecting an available gap, determining the Optimal Lane Change Start Point (OLCSP) in various traffic conditions, and positioning the merging vehicle at the OLCSP safely by longitudinal automatic controlling. The analysis of lane change behavior and modeling of fundamental lane change feature were performed for determining the default parameters and the boundary conditions of the algorithm. The algorithm was composed of six steps with closed-loop. In order to confirm the algorithm performance, numerical scenario tests were performed in various surrounding vehicles conditions. Moreover, feasibility of the developed system was verified in microscopic traffic simulation(VISSIM 5.3 version). The results showed that merging vehicles using the system had a tendency to find the OLCSP readily and precisely, so improved merging performance was observed when the system was applied. The system is also effective even during increases in vehicle volume of the mainline.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.6
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• pp.194-207
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• 2000

In this paper, we suggest a vision-based lane change control system, which can be applied on the straight road, without additional sensors such as a yaw rate sensor and a lateral accelerometer. In order to reduce the image processing time, we predict a reference line position during lane change using the lateral dynamics and the inverse perspective mapping. The sliding mode control algorithm with a boundary layer is adopted to overcome variations of parameters that significantly affects a vehicle`s lateral dynamics and to reduce chattering phenomenon. However, applying the sliding mode control to the system with a long sampling interval, the stability of a control system may seriously be affected by the sampling interval. Therefore, in this paper, a look ahead offset has been used instead of a lateral offset to reduce the effect of the long sampling interval due to the image processing time. The control algorithm is developed to follow the desired trajectory designed in advance. In the design of the desired trajectory, we take account of the constraints of lateral acceleration and lateral jerk for ride comfort. The performance of the suggested control system is evaluated in simulations as well as field tests.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.4
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• pp.19-25
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• 2005

This paper presents a lateral control system for the autonomous navigation vehicle that was developed and tested by Robotics Centre of Ecole des Mines do Paris in France. A robust lane detection algorithm was developed for detecting different types of lane marker in the images taken by a CCD camera mounted on the vehicle. $^{RT}Maps$ that is a software framework far developing vision and data fusion applications, especially in a car was used for implementing lane detection and lateral control. The lateral control has been tested on the urban road in Paris and the demonstration has been shown to the public during IEEE Intelligent Vehicle Symposium 2002. Over 100 people experienced the automatic lateral control. The demo vehicle could run at a speed of 130km1h in the straight road and 50km/h in high curvature road stably.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.110.3-110
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• 2002

$\textbullet$ Lane detection by TFALDA $\textbullet$ SVM for large scale data and multiclass classification problem $\textbullet$ TLC Classification $\textbullet$ Lateral offset estimation by IPT $\textbullet$ Lane departure warning by a fuzzy system $\textbullet$ Experimental results by HiLS $\textbullet$ Conclusion

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.240-248
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• 1999

This paper presents a lane-change collision avoidance control algorithm for autonomous vehicles that will be used in AHS(Automated Highway System). In the proposed control algorithm, nominal control inputs are generated by solving the inverse vehicle dynamic equations of motion for a lane-change maneuver. In addition, a corrective steering input from preview as well as DYC (Direct Yaw Moment Control) may be included to reduce unpredictable errors and to insure yaw directional stability, respectively. The performance of the algorithm is evaluated with an ABS HILS system which consist of 17 DOF vehicle model and real ABS hardware parts. The HILS simulation results show that the proposed algorithm may be used for emergency lane-change maneuvers for autonomous vehicles.

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.3
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• pp.54-61
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• 2009

Lane keeping assistant system (LKAS) could save thousands of lives each year by maintaining lane position and is regarded as a promising active safety system. The LKAS is expected to reduce the driver workload and to assist the driver during driving. This paper proposes a model based predictive controller for the LKAS which requires cooperative driving between the driver and the assistance system. A Hardware-In-the-Loop-Simulator (HILS) is constructed for its evaluation and includes Carsim, Matlab Simulink and a lane detection algorithm. The single camera is mounted with the HILS to acquire the monitor images and to detect the lane markers. The simulation is conducted to validate the LKAS control performance in various road scenario.