• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.183-200
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• 2022

A variety of simulation approaches based on automated driving technologies have been proposed to develop traffic operations strategies to prevent traffic crashes and alleviate congestion. The maneuver of simulated autonomous vehicles (AVs) needs to be realistic and be effectively differentiated from the behavior of manually driven vehicles (MVs). However, the verification of simulated AV maneuvers is limited due to the difficulty in collecting actual AVs trajectory and interaction data with MVs. The purpose of this study is to develop a methodology to evaluate the suitability of AV maneuvers based on both driving and traffic simulation experiments. The proposed evaluation framework includes the requirements for the behavior of individual AVs and the traffic stream performance resulting from the interactions with surrounding vehicles. A driving simulation approach is adopted to evaluate the feasibility of maneuvering of individual AVs. Meanwhile, traffic simulations are used to evaluate whether the impact of AVs on the performance of traffic stream is reasonable. The outcome of this study is expected to be used as a fundamental for the design and evaluation of transportation systems using automated driving technologies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.195-211
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• 2023

For the commercialization For the commercialization of autonomous vehicles (AV), the operational design domain (ODD) of automated driving systems (ADS) is to be clearly defined. A common language and consistent format must be prepared so that AV-related stakeholders can understand ODD at the same level. Therefore, overseas countries are presenting a standardized ODD framework and developing scenarios that can evaluate ADS-specific functions based on ODD. However, ODD includes conditions reflecting the characteristics of each country, such as road environment, weather environment, and traffic environment. Thus, it is necessary to clearly understand the meaning of the items defined overseas and to harmonize them to reflect the specific domestic conditions. Therefore, in this study, domestic optimization of the ODD classification system was performed by analyzing the domestic driving environment based on international standards. The driving environment of currently operating self-driving car test districts (Sangam, Seoul, and Gwangju) was investigated using the developed domestic ODD items. Then, based on the results obtained, the ranges of the ODDs in each test district were determined and compared.

• International Journal of Automotive Technology
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• v.5 no.2
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• pp.135-144
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• 2004

In this paper, the model-matching control in the longitudinal autonomous driving system is investigated by vehicle dynamics simulation, which contains nonlinear subcomponents and simplified subcomponents. The design of the robust model-matching controller is performed by the characteristics of the 2 degrees of freedom controller, which is composed of the feedforward compensator and the feedback compensator. It makes the characteristics of tractive and brake force to be equivalent to the specific transfer function, which is suggested as the reference model. Mathematical models of vehicle dynamic analysis including the model-matching control are constructed for computer simulation. Then, simple examples on open-loop simulation without any controller and closed loop simulation with the model-matching controller are applied to check the validity of the robust controller. As the practical example, the autonomous driving system in the longitudinal direction is adopted. It is proved that the model-matching control is effective and adequate to the disturbances and the perturbations, which are shown in the responses of the change of a vehicle mass and a road gradient.

• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.565-570
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• 2021

Agriculture in South Korea is losing productivity due to the lack of manpower as aging population increases. To overcome this, the agricultural robot market is growing rapidly, and research is being conducted on remote control and autonomous driving of agricultural robots. This work designs the appearance and structure of agricultural robots and implements the devices and control systems for driving. By utilizing and optimizing LiDAR sensors, we applied object recognition technology, which is an essential function for autonomous driving. This can reduce labor costs and improve productivity of transportation tasks that require the most labor in agriculture.

• 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.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.16 no.2
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• pp.1-11
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• 2008

Increasing demand for improved reliability and survivability of mission-critical systems is driving the development of health monitoring and Automated Contingency Management (ACM) systems. An ACM system is expected to adapt autonomously to fault conditions with the goal of still achieving mission objectives by allowing some degradation in system performance within permissible limits. ACM performance depends on supporting technologies like sensors and anomaly detection, diagnostic/prognostic and reasoning algorithms. This paper presents the development of a generic prototype test bench software framework for developing and validating ACM systems for advanced propulsion systems called the Propulsion ACM (PACM) Test Bench. The architecture has been implemented for a Monopropellant Propulsion System (MPS) to demonstrate the validity of the approach. A Simulink model of the MPS has been developed along with a fault injection module. It has been shown that the ACM system is capable of mitigating the failures by searching for an optimal strategy. Furthermore, the concepts of Validation and Verification (V&V) of such systems are introduced with relevant examples.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1793-1798
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• 2011

The railway structure for a rubber-wheeled automated guide-way transit system consists of a driveway and a guide-way. The most important factor of this system is the driveway and the guide-way aligned with each other, especially for curves and inclines section. The conventional construction method caused many problems such as discordancy by constructing the driveway before constructing the guide-way. Therefore, in this paper we introduce a new method of constructing a railway for a rubber-wheeled light rail vehicle; the new method of constructing the guide-way beforehand as a preceding process. The new method for AGT railway system can simplify the construction process and thus the construction costs may be reduced. It should also improve the driving performance and the comfortability in operating of a light rail vehicle.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.704-709
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• 1998

An automated calibration system of sound level meters was developed and tested. As a standard sound source, the speaker unit(Forstex FE208) cabineted by 440 * 390 * 490 mm$^{3}$(LHW) volume wood box was adopted. Including this source, the driving part was found out to have a good linearity of sound pressure output vs AC input. We use the Hybrid-Bisect, /Newton-Raphson method modified by the linearity as searching algorithm. Personal computer and program do the control, measurements, and calculations and finally do the accumulation of useful data and results. Several trials of automatic calibration using this developed system give reliable results.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.653-657
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• 2005

AGV is very useful equipment to transfer containers in automated container terminal. AGV must have Obstacle Detection System (ODS) for port automation. ODS needs the function to classify some specified object from background in acquired data. And it must be able to track classified moving objects. Finally, ODS could determine its next action for safe driving whether it should do emergency stop or speed down, or it should change its deriving lane. For these functions, ODS can have many different kinds of algorithm. In this paper, we present one of AGV to be used in automated container terminal.