• Title/Summary/Keyword: 첨단 운전자 보조 시스템

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A Study of the Autonomous Vehicle Technology and its Future Trend : Focusing on Current Industry and Technology Convergence of Trend (자율주행 기술의 현황과 미래 동향 고찰 : 산업계 동향을 중심으로 기술 융합 관점의 접근)

  • Park, Seongkeun
    • Journal of the Korea Convergence Society
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    • v.9 no.1
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    • pp.253-259
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    • 2018
  • The Korea Convergence Society. Recently, as the 4th industrial revolution is rising, there are many changes in various field of industries. Among these industries, autonomous vehicles based on artificial intelligence, big data and internet of things is one of the most promising industry. Autonomous vehicle stray from classical car domain of manufacturers and suppliers, IT/Electronics suppliers and communication companies are widen their business area to autonomous vehicle technology. In this paper, we analysis the state of art of autonomous vehicle technology and development direction of industries/research institute. Finally, we discuss the social/economic effects of autonomous vehicle.

Nearby Vehicle Detection in the Adjacent Lane using In-vehicle Front View Camera (차량용 전방 카메라를 이용한 근거리 옆 차선 차량 검출)

  • Baek, Yeul-Min;Lee, Gwang-Gook;Kim, Whoi-Yul
    • Journal of Korea Multimedia Society
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    • v.15 no.8
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    • pp.996-1003
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    • 2012
  • We present a nearby vehicle detection method in the adjacent lane using in-vehicle front view camera. Nearby vehicles in adjacent lanes show various appearances according to their relative positions to the host vehicle. Therefore, most conventional methods use motion information for detecting nearby vehicles in adjacent lanes. However, these methods can only detect overtaking vehicles which have faster speed than the host vehicle. To solve this problem, we use the feature of regions where nearby vehicle can appear. Consequently, our method cannot only detect nearby overtaking vehicles but also stationary and same speed vehicles in adjacent lanes. In our experiment, we validated our method through various whether, road conditions and real-time implementation.

Age-related Deficits in Response Characteristics on Safety Warning of Intelligent Vehicle (지능형 자동차의 안전 경고음에 대한 고령운전자의 반응 특성)

  • Kim, Man-Ho;Lee, Yong-Tae;Son, Joon-Woo;Jang, Chee-Hwan
    • Journal of the Korean Society for Precision Engineering
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    • v.26 no.12
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    • pp.131-137
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    • 2009
  • Recent technological advances made a vehicle more intelligent to increase safety and comfort. An intelligent vehicle provides drivers with safety warning information through audible sounds, visual displays, and tactile devices. However, elderly drivers have been known to decrease the physical and cognitive abilities such as muscular strength, hearing, eyesight, short term memory, and spatial perception. Therefore, possible age-related deficits should be considered to design an effective warning system. This paper aims to evaluate the impact of advancing age on response performance on audible safety warnings which are widely used for alerting driving hazards. In order to understand the effect of age-related hearing loss and movement slowing, three sound characteristics (frequency, intensity, and period) and three age groups (younger, middle, and older) are considered. Data was drawn from 38 drivers who drove a simulated rural road in a driving simulator. Experimental results show that age influences driver's response performance. In conclusion, the appropriate range of a warning sound is suggested.

Development of Collision Safety Control Logic using ADAS information and Machine Learning (머신러닝/ADAS 정보 활용 충돌안전 제어로직 개발)

  • Park, Hyungwook;Song, Soo Sung;Shin, Jang Ho;Han, Kwang Chul;Choi, Se Kyung;Ha, Heonseok;Yoon, Sungroh
    • Journal of Auto-vehicle Safety Association
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    • v.14 no.3
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    • pp.60-64
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    • 2022
  • In the automotive industry, the development of automobiles to meet safety requirements is becoming increasingly complex. This is because quality evaluation agencies in each country are continually strengthening new safety standards for vehicles. Among these various requirements, collision safety must be satisfied by controlling airbags, seat belts, etc., and can be defined as post-crash safety. Apart from this safety system, the Advanced Driver Assistance Systems (ADAS) use advanced detection sensors, GPS, communication, and video equipment to detect the hazard and notify driver before the collision. However, research to improve passenger safety in case of an accident by using the sensor of active safety represented by ADAS in the existing passive safety is limited to the level that utilizes the sudden braking level of the FCA (Forward Collision-avoidance Assist) system. Therefore, this study aims to develop logic that can improve passenger protection in case of an accident by using ADAS information and driving information secured before a collision. The proposed logic was constructed based on LSTM deep learning techniques and trained using crash test data.

