• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.6
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• pp.182-197
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• 1999

Described in this paper is an optimal driving control algorithm which focused on the improvement of fuel economy and the minimization of pollutant emissions in the parallel type hybrid drivertrain system for transit bus. For the energy balance among components such as engine, induction machine and buttery, the algorithm for power split ration determine is proposed. When it is implemented in the hybrid electric control unit(HECU) , using the sub-optimal method and the approximate technique , it is possible to save the memory , to shorten the calculation time, and to achieve the efficient driving actually. A Shift strategy for automated manual transmission is the other side of the driving control algorithm. It enables to select the optimal gear by using several shift maps which were predefined from the proposed method in this paper, As a results of driving simulation, it is proved that these algorithms make the hybrid drivetrain system to reduce fuel consumption and emissions considerably and to have the ability to the efficient use of battery.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.180-189
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• 2017

Some people who take a driver's license test retake it again because of license cancellation, but most of them take the test for the first time to drive the car. Driving a car is directly linked to life, and the initial correct driving habits are more important than anything else. In particular, it is very important to obtain a license by evaluating the correct driving ability based on objective and fair standards when learning the first driving, because many people acquire a driving license while entering the society for the first time. In this paper, we propose the S / W design and its main functions that can emit high quality drivers through efficient, fair and accurate automated scoring. Through this, it is proposed to improve the automatic grading driver's license system, to prevent traffic accidents, and to reduce traffic accidents through proper driving.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.2
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• pp.101-106
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• 2024

For the commercialization of automated vehicles, it is necessary to create various scenarios that can evaluate driving safety and establish a data system that can verify them. Depending on the vehicle's ODD (Operational Design Domain), there are numerous scenarios with various parameters indicating vehicle driving conditions, but no systematic methodology has been proposed to create and combine scenarios to test them. Therefore, projects are actively underway abroad to establish a scenario library for real-world testing or simulation of autonomous vehicles. However, since it is difficult to obtain data, research is being conducted based on simulations that simulate real road. Therefore, in this study, parameters calculated through individual vehicle trajectory data extracted based on roadside CCTV image-based driving environment DB was proposed through the extracted data. This study can be used as basic data for safety standards for scenarios representing various driving behaviors.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.230-245
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• 2023

The importance of evaluating the safety of Automated Vehicles (AV) is increasing with the advances in autonomous driving technology. Accordingly, an evaluation scenario that defines in advance the situations AV may face while driving is being used to conduct efficient stability evaluation. On the other hand, the single scenarios currently used in conventional evaluations address limited situations within short segments. As a result, there are limitations in evaluating continuous situations that occur on real roads. Therefore, this study developed a set of multiple scenarios that allow for continuous evaluation across entire sections of roads with diverse geometric structures to assess the safety of AV. In particular, the conditions for connecting individual scenarios were defined, and a methodology was proposed for developing concrete multiple scenarios based on the scenario evaluation procedure of the PEGASUS project. Furthermore, a simulation was performed to validate the practicality of these multiple scenarios.

• Journal of Biosystems Engineering
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• v.41 no.4
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• pp.319-327
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• 2016

Purpose: Automated guidance systems (AGSs) for mobile farm machinery have several advantages over manual operation in the crop production industry. Many researchers and companies have tried to develop such a system. However, it is not easy to evaluate the performance of an AGS because there is no established device used to evaluate it that complies with the ISO 12188 standard. The objective of this study was to develop a tracking sensor system using five laser distance measurement sensors. Methods: One sensor-for long-range distance measurement-was used to measure travel distance and velocity. The other four sensors-for mid-range distance measurement-were used to measure lateral deviation. Stationary, manual driving, and A-B line tests were conducted, and the results were compared with the real-time kinematic differential global positioning system (RTK-DGPS) signal used by the AGS. Results: For the stationary test, the average error of the tracking sensor system was 1.99 mm, and the average error of the RTK-DGPS was 15.19 mm. For the two types of driving tests, the data trends were similar. A comparison of the changes in lateral deviation showed that the data stability of the developed tracking system was better. Conclusions: Although the tracking system was not capable of measuring long travel distances under strong sunlight illumination because of the long-range sensor's limitations, this dilemma could be overcome using a higher-performance sensor.

