• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.628-637
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• 2017

The automobile industry has developed Advanced Driver Assistance Systems (ADASs) to prevent traffic accidents and reduce the burden for drivers. One example is the Lane Keeping Assistance System (LKAS), which was developed for automotive vehicle systems for safety and better driving. The main system of the LKAS supports the driver while maintaining the vehicle within a lane. LKAS uses a radar sensor and camera sensor to collect information about the vehicle's position in the lane and send commands to the actuator to influence the lateral movement of the vehicle if necessary. Recently, vehicles equipped with LKAS have become commercially available. Test procedures for international LKAS evaluation are being discussed and developed by international committees, such as the International Organization for Standardization and United Nations Economic Commission for Europe. In Korea, an evaluation of LKASs for car safety is being planned by the Korean New Car Assessment Program. Therefore, test procedures should be developed for LKASs that are suitable for the domestic road environment while accommodating international standards. We developed a test scenario for LKASs and propose a formula for obtaining the target relative distance. To validate the methods, a series of experiments were conducted using commercially available vehicles equipped with LKAS.

• 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.

• Journal of Auto-vehicle Safety Association
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• v.9 no.4
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• pp.7-13
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• 2017

As automotive industry develops, the demand for increasing traffic safety is growing. Lots of researches about vehicle convenience and safety technology have been implemented. Now, the autonomous driving test is being conducted all over the world, and the autonomous driving regulations are also being developed. Autonomous vehicles are being commercialized, but autonomous vehicle safety has not been guaranteed yet. This paper presents scenarios that assess the safety of autonomous vehicles by identifying the minimum requirements to ensure safety for a variety of situations on highway. In assessing driving safety, seven scenarios were totally selected. Seven scenarios were related to lane keeping and lane change performance in certain situations. These scenarios were verified by analyzing the driving data acquired through actual vehicle driving. Data analysis was implemented via computer simulation. These scenarios are developed based on existing ADAS evaluation and simulation of autonomous vehicle algorithm. Also Safety evaluation factors are developed based on ISO requirements, other papers and the current traffic regulations.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.6
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• pp.730-736
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• 2016

Recent research suggests the various applications of Model Predictive Control on vehicle systems. In numerous cases, nonlinear tire models such as the Magic Formula, which are highly complex and are more detailed than necessary, are used. This paper presents a nonlinear tire model that excludes the region of negative slope but expresses the nonlinear properties of tire well enough for tracking the lane of a racing course. The proposed inverse tire model can also be used to calculate the slip angle from the tire force. Thus, the model can be utilized to design the Model Predictive Controller.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.7
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• pp.575-583
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• 2017

This paper describes the design and evaluation of a driving mode decision algorithm for automated driving for merge situations on highways. For the development of a highly automated driving control algorithm for merge situations, the driving mode decision is crucial for merging appropriately. There are two driving modes: lane keeping and lane changing (merging). The merge mode decision is determined based on the state of the surrounding vehicles and the remaining length of the merge lane. In the merge mode decision algorithm, merge possibility and the desired merge position are decided to change the lane safely and quickly. A safety driving envelope is defined based on the desired driving mode using the information on the surrounding vehicles' behaviors. To obtain the desired steering angle and longitudinal acceleration for maintaining the subject vehicle in the safe driving envelope, a motion planning controller is designed using model predictive control (MPC), with constraints that are decided considering the vehicle dynamics, safe driving envelope, and actuator limit. The proposed control algorithm has been evaluated via computer simulation studies.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.717-722
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• 2003

A driving simulator is a computer-controlled tool to study an interface between a driver and vehicle response by enabling the driver to participate in judging vehicle characteristics. Using the driving simulator, human factor study, vehicle system development and other research can be effectively done under controllable, reproducible and non-dangerous conditions. An Adaptive Cruise Control (ACC) system is generally regarded as a system that can be achieved in the near future without the demanding infrastructure components and technologies. ACC system is an automatic vehicle following system with no human engagement in the longitudinal vehicle direction. And the influence of the driver is substantial in developing the system. Driving characteristic is very different according to the accident riskiness, gender, age and so on. In this research, experiments have been carried out to investigate driving characteristics with the ACC system, using a driving simulator. Participants are 21 male and 19 female. Driving characteristics such as preferred headway-time, lane keeping ability, eye direction, and head movement have been observed and compared between the driving with ACC and the driving without ACC.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.162-171
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• 1999

The most important part in automated transport systems is steering control for lane keeping Most of systems developed so far have used the visual information for steering control. In this study, the steering control algorithm based on visual servoing has been developed and tested by applying it on Radio Controlled(R/C) model car equipped with one CCD camera. We also demonstrated the feasibility of using it as a pre-test car before the real car experiment in developing automated vehicles. In order to solve the problem of the limited spave and load of a model car, remote-brained approach has been taken. For steering control of a model car, the PD controller which uses the look ahead offset to generate control input has been implemented and the characteristics of the controller has been explained in view of kinematics. Some experimental results have been also illustrated so as to show the control performance and stability.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.23.1-23
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• 2001

The unmanned vehicle is composed of three parts the front & side sensor system for keeping the lane and avoiding obstacles, the acceleration & brake control system for longitudinal motion control, and the steering control system for the lateral motion control. Each system helps the unmanned vehicle of which should take notice of its location and recognize obstacles around the place by itself and make a decision how much fast to proceed according to circumstances. During the operation, the control strategy that the vehicle can detect obstacles and avoid collision on the road involves with vehicle velocity very much. Therefore, We have to define a traction system which is powered by DC motor so that, unmanned vehicle can control its velocity accurately. In this study, we find mechanical and ...

• Journal of Auto-vehicle Safety Association
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• v.14 no.1
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• pp.20-25
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• 2022

This paper presents a development of simulation environment for validation of autonomous driving (AD) algorithm based on Robot Operating System (ROS). ROS is one of the commonly-used frameworks utilized to control autonomous vehicles. For the evaluation of AD algorithm, a 3D autonomous driving simulator has been developed based on LGSVL. Two additional sensors are implemented in the simulation vehicle. First, Lidar sensor is mounted on the ego vehicle for real-time driving environment perception. Second, GPS sensor is equipped to estimate ego vehicle's position. With the vehicle sensor configuration in the simulation, the AD algorithm can predict the local environment and determine control commands with motion planning. The simulation environment has been evaluated with lane changing and keeping scenarios. The simulation results show that the proposed 3D simulator can successfully imitate the operation of a real-world vehicle.

• Journal of Auto-vehicle Safety Association
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• v.15 no.4
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• pp.6-15
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• 2023

This paper develops scenarios to evaluate the safety performance of Unmanned Ground Vehicle on military circumstances. The scenarios were created using Pegasus Project 6-layer format. These scenarios consist of straight road, curved road, merging road and crossroad. We adapt these scenarios to unpaved road. The characteristics of unpaved roads were divided into roughness, friction coefficient and road frequency. This adaption is validated via computer simulation. We observe the scan lines of vehicle become tangled of the straight road that make the cognitive abilities of the vehicle low and the lane-keeping is unable when vehicles entering curved off-roads over 40 km/h. The developed scenarios will contribute to enhancing stability from the perspective of introducing autonomous driving technology to Korean military.