• International Journal of Highway Engineering
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• v.15 no.5
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• pp.111-122
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• 2013

PURPOSES : The purpose of this system (Rear Lighting System) is to provide illumination for the driver to operate the commercial vehicle safely after dark in highway, to increase the conspicuity of the vehicle, and especially be suggesting the finest observable improvement method, depending on color and pattern of rear lighting system of truck for midnight highway traffic. METHODS : Rear lightning system as an improving way for forward commercial vehicles lighting the securing sight from human factors and the surrounding environment in midnight driving. For this one, basic materials were collected from the data analysis about many types of problems, and filed investigation for establishing Driving Simulator. also taking statistic test to human volunteers after finding recognizable distance of them. RESULTS : As a result, color with the highest visuality is amber followed by green-red-blue as in order for all road types. Especially almost no difference is found between red and green, also when the light is turn off, recognizable distances is wide difference compared to turn on the light. One more thing about study per pattern, upper and entire lighting have similar recognizable distances, but under lighting shows short distance with difficulty securing sight from medians. And straight section shows similar recognizable distances. By finding visuality improvement method depending on color and pattern of supplement taillight, it is expected to suggest quantitative judgement standard for introducing regulation and improvement of supplement taillight. CONCLUSIONS : Night time vehicle conspicuity to the rear is provided by rear position lamps. this study is showed that the color of light ramp is not important to be safe driving, most important is to turn on the light, recognizable distances is big different compared to turn off the rear light, so when the drivng dark in highway, have to turn on the light for reducing risk.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.252-252
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• 2010

적외선 센서는 빛의 유무에 관계없이 주 야간 전방의 물체에서 발산하는 미약한 적외선(열선)을 감지하여 영상으로 재현하는 열상시스템은 자동차 야간 운전자 보조용 나이트 비젼, 핵심 시설의 감시 관리, 군수 등의 분야에 적용되어지고 있는 최첨단, 고부가가치를 지니고 있는 기술이다. 양자형은 센서 특성은 좋으나 냉각기(작동온도: $-196^{\circ}C$) 및 고진공 패키지인 dewar를 사용하는 반면에, 열형은 대부분 상온에서 동작되는 온도안정화를 위한 전자냉각모듈만을 구비하면 되므로 저가형으로 제작이 가능한 비냉각형 적외선 센서이다. 본 연구에서는 적외선 센서용 진공패키지 조립공정 및 패키지된 센서의 측정기술을 개발하였다. 금속 메탈패키지를 제작하였으며, 금속 진공패키지는 소자냉각용 TE Cooler와 장수명 진공유지를 위한 getter, 그리고 센서칩, 온도센서를. 장착하여 칩을 조립하였다. Cap ass'y와 base envelop의 솔더링 공정을 수행하였으며, 진공패키지의 진공유지를 위해 TMP를 이용하여 진공을 유지하고, 약 5일동안 패키지 bake-out을 수행하였다. 진공압력은 $10^{-7}\;torr$ 이하를 유지하였으며, getter를 활성화시키고, pinch-off 공정으로 조립 ass'y를 완성하였다. 진공 패키지의 기밀성은 He leak tester를 이용하여 측정하였으며, ${\sim}10^{-9}\;std.cm^3/sec$로 기밀성을 유지하였다. TE cooler를 작동한 온도안정성은 0.05 K 이하였다. 볼로미터 센서의 반응도는 $10^2\;V/W$ 이상을 나타내었으며, 탐지도는 $2{\times}10^8cm-Hz^{1/2}/W$를 나타내었다. 본 연구를 통하여 얻어진 결과는 향후 2차원 열영상용 어레이 검출기 및 웨이퍼수준의 패키징 공정에 유용하게 응용될 것으로 판단된다.

• Journal of Auto-vehicle Safety Association
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• v.11 no.2
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• pp.6-10
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• 2019

This paper describes effectiveness of accident reduction on vehicles equipped with AEB using accident data occurring in Korea. During the statistical period, we used the number of vehicles which are covered by auto insurance and the number of accidents. To maximize the reduction effect of accidents caused by the driver's carelessness, the analysis was limited to Physical Damage Coverage that covers the cost of repairing or replacing the damaged vehicle caused by the driver's fault. Due to Personal Information Protection Law, it was not capable of comparing the same vehicle using Vehicle Identification Number in this study. Instead of that, we used it as a similar vehicle, so there are limits to the comparison and analysis results. As a result of this study, we have found that the effect of reducing accidents was different depending on the vehicle class, but it was generally concluded that the number of accidents decreased when the vehicle was equipped with an AEB system. Domestic research on the AEB effect of reducing accidents is not active yet. Therefore, it is absolutely essential to analyze the effects according to various conditions such as driver's age, occupation and gender as well as expanding the study models in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.632-637
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• 2019

Recent researches on autonomous driving of vehicles are becoming very active, and it is a trend to assist safe driving and improve driver's convenience. Autonomous vehicles are required to combine artificial intelligence, image recognition capability, and Internet communication between objects. Because mobile telecommunication networks have limitations in their processing, they can be easily implemented and scale using an easily expandable Wi-Fi network. We propose a wireless design method to construct such a vehicle control network. We propose the arrangement of AP and the software configuration method to minimize loss of data transmission / reception of mobile terminal. Through the design of the proposed network system, the communication performance of the moving vehicle can be dramatically increased. We also verify the packet structure of GPS, video, voice, and data communication that can be used for the vehicle through experiments on the movement of various terminal devices. This wireless design technology can be extended to various general purpose wireless networks such as 2.4GHz, 5GHz and 10GHz Wi-Fi. It is also possible to link wireless intelligent road network with autonomous driving.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.3
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• pp.47-58
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• 2021

