• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2202-2205
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• 2001

This paper is composed of two parts. One is image preprocessing part to measure the condition of the lane and vehicle. This finds the information of lines using RGB ratio cutting algorithm, the edge detection and Hough transform. The other obtains the situation of other vehicles using the image processing and viewport. At first, 2 dimension image information derived from vision sensor is interpreted to the 3 dimension information by the angle and position of the CCD camera. Through these processes, if vehicle knows the driving conditions which are lane angle, distance error and real position of other vehicles, we should calculate the reference steering angle by steering controller.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.57-64
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• 2020

The leading technologies of the ADAS (Advanced Driver Assist System) are ACC (Advanced Cruise Control), LKAS (Lane Keeping Assist System), and AEB (Autonomous Emergency Braking). LKAS is a system that uses cameras and infrared sensors to control steering and return to its running lane in the event of unintentional deviations. The actual test is performed for a safety evaluation and verification of the system. On the other hand, research on the system evaluation method is insufficient when an additional steering angle is applied. In this study, a model using Prescan was developed and simulated for the scenarios proposed in the preceding study. Comparative analyses of the simulation and the actual test were performed. As a result, the modeling validity was verified. A difference between the front wheels and the lane occurred due to the return velocity. The results revealed a maximum error of 0.56 m. The error occurred because the lateral velocity of the car was relatively small. On the other hand, the distance from wheels to the lanes displayed a tendency of approximately 0.5 m. This can be verified reliably.

• International Journal of Automotive Technology
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• v.6 no.6
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• pp.615-623
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• 2005

In this research, an effective technique was examined to improve the drift running performance. Concretely, the driver model by which the counter steer was done was assumed to the model by which the vehicle body slip angle (and the vehicle body slip angle velocity) was feed back. Next, the effectiveness of the system which added the assist steer angle corresponding to the steering wheel angle velocity to a front wheel steer angle was clarified as a drift running performance improvement technique of the vehicle. As a result, because the phase advances when the differentiation steer assistance is added, it has been understood to be able to cover the delay of the counter steer when the drift running. Therefore, it has been understood that the drift control does considerably easily. Moreover, it has been understood that the differentiation steer assistance acts effectively at the drift cornering by which the drift angle is maintained in cornering and the severe lane change with a drift at a situation. That is, it was understood to be able to settle to the drift angle of the aim quickly at the time of the drift cornering because the delay of the control steer angle of the counter steer was improved. Moreover, it was understood for the transient overshoot of the vehicle tracks to be able to decrease, and to return to the state of stability quickly at the severe lane change.

• Journal of IKEEE
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• v.24 no.1
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• pp.147-153
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• 2020

Conventional lane detection algorithms have problems in that the detection rate is lowered in road environments having a large change in curvature and illumination. The probabilistic Hough transform method has low lane detection rate since it exploits edges and restrictive angles. On the other hand, the method using a sliding window can detect a curved lane as the lane is detected by dividing the image into windows. However, the detection rate of this method is affected by road slopes because it uses affine transformation. In order to detect lanes robustly and avoid obstacles, we propose driving assist system using semantic segmentation based on deep learning. The architecture for segmentation is SegNet based on VGG-16. The semantic image segmentation feature can be used to calculate safety space and predict collisions so that we control a vehicle using adaptive-MPC to avoid objects and keep lanes. Simulation results with CARLA show that the proposed algorithm detects lanes robustly and avoids unknown obstacles in front of vehicle.

• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.19-26
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• 2012

Reversible lanes in urban intersections is used to efficiently control vehicles, reduce traffic congestion and increase the capacity of a roadway. But by far traffic control systems in urban intersections are simple and manually operated by police officers. In this study, we present a hybrid algorithm that intelligently resolve the moving direction of reversible lanes to efficiently manage the flow of traffic at intersection. The proposed algorithm consists of three stages:(i) fuzzy inference method to get the efficiency of moving direction, (ii) a provisional decision whether to change the reversible lane to different direction, (iii) a final evaluation criterion for changing the directions of the reversible lanes. The fuzzy inference results of efficiency are shown by using matlab application.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.6
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• pp.468-476
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• 2002

The confidence of information from image processing depends on the original image quality. Enhancing the confidence by an algorithm has an essential limitation. Especially, road images are exposed to lots of noisy sources, which makes image processing difficult. We, in this paper, propose a FNN (fuzzy-neural network) capable oi deciding the quality of a road image prior to extracting lane-related information. According to the decision by the FNN, road images are classified into good or bad to extract lane-related information. A CDF (cumulative distribution function), a function of edge histogram, is utilized to construct input parameters of the FNN, it is based on the fact that the shape of the CDF and the image quality has large correlation. Input pattern vector to the FNN consists of ten parameters in which nine parameters are from the CDF and the other one is from intensity distribution of raw image. Correlation analysis shows that each parameter represents the image quality well. According to the experimental results, the proposed FNN system was quite successful. We carried out simulations with real images taken by various lighting and weather conditions and achieved about 99% successful decision-making.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.33-39
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• 2014

Automatic driving needs many functions such as the obstacle recognition, the lane recognition, and the lane change, etc. In this paper, we realized a system which automatically drove the three-kinds of vehicle driving course, to introduce and apply the concept of 'color recognition' that expands the scope of 'lane recognition' for vehicle driving. We made the reduced each course compared with RC(Radio Control) car size, and controlled the steering considering the position and the slope of the detection line and the speed. Because the RC car does not have the brake function, we consider the speed and the position of the detection line to stop the RC car.