• Journal of Drive and Control
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• v.17 no.4
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• pp.80-86
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• 2020

Autonomous driving is one of the most important new technologies of our time; it has benefits in terms of safety, the environment, and economic issues. Path following algorithms, such as automated lane keeping systems (ALKSs), are key level 3 or higher functions of autonomous driving. Pure-Pursuit and Stanley controllers are widely used because of their good path tracking performance and simplicity. However, with the Pure-Pursuit controller, corner cutting behavior occurs on curved roads, and the Stanley controller has a risk of divergence depending on the response of the steering system. In this study, we use the advantages of each controller to propose a hybrid control strategy that can be stably applied to complex driving environments. The weight of each controller is determined from the global and local curvature indexes calculated from HD map information and the current driving speed. Our experimental results demonstrate the ability of the hybrid controller, which had a cross-track error of under 0.1 m in a virtual environment that simulates K-City, with complex driving environments such as urban areas, community roads, and high-speed driving roads.

• Journal of Auto-vehicle Safety Association
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• v.11 no.4
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• pp.50-56
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• 2019

Recently, automobile industries have developed ADAS, smart cars, connected cars, automated driving systems, which use a variety of sensor systems - ultrasonics, cameras, lidars and radars - and communication systems. It is necessary to examine the electromagnetic immunity of vehicles equipped with those systems. The electromagnetic immunity tests are carried out in an electromagnetic semi anechoic chamber, which is cut off from the outside. It is difficult to create test environments in which the radar sensor systems of vehicles work properly in the test chamber. In this study, test jigs were designed and tested and as a result they are shown to be effective to create test environments for electromagnetic immunity tests of vehicles equipped with radar sensors. We also proposed additional safety standards for immunity tests of vehicles with radar systems that currently do not exist.

• Journal of Auto-vehicle Safety Association
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• v.12 no.4
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• pp.7-12
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• 2020

Recently, automobile industries have developed ADAS, smart cars, connected cars, automated driving systems, which use a variety of sensor systems - ultrasonics, cameras, lidars and radars - and communication systems. It is necessary to examine the electromagnetic immunity of vehicles equipped with the sensor systems due to the fact that the normal operation of those systems is very important to the safety of the vehicles. The electromagnetic immunity tests are carried out in an electromagnetic semi anechoic chamber, which is cut off from the outside. It is difficult to create test environments in which the camera sensor systems of vehicles work properly in the test chamber. In this study, test jigs were designed and tested and as a result they are shown to be effective to create test environments for electromagnetic immunity tests of vehicles equipped with camera sensors. We also proposed additional safety standards for immunity tests of vehicles with camera systems that currently do not exist.

• Journal of Auto-vehicle Safety Association
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• v.13 no.2
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• pp.7-14
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• 2021

Recently, the amount of electrical and electronic systems is increasing rapidly with the development of advanced vehicles such as ADAS, smart cars, connected cars, automated driving systems. It is necessary to examine the electromagnetic compatibility of vehicles equipped with those systems. The standards and regulations for examination of electromagnetic compatibility have been established and revised according to newly introduced electrical and electronic systems. They are administered in some different international standard associations such as ISO, CISPR, UN/ECE and are somewhat complex and bulky. In the study, the improvements and changes in them are tracked and analyzed chronologically. Research of the history of them will be helpful for understanding progress and forecasting the direction of development.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.200-209
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• 2018

This study proposed a method to select existing facilities as a landmark in order to reset accumulated errors of dead reckoning in a tunnel difficult to receive GNSS signals in automated driving. First, related standards and regulations were reviewed in order to survey 'variety' on shapes and installation locations as a feature of facilities. Second, 'recognition' on facilities was examined using image and Lidar sensors. Last, 'regularity' in terms of installation locations and intervals was surveyed through related references. The results of this study selected a fire fighting box / lamp (50m), an evacuation corridor lamp (300m), a lane control system (500m), a maximum / minimum speed limit sign and a jet fan as a candidate landmark to reset positioning errors. Based on those facilities, it was determined that error correction was possible. The results of this study are expected to be used in repositioning of automated driving vehicles in a tunnel.