• Journal of Korean Port Research
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• v.14 no.3
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• pp.291-301
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• 2000

T his paper presents the lateral and longitudinal control algorithm for the driving of a 4WS AGV(Automated Guided Vehicle). The control law to the lateral and longitudinal control of the AGV includes adaptive agin tuning ability, that is the controller gain of the gravity compensated PD controller can be changed on a real-time. The gain tuning law is derived from the Lyapunov direct method using the output error of the reference model and the actual model, And to show the performance of the presented lateral and longitudinal control algorithm, we simulate toe nonlinear AGV equations of the motion by deriving the Newton-Euler Method, The read path is from quay yard area to docking position in loading yard area. The quay yard area is where the quay crane loads the container to the AGV and the docking position is where the container is transferred to the gantry crane. The road types are constructed in a straight line and J-turn. When driving the straight line, the driving velocity is 6㎧ and the J-turn is 3㎧.

• Journal of Auto-vehicle Safety Association
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• v.9 no.3
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• pp.24-30
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• 2017

This paper presents the development of laser scanner based static obstacle detection algorithm for vehicle localization on lane lost section. On urban autonomous driving, vehicle localization is based on lane information, GPS and digital map is required to ensure. However, in actual urban roads, the lane data may not come in due to traffic jams, intersections, weather conditions, faint lanes and so on. For lane lost section, lane based localization is limited or impossible. The proposed algorithm is designed to determine the lane existence by using reliability of front vision data and can be utilized on lane lost section. For the localization, the laser scanner is used to distinguish the static object through estimation and fusion process based on the speed information on radar data. Then, the laser scanner data are clustered to determine if the object is a static obstacle such as a fence, pole, curb and traffic light. The road boundary is extracted and localization is performed to determine the location of the ego vehicle by comparing with digital map by detection algorithm. It is shown that the localization using the proposed algorithm can contribute effectively to safe autonomous driving.

• Advances in Automotive Engineering
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• v.1 no.1
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• pp.123-141
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• 2018

Hardware-in-the-loop (HiL) simulation is a very powerful tool to design, test and verify automotive control systems. However, well-validated and high degree of freedom vehicle models have to be utilized in these simulations in order to obtain realistic results. In this paper, a vehicle dynamics model developed in the Carsim Real Time program environment and its validation has been performed using experimental results. The developed Carsim real time model has been employed in the Tofas R&D hardware-in-the-loop simulator. Experimental and hardware-in-the-loop simulation results have been compared for the standard FMVSS No. 126 test and the results have been found to be in good agreement with each other. Two electronic stability control (ESC) algorithms, named the Basic ESC and the Integrated ESC, taken from the earlier work of the authors have been tested and evaluated in the hardware-in-the-loop simulator. Different evaluation methods have been formulated and used to compare these ESC algorithms. As a result, the Integrated ESC system has been shown superior performance as compared to the Basic ESC algorithm.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.20-25
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• 2022

This paper represents an adaptive Region of Interest (ROI) decision for real-time performance in an autonomous driving perception module. Since the whole automated driving system consists of numerous modules and subdivisions of module occur, it is necessary to consider the characteristics, complexity, and limitations of each module. Furthermore, Light Detection And Ranging (Lidar) sensors require a considerable amount of time. In view of these limitations, division of submodule is inevitable to represent high real-time performance for stable system. This paper proposes ROI to reduce the number of data respect to computation time. ROI is set by a road's design speed and the corresponding ROI is applied differently to each vehicle considering its speed. The simulation model is constructed by ROS, and overall data analysis is conducted by Matlab. The algorithm is validated using real-time driving data in urban environment, and the result shows that ROI provides low computational costs.

