• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.3
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• pp.40-48
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• 2022

An automated material handling system (AMHS) has been emerging as an important factor in the semiconductor wafer manufacturing industry. In general, an automated guided vehicle (AGV) in the Fab's AMHS travels hundreds of miles on guided paths to transport a lot through hundreds of operations. The AMHS aims to transfer wafers while ensuring a short delivery time and high operational reliability. Many linear and analytic approaches have evaluated and improved the performance of the AMHS under a deterministic environment. However, the analytic approaches cannot consider a non-linear, non-convex, and black-box performance measurement of the AMHS owing to the AMHS's complexity and uncertainty. Unexpected vehicle congestion increases the delivery time and deteriorates the Fab's production efficiency. In this study, we propose a Q-Learning based dynamic routing algorithm considering vehicle congestion to reduce the delivery time. The proposed algorithm captures time-variant vehicle traffic and decreases vehicle congestion. Through simulation experiments, we confirm that the proposed algorithm finds an efficient path for the vehicles compared to benchmark algorithms with a reduced mean and decreased standard deviation of the delivery time in the Fab's AMHS.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2016.05a
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• pp.211-212
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• 2016

It is important to adopt an operation system to operate the Automated warehouses using limited resources such as space, mobile racks, and forklift. The main purpose from the operation system is to reduce the length of moving and time for both mobile racks and forklift. The complexity of the warehouse will be higher because the racks and vehicles are moving at the same time. This complexity influences badly so the operation system has to control it well. Not only layout or receipt or issue, but also conflict between mobile racks and vehicles give more complexity to the warehouse. This paper aims to fine the proper operation method related to the layout and the cargo assignment.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.113-122
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• 2018

In level 3 automated vehicles, drivers are expected to encounter transition of control when the system reaches its limit. Drivers need to refocus their attention on the road ahead and gain situational awareness. Appropriate information should be conveyed during this period in order to prevent human errors. In this paper, we defined the takeover process as 'in-the-middle-of-the-loop' and conducted Task Analysis and Work Domain Analysis to find out information requirements. As a result, we specified required information types and interface considerations. Moreover, we conducted an experimental study to find how the information types affect drivers on situation awareness, cognitive load and reaction time. Consequently, we found different information on system transparency should be conveyed depending on the urgency of takeover situation and driver guidance could help drivers with better situation awareness after the takeover.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.3
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• pp.97-106
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• 2024

The Data Storage System for Automated Driving(DSSAD) is a system that records driving information of Lv.4 or higher autonomous vehicles and is different from EDR that records car information in emergency situations. The study of DSSAD recordings is important for responding to various events that may occur in the future commercialization of Lv.4 autonomous vehicles. Therefore, in this study, we conducted a expressway automated driving demonstration and analyzed the collected data to derive the recording elements of DSSAD. During our two-year demonstration of autonomous driving on expressways, we collected and analyzed instances of disengagement. Our findings indicate that 51.6% of disengagement on expressways occurred during lane changes. From the study, we have identified DSSAD record elements for analyzing disengagement situations. Furthermore, implications of future research direction of disengagement analysis were presented.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.4
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• pp.107-121
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• 2017

This study conducted a 3-stage survey and simulation experiment to identify the impact of vehicle platoons on car-following behavior of manually-driven vehicles. Vehicle maneuvering data obtained from driving simulations was statistically analyzed based on three measures including average speed, acceleration noise, and offset to represent the deviation of lateral movements. Results indicate that MV drivers tended to have psychological burden while driving in automated vehicle platooning environments, which resulted in different vehicle maneuvers. It is expected that the outcome of this study would be useful fundamentals in developing various traffic operations strategies for managing mixed traffic stream consisting of MVs and autonomous vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.6
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• pp.21-36
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• 2015

These days Automated Vehicle(AV) has been receiving attention as a fundamental solution to resolve the various transportation problems and various researches related to the benefits of AV have been done. However, previous researches mainly analyzed the effects in the virtual network. The purpose of this research is to predict and to find out the benefits by introducing the Automated Vehicle to present road traffic system. Thus, the study analyzes the traffic-flow changes of Gyeongbu freeway Seoul-Singal basic section which is planned for setting the test-bed. The results show that Automated Vehicle can have negative effects on the traffic-flow in low volume of LOS A and B. However, the average speed increases and the traffic density decreases in more than LOS C, the traffic volume increase. Therefore, the introduction of Automated Vehicle achieves positive effect on various transportation problems such as the traffic congestion.

• Journal of the Korean Society for Railway
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• v.9 no.5 s.36
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• pp.561-568
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• 2006

Dynamic equations of motion for the interaction system of bridge and vehicle are derived to investigate the dynamic responses of bridge and vehicles induced by moving automated guide-way transit(AGT) vehicle and surface roughness of bridge. The vehicle model for ACT vehicle is idealized as 11 DOF including yawing, lateral translation and steering of wheels, and the bridges are modeled with finite element method. The AGT vehicle model was verified by experimental study. Parametric studies are carried out to investigate the effect of vehicle speed, surface roughness, stiffness and damping of the suspension system, AGT vehicles and dynamic wheel loads of the AGT vehicles. From the parametric study it can be seen that the dynamic incremental factor of the bridge and dynamic responses of vehicles have a tendency to increase with vehicle speeds, surface roughness and the stiffness of AGT vehicle suspension system. On the other hand those dynamic wheel loads have tendencies to decrease in according to increase of damping of the suspension system.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.39-52
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• 2021

This paper presents a longitudinal acceleration controller that can be applied to real vehicles (nonlinear and time-varing systems) with only a simple experiment regardless of the type of vehicle and the control interface structure. The controller consists of a feedforward term for fast response, a zero-throttle acceleration compensation term, and a feedback term (P gain) to compensate for errors in the feedforward term, and another feedback term (I gain) to respond to disturbances such as slope. In order to easily apply it to real vehicles, there are only two tuning parameters, feedforward terms of throttle and brake control. And the remaining parameters can be calculated immediately when the two parameters are decided. The tuning procedure is also unified so that it can be quickly and easily applied to various vehicles. The performance of the controller was evaluated using MATLAB/Simulink and Truksim's European Ben model. In addition, the controller was successfully implemented to 3 medium-sized vehicle (HMC Solati), which is composed of different control interface characteristic. Vehicle driving performance was evaluated on the test track and on the urban roads in Siheung and Seoul.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.182-199
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• 2023

Since 2021, government departments have been promoting Automated Driving Technology Development and Innovation Project as national research and development(R&D) project. The automated vehicles and service technologies developed as part of these projects are planned to be subsequently provided to the public at the selected Living Lab City. Therefore, it is important to determine a spatial area and operation section that enables safe and stable automated driving, depending on the purpose and characteristics of the target service. In this study, the static Operational Design Domain(ODD) elements for Level 4 automated driving services were reclassified by reviewing previously published papers and related literature surveys and investigating field data. Spatial analysis techniques were used to consider the reclassified ODD elements for level 4 in the real area of level 3 automated driving services because it is important to reflect the spatial factors affecting safety related to real automated driving technologies and services. Consequently, a total of six driving mode changes(disengagement) were derived through spatial information analysis techniques, and the factors affecting the safety of automated driving were crosswalk, traffic light, intersection, bicycle road, pocket lane, caution sign, and median strip. This spatial factor analysis method is expected to be useful for determining special areas for the automated driving service.