Recently, personal mobility (PM)-related complaints and PM accidents have increased as the number of users soars due to growth in the domestic PM market and the emergence of a number of electric scooter-sharing services. As a result, the need for PM education and practice spaces is emerging as a way to reduce accidents caused by poor PM manipulation and operation. In this study, we analyze the relevant conflict factors in order to come up with a systematic operation and activation plan for PM, and as an alternative, we review and propose how to operate a PM playground and test zone. It is expected that basic data collection and analysis of rudimentary driver behavior through PM playground operations will improve users' operational safety, and various conflicts of interest between users and non-users will be resolved by installing facilities to secure their safety.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.849-856
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• 2020

Recently, as the number of high-height vehicles such as double-decker buses has increased, collision accidents have occurred in bridges and tunnels due to the deviation from the designated routes and driver's carelessness. In the case of the existing front collision warning system, it is limited to vehicles and pedestrians, so it is difficult to use it as a pass height warning system for the high height vehicles. In this paper, we propose a system that generates a warning by determining the correlation and time series characteristics of data for each segment using multiple lidar sensors and then determining the possibility of collision in the upper part of the vehicle. Also, the proposed system confirmed the proper operation through a real-time driving test and a system performance evaluation by the Korea Automobile Testing & Research Institute.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.31-48
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• 2024

The domestic automotive industry must consider a strategic shift from traditional automotive component manufacturing to align with future trends such as connectivity, autonomous driving, sharing, and electrification. This research conducted topic modeling on R&D projects in the future automotive sector funded by the Ministry of Trade, Industry, and Energy from 2013 to 2021. We found that topics such as sensors, communication, driver assistance technology, and battery and power technology remained consistently prominent throughout the entire period. Conversely, topics like high-strength lightweight chassis were observed only in the first period, while topics like AI, big data, and hydrogen fuel cells gained increasing importance in the second and third periods. Furthermore, this research analyzed the areas of concentrated investment for each period based on topic-specific government investment amounts and investment growth rates.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.6
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• pp.907-915
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• 2013

Tire Pressure Monitoring System (TPMS) is an auxiliary safety system for recognizing the condition of tires based on the pressure and temperature data transmitted from the sensor unit installed on a tire of the vehicle. Using TPMS, a driver can frequently check the state of tires and it aids to maintain the optimum running condition of the vehicle. Since TPMS must utilize the wireless communication technique to transmit data from a sensor unit to a signal processing unit installed in the vehicle, it suffers from interference signals caused by various external electrical or electronic devices. In order to suppress high-power interference signals, we employ beamforming techniques based on the uniform linear antenna array. As the number of the antennas is increased, the performance of the interference suppression is improved. However, there is the limit of the number of antennas, installed in the center of a vehicle, because of its size. In this paper, we compare and analyze the performance of the beamformer, when reducing the interelement spacing of antennas, to increase the number of the receiving antennas. For the performance analysis of the beamformers, we consider the switching beamformer and minimum-variance distortionless-response (MVDR) beamformer for TPMS, recently proposed.

• Therapeutic Science for Rehabilitation
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• v.5 no.2
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• pp.35-47
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• 2016

Objective: The aim of this study was to identify the driving rehabilitation for on-road driving through a systematic review. Methods: We systematically examined papers published in journals from December 2014 to January 2015, using CINAH, Embase, Pubmed, PsycINFO, and The Cochrane Library. Eventually, 15 studies were included in the analyses. Results: The evidence of 15 studies was from levels I, III, and V. The subjects included in the analyses were patients with stroke(40.0%), older driver(20.0%), traumatic brain injury(20.0%), acquired brain injury(13.3%) and spinal cord injury(6.7%). The intervention types were driving simulator training(53.3%), cognitive skills training(26.6%), off-road educational training(6.7%), adaptation of assistive device(6.7%), and behind-the-wheel training(6.7%). The effects of driving rehabilitation were different depending on the types of intervention. However, driving simulator training showed significant improvement of on-road assessments in all studies included this study. Conclusions: Driving rehabilitation for on-road driving has been used in various types. Specially, the effect of the driving simulator training has been proved by many studies. Future studies are to be required with client from a range of diagnostic groups to establish evidence-based interventions and determine their effectiveness in improving on-road driving.

• Journal of IKEEE
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• v.18 no.4
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• pp.485-494
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• 2014

Traffic Sign Recognition(TSR) is an important element in an Advanced Driver Assistance System(ADAS). However, many studies related to TSR approaches only in normal daytime environment because a sign's unique color doesn't appear in poor environment such as night time, snow, rain or fog. In this paper, we propose a new TSR algorithm based on machine learning for daytime as well as poor environment. In poor environment, traditional methods which use RGB color region doesn't show good performance. So we extracted sign characteristics using HoG extraction, and detected signs using a Support Vector Machine(SVM). The detected sign is recognized by a decision tree based on 25 reference points in a Normalized RGB system. The detection rate of the proposed system is 96.4% and the recognition rate is 94% when applied in poor environment. The testing was performed on an Intel i5 processor at 3.4 GHz using Full HD resolution images. As a result, the proposed algorithm shows that machine learning based detection and recognition methods can efficiently be used for TSR algorithm even in poor driving environment.