• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.11
• /
• pp.1-9
• /
• 2016

Train control systems have changed from wayside electricity-centric to onboard communications-centric. The latest train control system, the CBTC system, has high efficiency for interval control based on two-way radio communications between the onboard and wayside systems. However, since the wayside system is the center of control, the number of input trains to allow a wayside system is limited, and due to the cyclic-path control flows between onboard and wayside systems, headway improvement is limited. In this paper, we propose a train interval-control and train-centric distributed interlocking algorithm for an autonomous train-driving control system. Because an autonomous train-driving control system performs interval and branch control onboard, both tracks and switches are shared resources as well as semaphore elements. The proposed autonomous train-driving control performs train interval control via direct communication between trains or between trains and track-side apparatus, instead of relying on control commands from ground control systems. The proposed interlocking algorithm newly defines the semaphore scheme using a unique key for the shared resource, and a switch that is not accessed at the same time by the interlocking system within each train. The simulated results show the proposed autonomous train-driving control system improves interval control performance, and safe train control is possible with a simplified interlocking algorithm by comparing the proposed train-centric distributed interlocking algorithm and various types of interlock logic performed in existing interlocking systems.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.2
• /
• pp.87-94
• /
• 2015

This paper proposes a situation awareness method based on data fusion and independent objects for autonomous driving in on-road environment. The proposed method, designed to achieve an accurate analysis of driving situations in on-road environment, executes preprocessing tasks that include coordinate transformations, data filtering, and data fusion and independent object based situation assessment to evaluate the collision risks of driving situations and calculate a desired velocity. The method was implemented in an open-source robot operating system called ROS and tested on a closed road with other vehicles. It performed successfully in several scenarios similar to a real road environment.

• The Journal of Korea Robotics Society
• /
• v.5 no.2
• /
• pp.110-119
• /
• 2010

This paper aims to add the autonomous driving capability to the inverted pendulum system which maintains the inverted pendulum upright stably. For the autonomous driving from the starting position to the goal position, the motion control algorithm is proposed based on the dynamics of the inverted pendulum robot. To derive the dynamic model of the inverted pendulum robot, a three dimensional robot coordinate is defined and the velocity jacobian is newly derived. With the analysis of the wheel rolling motion, the dynamics of inverted pendulum robot are derived and used for the motion control algorithm. To maintain the balance of the inverted pendulum, the autonomous driving strategy is derived step by step considering the acceleration, constant velocity and deceleration states simultaneously. The driving experiments of inverted pendulum robot are performed while maintaining the balance of the inverted pendulum. For reading the positions of the inverted pendulum and wheels, only the encoders are utilized to make the system cheap and reliable. Even though the derived dynamics works for the slanted surface, the experiments are carried out in the standardized flat ground using the inverted pendulum robot in this paper. The experimental data for the wheel rolling and inverted pendulum motions are demonstrated for the straight line motion from a start position to the goal position.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.104-104
• /
• 2000

Among durability tests, the accelerated durability test has been widely used to evaluate the durability of vehicle structure and chassis pans in a shon period of time on the designed road which has severe surface conditions. However it increases the drivers fatigue mainly caused by the severe driving conditions. The drivers difficulty of maintaining constant speed and controlling the steering wheel reduces the reliability of test results. The durability test includes the position and distance sensing system for the recognition of the absolute and relative driving position, the driving control system for the control of whole driving circumstance, the emergency system for responding to system errors. AGVDS (Autonomous Guided Vehicle Driving System) was Proved to facilitate the development of now car projects. Therefore the AGVDS we propose will help make the fundamentals for all future traffic systems.

