• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.57-69
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• 2022

Recently, as interest in self-driving cars has increased worldwide, research and development on the Advanced Driver Assist System is actively underway. Among them, the purpose of Adaptive Cruise Control (ACC) is to minimize the driver's driving fatigue through the control of the vehicle's longitudinal speed and relative distance. In this study, for the research of the ACC test in the real environment, the real-road test was conducted based on domestic-road test scenario proposed in preceding study, considering ISO 15622 test method. In this case, the distance measurement method using the dual camera was verified by comparing and analyzing the result of using the dual camera and the result of using the measurement equipment. As a result of the comparison, two results could be derived. First, the relative distance after stabilizing the ACC was compared. As a result of the comparison, it was found that the minimum error rate was 0.251% in the first test of scenario 8 and the maximum error rate was 4.202% in the third test of scenario 9. Second, the result of the same time was compared. As a result of the comparison, it was found that the minimum error rate was 0.000% in the second test of scenario 10 and the maximum error rate was 9.945% in the second test of scenario 1. However, the average error rate for all scenarios was within 3%. It was determined that the representative cause of the maximum error occurred in the dual camera installed in the test vehicle. There were problems such as shaking caused by road surface vibration and air resistance during driving, changes in ambient brightness, and the process of focusing the video. Accordingly, it was determined that the result of calculating the distance to the preceding vehicle in the image where the problem occurred was incorrect. In the development stage of ADAS such as ACC, it is judged that only dual cameras can reduce the cost burden according to the above derivation of test results.

• The Journal of Korea Robotics Society
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• v.12 no.3
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• pp.297-305
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• 2017

As the development of autonomous vehicles becomes realistic, many automobile manufacturers and components producers aim to develop 'completely autonomous driving'. ADAS (Advanced Driver Assistance Systems) which has been applied in automobile recently, supports the driver in controlling lane maintenance, speed and direction in a single lane based on limited road environment. Although technologies of obstacles avoidance on the obstacle environment have been developed, they concentrates on simple obstacle avoidances, not considering the control of the actual vehicle in the real situation which makes drivers feel unsafe from the sudden change of the wheel and the speed of the vehicle. In order to develop the 'completely autonomous driving' automobile which perceives the surrounding environment by itself and operates, ability of the vehicle should be enhanced in a way human driver does. In this sense, this paper intends to establish a strategy with which autonomous vehicles behave human-friendly based on vehicle dynamics through the reinforcement learning that is based on Q-learning, a type of machine learning. The obstacle avoidance reinforcement learning proceeded in 5 simulations. The reward rule has been set in the experiment so that the car can learn by itself with recurring events, allowing the experiment to have the similar environment to the one when humans drive. Driving Simulator has been used to verify results of the reinforcement learning. The ultimate goal of this study is to enable autonomous vehicles avoid obstacles in a human-friendly way when obstacles appear in their sight, using controlling methods that have previously been learned in various conditions through the reinforcement learning.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.68-80
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• 2016

This study proposes the traffic prediction and optimal traffic control system based on cell transmission model and genetic algorithm in cloud environment. The proposed prediction and control system consists of four parts. 1) Data preprocessing module detects and imputes the corrupted data and missing data points. 2) Data-driven traffic prediction module predicts the future traffic state using Multi-level K-Nearest Neighbor (MK-NN) Algorithm with stored historical data in SQL database. 3) Online traffic simulation module simulates the future traffic state in various situations including accident, road work, and extreme weather condition with predicted traffic data by MK-NN. 4) Optimal road control module produces the control strategy for large road network with cell transmission model and genetic algorithm. The results show that proposed system can effectively reduce the Vehicle Hours Traveled upto 60%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.152-164
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• 2015

A rapid development of semiconductors, sensors and mobile network technologies has enable that the embedded device includes high sensitivity sensors, wireless communication modules and a video processing module for vehicular environment, and many researchers have been actively studying the smart car technology combined on the high performance embedded devices. The vehicle is increased as the development of society, and the risk of accidents is increasing gradually. Thus, the advanced driver assistance system providing the vehicular status and the surrounding environment of the vehicle to the driver using various sensor data is actively studied. In this paper, we design and implement the smart vehicular camera device providing the V2X communication and gathering environment information. And we studied the method to create the metadata from a received video data and sensor data using video analysis algorithm. In addition, we invent S-ROI, D-ROI methods that set a region of interest in a video frame to improve calculation performance. We performed the performance evaluation for two ROI methods. As the result, we confirmed the video processing speed that S-ROI is 3.0 times and D-ROI is 4.8 times better than a full frame analysis.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.2
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• pp.30-42
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• 2021