• Journal of Korean Society of Transportation
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• v.36 no.2
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• pp.67-85
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• 2018

Vehicle platooning through wireless communication and automated driving technology has become realized. Platooning is a technique in which several vehicles travel at regular intervals while maintaining a minimum safety distance. Truck platooning is of keen interest because it contributes to preventing truck crashes and reducing vehicle emissions, in addition to the increase in truck flow capacity. However, it should be noted that interactions between vehicle platoons and adjacent manually-driven vehicles (MV) significantly give an impact on the performance of traffic flow. In particular, when vehicles entering from on-ramp attempt to merge into the mainstream of freeway, proper interactions by adjusting platoon size and inter-platoon spacing are required to maximize traffic performance. This study developed a methodology for establishing operational strategies for truck platoonings on freeway on-ramp areas. Average speed and conflict rate were used as measure of effectiveness (MOE) to evaluate operational efficiency and safety. Microscopic traffic simulation experiments using VISSIM were conducted to evaluate the effectiveness of various platooning scenarios. A decision making process for selecting better platoon operations to satisfy operations and safety requirements was proposed. It was revealed that a platoon operating scenario with 50m inter-platoon spacing and the platoon consisting of 6 vehicles outperformed other scenarios. The proposed methodology would effectively support the realization of novel traffic management concepts in the era of automated driving environments.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.57-62
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• 2002

This study described the specification and configuration of developed fixed-base AHS (Automated Highway System) simulator fur the human factors researches, and its usability evaluation results after riding 120, 140, and 160kph automated driving speed. As the results, this study suggested the subjects' preferences and opinions about simulator and AHS configurations that would help to establish the AHS R&D plan and driver-vehicle/road interface design guidelines as the basic researches of the AHS human factors.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.197-217
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• 2022

As automated vehicle(AV) accidents continue to occur, the importance of safety verification to ensure the safety and reliability of automated driving system(ADS) is being emphasized. In order to encure safety and reliability, it is necessary to define an operational design domain(ODD) of the ADS and verify the safety of the ADS while evaluating its ability to respond in situations outside of the ODD. To this, international associations such as SAE, BSI, NHTSA, ISO, etc. stipulate ODD standards. However, in Korea, there is no standard for the ODD, so automated vehicles's ODD expression method and safety verification and evaluation are not properly conducted. Therefore, this study analyzed overseas ODD standards and selected suitable ODD for safety verification and evaluation, and presented evaluation elements for ADS safety verification and evaluation. In particular, evaluation elements were selected by analyzing the evaluation environment of the automated driving experimental city (K-City) that supports the development of ADS technology.

• Journal of Auto-vehicle Safety Association
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• v.14 no.3
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• pp.65-70
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• 2022

Lane change in urban environments is a challenge for both human-driving and automated driving due to their complexity and non-linearity. With the recent development of deep-learning, the use of the RNN network, which uses time series data, has become the mainstream in this field. Many researches using RNN show high accuracy in highway environments, but still do not for urban environments where the surrounding situation is complex and rapidly changing. Therefore, this paper proposes a lane change possibility decision network by adopting Attention layer, which is an SOTA in the field of seq2seq. By weighting each time step within a given time horizon, the context of the road situation is more human-like. A total 7D vectors of x, y distances and longitudinal relative speed of side front and rear vehicles, and longitudinal speed of ego vehicle were used as input. A total 5,614 expert data of 4,098 yield cases and 1,516 non-yield cases were used for training, and the performance of this network was tested through 1,817 data. Our network achieves 99.641% of test accuracy, which is about 4% higher than a network using only LSTM in an urban environment. Furthermore, it shows robust behavior to false-positive or true-negative objects.

• Journal of Auto-vehicle Safety Association
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• v.11 no.3
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• pp.13-18
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• 2019

According to the development of autonomous vehicles worldwide, the driver's posture may not be a normal posture but the various seating positions. Recently, a numbers of research activities has been focused to protect of driver and passengers in various seating positions as well as seating postures. In this paper, the occupant injury severity was evaluated with different seat positions, seatback angles and TTF times.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.96-106
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• 1999

In this study, the advanced shift control algorithm for parallel type hybrid drivetrain system with automated manual transmission(AMT) is proposed. The AMT can be easily realized by mounting the pneumatic actuators and sensors on the clutch and shift levers of the conventional manual transmission. By using the electronic-controlled AMT, engine and induction machine, it is possible to achieve the integrated control of overall system for the efficiency and the performance of the vehicle. Performing the speed control of the induction machine and the engine, the synchronization at gear shifting and the smooth engagement of clutch can be guaranteed. And it enables to reduce the shift shock and shorten the shift time. Hence, it results in the improvement of shift quality and the driving comfort of the vehicle. Dynamometer-based experiments are carried out to prove the validity of the proposed shift control algorithm.