• Journal of Korean Society of Transportation
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• v.4 no.1
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• pp.3-11
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• 1986

One important element of a systematic approach to the management and control of the flow of people over an urban street network is the monitoring and evaluation of system performance. The nature of TSM strategies that, in part, differentiates them from traditional long-range transportation improvement alternatives is that they are less costly, are more quickly implemented and modified, and are often oriented toward sub-area problems which must be addressed at a more microscopic level of analysis. These factors suggest that pre-implementation evaluations of alternative TSM actions will often have to rely on quick-turn around, manual methods of analysis to guide the choice of which management action should be implemented. This paper was prepared to focus on the definition and importance of TSM, specifically associated with monitoring and evaluating traffic performance in the context of TSM startegies. A simple case study of reversible lane technique was presented. The purposes of the case study is to illustrate the methodology of evaluating TSM strategies and demonstrate to identify the benefit from the reversible lane technique, which may otherwise be overlooked in real world. Applying the reversible lane technique to Sam-Il elevate highway, it was found to be a very promising low cost alternative to reduce total travel time(or delay) and fuel consumption.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.4
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• pp.683-690
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• 2012

In this work, the semi-active control of a large-sized bus suspension system with an MR damper was studied. An MR damper model that can aptly describe the hysteretic characteristics of an MR damper was adopted. Parameter values of the MR damper model were suitably modified by considering the maximum damping force of a passive damper used in the suspension system of a real large-sized bus. In addition, a fuzzy logic controller was developed for semi-active control of a suspension system with an MR damper. The vertical acceleration at the attachment point of the MR damper and the relative velocity between sprung and unsprung masses were used as input variables, while voltage was used as the output variable. Straight-ahead driving simulations were performed on a road with a random road profile and on a flat road with a bump. In straight-ahead driving simulations, the vertical acceleration and pitch angle were measured to compare the riding performance of a suspension system with a passive damper with that of a suspension with an MR damper. In addition, a single lane change simulation was performed. In the simulation, the lateral acceleration and roll angle were measured in order to compare the handling performance of a suspension system using a passive damper with that of a suspension system using an MR damper.

• Journal of the Ergonomics Society of Korea
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• v.35 no.1
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• pp.11-27
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• 2016

Objective: The purpose of this study was to develop and evaluate high technology adaptive driving controls, such as mini steering wheel-lever system and joystick system, for the people with physical disabilities in the driving simulator. Background: The drivers with severe physical disabilities have problems in operation of the motor vehicle because of reduced muscle strength and limited range of motion. Therefore, if the remote control system with driver-by-wire technology is used for adaptive driving controls for people with physical limitations, the disabled people can improve their quality of life by driving a motor vehicle. Method: We developed the remotely controlled driving simulator with drive-by-wire technology, e.g., mini steering wheel-lever system and joystick system, in order to evaluate driving performance in a safe environment for people with severe physical disabilities. STISim Drive 3 software was used for driving test and the customized Labview program was used in order to control the servomotors and the adaptive driving devices. Thirty subjects participated in the study to evaluate driving performance associated with three different driving controls: conventional driving control, mini steering wheel-lever controls and joystick controls. We analyzed the driving performance in three different courses: straight lane course for acceleration and braking performance, a curved course for steering performance, and intersections for coupled performance. Results: The mini steering wheel-lever system and joystick system developed in this study showed no significant statistical difference (p>0.05) compared to the conventional driving system in the acceleration performance (specified speed travel time, average speed when passing on the right), steering performance (lane departure at the slow curved road, high-speed curved road and the intersection), and braking performance (brake reaction time). However, conventional driving system showed significant statistical difference (p<0.05) compared to the mini steering wheel-lever system or joystick system in the heading angle of the vehicle at the completion point of intersection and the passing speed of the vehicle at left turning. Characteristics of the subjects were found to give a significant effect (p<0.05) on the driving performance, except for the braking reaction time (p>0.05). The subjects with physical disabilities showed a tendency of relatively slow acceleration (p<0.05) at the straight lane course and intersection. The steering performance and braking performance were confirmed that there was no statistically significant difference (p>0.05) according to the characteristics of the subjects. Conclusion: The driving performance with mini steering wheel-lever system and joystick control system showed no significant statistical difference compared to conventional system in the driving simulator. Application: This study can be used to design primary controls with driver-by-wire technology for adaptive vehicle and to improve their community mobility for people with severe physical disabilities.