The amount of compensation and the number of cases owing to car damage from pot holes on highways across the country increased by about 4.2 times and 3.5 times, respectively, in 2019 compared to 2015. Due to the increase in damage caused by these road hazards, the Ministry of Land, Infrastructure and Transport is developing technologies and services that can collect road hazard information by using devices on commercial vehicles (DTGs, black boxes, ADASs). In preparation for the development of these technologies, this study conducted an integrated assessment of algorithms developed for interrupted-flow and uninterrupted-flow traffic under three scenarios in order to provide road hazard information to drivers and road managers. As a result, the overall accuracy of the integrated assessment was derived at 81.88%. Errors generated in this integrated assessment reflect only missing data in less than 1 minute, GPS coordinate location and algorithm related errors, taking into account the purpose and assumptions of the assessment. Among them, we derive an accuracy of 90.15%overall by calibrating GPS error data. The results of this study can be used as basic data for improving the accuracy of location-based information collected by commercial vehicles and for policy development.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.174-192
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• 2021

The LIDAR sensor, which provides higher cognitive performance than cameras and radar, is difficult to apply to ADAS or autonomous driving because of its high price. On the other hand, as the price is decreasing rapidly, expectations are rising to improve existing autonomous driving functions by taking advantage of the LIDAR sensor. In level 3 autonomous vehicles, when a dangerous situation in the cognitive module occurs due to a sensor defect or sensor limit, the driver must take control of the vehicle for manual driving. If the driver does not respond to the request, the system must automatically kick in and implement a minimum risk maneuver to maintain the risk within a tolerable level. In this study, based on this background, a LIDAR-based LKS MRM algorithm was developed for the case when the normal operation of LKS was not possible due to troubles in the cognitive system. From point cloud data collected by LIDAR, the algorithm generates the trajectory of the vehicle in front through object clustering and converts it to the target waypoints of its own. Hence, if the camera-based LKS is not operating normally, LIDAR-based path tracking control is performed as MRM. The HAZOP method was used to identify the risk sources in the LKS cognitive systems. B, and based on this, test scenarios were derived and used in the validation process by simulation. The simulation results indicated that the LIDAR-based LKS MRM algorithm of this study prevents lane departure in dangerous situations caused by various problems or difficulties in the LKS cognitive systems and could prevent possible traffic accidents.

• The Korean Journal of Air & Space Law and Policy
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• v.23 no.2
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• pp.115-136
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• 2008

The development of the aviation technology is beyond the people's imagination. For example, with some exaggeration, If the autopilot engage upon take off, You will realize that you are on the centerline of the foggy JFK runway 13R after 15 hours with only once or twice of intervention. But the more aviation technology develops, the more responsible the pilot will be who has the final authority of the aviation safety. In the JAL 706 accident caused by unidentified reason, the pilot increased pitch abruptly and overrode the control from the autopilot. The result of this process made the death of a flight attendant and some injuries of a few passengers. The district court found the pilot not guilty at the first trial on the ground that the control override was not connected to the possibility of foresight and avoidance of the human death. The pilot was proved to be innocent through the analysis of the DFDR and ADAS that the override did not precede the unidentified pitch up motion. The judicial precedent related to aviation accidents in Korea requires pilots' absolute and extended care compared to the ordinarily prudent or reasonably careful behaviors in the vehicle and medical accidents. Although there is some controversy about the standard care, the care required in the actual operation of high tech aircraft by a pilot should include objective and standard care and be judged by analysis of the scientific data. Although the pilot maintained the unusual hi speed that doesn't have safety margin and descended under turbulence in case of the JAL 706 accident, the court negatived its relation to the cause of pitch up. Also, the override of the control after initial pitch up might have caused the possibility of the death and injury, but the court denied it. Because of this complex cause of the aviation accidents, it is important for a court to figure out the core reason of the event and casual relationship with the pilot Now, It is required that the judgement of negligence in the aviation accidents should include an objective care with scientific data from simulated circumstances(or a simulator) as the Japanese court not from the theory of vehicle's negligence.

• Korean Journal of Food Science and Technology
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• v.53 no.3
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• pp.278-289
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• 2021

The rapid aging of society has led to a surge in cognitive dysfunction in the elderly. As there is limited evidence for the development of dementia in medicine, a shift in focus on prevention strategies using bioactive compounds in food is required. This systematic review evaluated the effects of various bioactive compounds on age-associated cognitive decline. The literature was searched for terms related to bioactive compounds in cognitive decline and article selection was limited to clinical randomized controlled trials for a single bioactive compound. We identified 21 studies that evaluated the strength of the evidence. ω-3 fatty acids and vitamin B presented a strong evidence level, whereas vitamin D and E, anserine/carnosine, and chromium were defined as having moderate levels of evidence. ω-3 fatty acids relieved cognitive decline and reduced amyloid β-related protein accumulation. Vitamin B decreased homocysteine levels, which is accompanied by alleviation of cognitive function. In conclusion, ω-3 and vitamin B have the potential to improve age-associated cognitive decline.