• Journal of Auto-vehicle Safety Association
• /
• v.16 no.1
• /
• pp.55-61
• /
• 2024

The advancement of autonomous driving technology is expected to transform cars beyond mere transportation into multifunctional spaces for relaxation and entertainment. As autonomous driving technology becomes more sophisticated, with no need for direct driver control, the interior space of vehicles is anticipated to be utilized for various purposes. Consequently, the importance of car seats, the component most frequently interacted with by passengers during travel, is expected to significantly rise. However, existing car seats are designed according to a seated posture, necessitating verification for passenger safety and seat structure considerations in the context of autonomous driving, where comfortable postures may differ. For these reasons, it is anticipated that the seats of future autonomous vehicles will evolve with the incorporation of additional safety and convenience features. In this study, a three-axis car simulator was employed to investigate seat angles for comfortable postures of passengers in autonomous driving scenarios. Representative postures were identified to enhance passenger convenience. Furthermore, functional design factors contributing to passenger comfort were applied to conduct seat design, seat structure, and collision analysis, with an analysis of the interrelationships among design factors.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2010.11a
• /
• pp.723-724
• /
• 2010

• The Journal of Korea Robotics Society
• /
• v.17 no.2
• /
• pp.198-208
• /
• 2022

In this paper, an autonomous driving system is implemented for the Segye AI Robot Race Competition that multiple vehicles drive simultaneously. By utilizing the ERP42-racing platform, RTK-GPS, and LiDAR sensors provided in the competition, we propose an autonomous driving system that can drive safely and quickly in a road environment with multiple vehicles. This system consists of a recognition, judgement, and control parts. In the recognition stage, vehicle localization and obstacle detection through waypoint-based LiDAR ROI were performed. In the judgement stage, target velocity setting and obstacle avoidance judgement are determined in consideration of the straight/curved section and the distance between the vehicle and the neighboring vehicle. In the control stage, adaptive cruise longitudinal velocity control based on safe distance and lateral velocity control based on pure-pursuit are performed. To overcome the limited experimental environment, simulation and partial actual experiments were conducted together to develop and verify the proposed algorithms. After that, we participated in the Segye AI Robot Race Competition and performed autonomous driving racing with verified algorithms.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.1
• /
• pp.65-74
• /
• 2024

In recent years, image processing technology has played a critical role in the field of autonomous driving. Among them, image recognition technology is essential for the safety and performance of autonomous vehicles. Therefore, this paper aims to develop a hybrid image recognition system to enhance the safety and performance of autonomous vehicles. In this paper, various image recognition technologies are utilized to construct a system that recognizes and tracks objects in the vehicle's surroundings. Machine learning and deep learning algorithms are employed for this purpose, and objects are identified and classified in real-time through image processing and analysis. Furthermore, this study aims to fuse image processing technology with vehicle control systems to improve the safety and performance of autonomous vehicles. To achieve this, the identified object's information is transmitted to the vehicle control system to enable appropriate autonomous driving responses. The developed hybrid image recognition system in this paper is expected to significantly improve the safety and performance of autonomous vehicles. This is expected to accelerate the commercialization of autonomous vehicles.

• The Journal of Korea Robotics Society
• /
• v.15 no.3
• /
• pp.233-239
• /
• 2020

The aims of this paper is to develop a modular agricultural robot and its autonomous driving algorithm that can be used in field farming. Actually, it is difficult to develop a controller for autonomous agricultural robot that transforming their dynamic characteristics by installation of machine modules. So we develop for the model based control algorithm of rotary machine connected to agricultural robot. Autonomous control algorithm of agricultural robot consists of the path control, velocity control, orientation control. To verify the developed algorithm, we used to analytical techniques that have the advantage of reducing development time and risks. The model is formulated based on the multibody dynamics methods for high accuracy. Their model parameters get from the design parameter and real constructed data. Then we developed the co-simulation that is combined between the multibody dynamics model and control model using the ADAMS and Matlab simulink programs. Using the developed model, we carried out various dynamics simulation in the several rotation speed of blades.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.10a
• /
• pp.274-281
• /
• 1998

This paper describes a visual control of autonomous vehicle using neural network. Visual control for road-following of autonomous vehicle is based on road image from camera. Road points on image are inputs of controller and vehicle speed and steering angle are outputs of controller using neural network. Simulation study confirmed the visual control of road-following using neural network. For experimental test, autonomous electric vehicle is designed and driving test is realized