• 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 Korean Society for Quality Management
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• v.46 no.4
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• pp.973-982
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• 2018

Purpose: The purpose of this study is to develop an effective simulation modeling formalism for autonomous control systems, such as unmanned aerial vehicles and unmanned surface vehicles. The proposed simulation modeling formalism can be used to evaluate the quality and effectiveness of autonomous control systems. Methods: The proposed simulation modeling formalism is developed by extending the classic DEVS (Discrete Event Systems Specifications) formalism. The main advantages of the classic DEVS formalism includes its rigorous formal definition as well as its support for the specification of discrete event models in a hierarchical and modular manner. Results: Although the classic DEVS formalism has been a popular modeling tool, it has limitations in describing an autonomous control system which needs to make decisions by its own. As a result, we proposed an extended DEVS formalism which enables the effective description of internal decisions according to its conditional variables. Conclusion: The extended DEVS formalism overcomes the limitations of the classic DEVS formalism, and it can be used for the effectiveness simulation of autonomous weapon systems.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.3
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• pp.441-450
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• 2022

The introduction of autonomous underwater gliders (AUGs) specifically addresses the reduction of operational costs that were previously prohibited with conventional autonomous underwater vehicles (AUVs) using a "scaling-down" design philosophy by utilizing the characteristics of autonomous drifters to far extend operation duration and coverage. Long-duration, wide-area missions raise the cost and complexity of in-water testing for novel approaches to autonomous mission planning. As a result, a simulator that supports the rapid design, development, and testing of autonomy solutions across a wide range using software-in-the-loop simulation at faster-than-real-time speeds becomes critical. This paper describes a faster-than-real-time AUG simulator that can support high-resolution bathymetry for a wide variety of ocean environments, including ocean currents, various sensors, and vehicle dynamics. On top of the de facto standard ROS-Gazebo framework and open-sourced underwater vehicle simulation packages, features specific to AUGs for ocean mapping are developed. For vehicle dynamics, the next-generation hybrid autonomous underwater gliders (Hybrid-AUGs) operate with both the buoyancy engine and the thrusters to improve navigation for bathymetry mappings, e.g., line trajectory, are is implemented since because it can also describe conventional AUGs without the thrusters. The simulation results are validated with experiments while operating at 120 times faster than the real-time.

• Journal of the Korea Society for Simulation
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• v.8 no.1
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• pp.89-99
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• 1999

The major objective of this research is to propose a design architecture for autonomous defense systems for supporting highly intelligent behavior by combining decision, perception, and action components. Systems with such high levels of autonomy are critical for advanced battlefield missions. By integrating a plenty of advanced modeling concepts such as system entity structure, endomorphic modeling, engine-based modeling, and hierarchical encapsulation & abstraction principle, we have proposed four layered design methodology for autonomous defense systems that can support an intelligent behavior under the complicated and unstable warfare. Proposed methodology has been successfully applied to a design of autonomous tank systems capable of supporting the autonomous planning, sensing, control, and diagnosis.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.6
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• pp.473-481
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• 2023

In this study, a simulation system was developed to verify autonomous navigation algorithm in complex maritime traffic areas. In particular, real-world maritime traffic scenario was applied by considering near real-time maritime traffic information provided by Korean e-Navigation service. For this, a navigation simulation system of Unmanned Surface Vehicle (USV) was integrated with an e-Navigation equipment, called Electronic Chart System (ECS). To verify autonomous navigation algorithm in the simulation system, initial conditions including initial position of an own ship and a set of paths for the ship to follow are assigned by an operator. Then, considering real-world maritime traffic information obtained from the service, the simulation is implemented in which the ship repeatedly travels by avoiding surrounding obstacles (e.g., approaching ships). In this paper, the developed simulation system and its application on verification of the autonomous navigation algorithm in complex maritime traffic areas are introduced.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.70-86
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• 2022

An autonomous demand-responsive bus with mobility-on-demand service is an innovative transport compensating for the disadvantages of an autonomous bus and a demand-responsive bus with mobility-on-demand service. However, less attention has been paid to the quantitative impact assessment of the autonomous demand-responsive bus due to the technological complexity of the autonomous demand-responsive bus. This study simulates autonomous demand-responsive bus trips by reinforcement learning on a microscopic traffic simulation to quantify the impact of the autonomous demand-responsive bus. The Chungju campus of the Korea National University of Transportation is selected as a testbed. Simulation results show that the introduction of the autonomous demand-responsive bus can reduce the wait time of passengers, average control delay, and increase the traffic speed compared to the results with fixed route bus service. This study contributes to the quantitative evaluation of the autonomous demand-responsive bus.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.196-196
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• 2000

This paper describes a lateral guidance system of an autonomous vehicle, using a neural network model of magneto-resistive sensor and magnetic fields. The model equation was compared with experimental sensing data. We found that the experimental result has a negligible difference from the modeling equation result. We verified that the modeling equation can be used in simulations. As the neural network controller acquires magnetic field values(B$\_$x/, B$\_$y/, B$\_$z/) from the three-axis, the controller outputs a steering angle. The controller uses the back-propagation algorithms of neural network. The learning pattern acquisition was obtained using computer simulation, which is more exact than human driving. The simulation program was developed in order to verify the acquisition of the teaming pattern, teaming itself, and the adequacy of the design controller. The performance of the controller can be verified through simulation. The real autonomous electric vehicle using neural network controller verified good results.

• Journal of Auto-vehicle Safety Association
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• v.14 no.1
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• pp.39-44
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• 2022

This paper presents a development of throttle and brake controller for autonomous vehicle simulation environment. Most of 3D simulator control autonomous vehicle by throttle and brake command. Therefore additional longitudinal controller is required to calculate pedal input from desired acceleration. The controller consists of two parts, feedback controller and feedforward controller. The feedback controller is designed to compensate error between the actual acceleration and desired acceleration calculated from autonomous driving algorithm. The feedforward controller is designed for fast response and the output is determined by the actual vehicle speed and desired acceleration. To verify the performance of the controller, simulations were conducted for various scenarios, and it was confirmed that the controller can successfully follow the target acceleration.

• Journal of Auto-vehicle Safety Association
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• v.15 no.3
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• pp.34-42
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• 2023

Simulation-based virtual testing is known to be a major requirement for verifying the safety of autonomous driving functions. However, in the simulation environment, there is a difficulty in that all driving environments related to the autonomous driving system must be realistically modeled. In particular, C-ITS (Cooperative-Intelligent Transport Systems) is essential for urban autonomous driving of Lv.4, but the approach to modeling for C-ITS service in the MILS (Model in the Loop Simulation) environment is not yet clear. Therefore, this paper aims to deal with V2X (Vehicle to Everything) modeling methods to effectively apply C-ITS-based autonomous cooperative driving services in the MILS environment. First, major C-ITS services and use cases for autonomous cooperative driving are analyzed, and a modeling method of V2X signals for C-ITS service simulation is proposed. Based on the modeled V2X messages, the validity of the proposed approach is reviewed through simulations on the C-ITS service use case.

• Journal of Biosystems Engineering
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• v.21 no.2
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• pp.167-174
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• 1996

A Fuzzy Logic Controller(FLC) was developed for the autonomous operation of speedsprayer in an orchard. The autonomous operation with the FLC was graphically simulated under the real condition of the orchard. Image processing was used to find out the direction of running and four ultrasonic sensors were used to detect obstacles for the running. The simulation results showed that the speedsprayer could be operated autonomously with the FLC combined with the image processing and the ultrasonic sensors.