Development of a Vehicle Positioning Algorithm Using In-vehicle Sensors and Single Photo Resection and its Performance Evaluation (차량 내장 센서와 단영상 후방 교차법을 이용한 차량 위치 결정 알고리즘 개발 및 성능 평가)

  • Kim, Ho Jun;Lee, Im Pyeong
    • Journal of Korean Society for Geospatial Information Science
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    • v.25 no.2
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    • pp.21-29
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    • 2017
  • For the efficient and stable operation of autonomous vehicles or advanced driver assistance systems being actively studied nowadays, it is important to determine the positions of the vehicle accurately and economically. A satellite based navigation system is mainly used for positioning, but it has a limitation in signal blockage areas. To overcome this limitation, sensor fusion methods including additional sensors such as an inertial navigation system have been mainly proposed but the high sensor cost has been a problem. In this work, we develop a vehicle position estimation algorithm using in-vehicle sensors and a low-cost imaging sensor without any expensive additional sensor. We determine the vehicle positions using the velocity and yaw-rate of a car from the in-vehicle sensors and the position and attitude of the camera based on the single photo resection process. For the evaluation, we built a prototype system, acquired test data using the system, and estimated the trajectory. The proposed algorithm shows the accuracy of about 40% higher than an in-vehicle sensor only method.

UTIS Vitalization Countermeasures Using Traffic Information Use Satisfaction Rate Model (교통정보 이용 만족도 모형을 활용한 UTIS 활성화 대책)

  • Jang, Seok Yong;Jung, Hun Young;Ko, Sang Seon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.2D
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    • pp.199-207
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    • 2009
  • We tried to show the course of UTIS vitalization, promoting to introduce as part of the advanced traveler information system through analysis using traffic information gap model of service and structural equation modeling being used by drivers. The summary of the research is as follows. 1. We could find out the service matters needed to improve and what should be prior that make drivers' use increase through establishing the gap model of service. 2. We could establish the structural equation modeling through using traffic information use satisfaction rate, entire traffic information satisfaction rate as the observation variables. You can say it is the fruit of this research that it was confirmed the entire satisfaction rate of traffic information influenced extension, convenience, accuracy, economical efficiency in order. We could also arrange the base to determine the order of services for vitalization of UTIS in the future through grasping the priority of each service functions classified by factors. 3. It is confirmed that many drivers want multimedia function, driving support function and various functions for the personal convenience in situations except driving, which enable the drivers to enjoy leisures and interests rather than economical functions during driving due to the recent social and economic changes.

A Real-Time Hardware Design of CNN for Vehicle Detection (차량 검출용 CNN 분류기의 실시간 처리를 위한 하드웨어 설계)

  • Bang, Ji-Won;Jeong, Yong-Jin
    • Journal of IKEEE
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    • v.20 no.4
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    • pp.351-360
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    • 2016
  • Recently, machine learning algorithms, especially deep learning-based algorithms, have been receiving attention due to its high classification performance. Among the algorithms, Convolutional Neural Network(CNN) is known to be efficient for image processing tasks used for Advanced Driver Assistance Systems(ADAS). However, it is difficult to achieve real-time processing for CNN in vehicle embedded software environment due to the repeated operations contained in each layer of CNN. In this paper, we propose a hardware accelerator which enhances the execution time of CNN by parallelizing the repeated operations such as convolution. Xilinx ZC706 evaluation board is used to verify the performance of the proposed accelerator. For $36{\times}36$ input images, the hardware execution time of CNN is 2.812ms in 100MHz clock frequency and shows that our hardware can be executed in real-time.

Mobile Advanced Driver Assistance System using OpenCL : Pedestrian Detection (OpenCL을 이용한 모바일 ADAS : 보행자 검출)

  • Kim, Jong-Hee;Lee, Chung-Su;Kim, Hakil
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.10
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    • pp.190-196
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    • 2014
  • This paper proposes a mobile-optimized pedestrian detection method using Cascade of HOG(Histograms of Oriented Gradients) for ADAS(Advanced Driver Assistance System) on smartphones. In order to use the limited resource of mobile platforms efficiently, the method is implemented by the OpenCL(Open Computing Language) library, and its processing time is reduced in the following two aspects. Firstly, the method sets a program build option specifically and adjusts work group sizes as variety of kernels in the host code. Secondly, it utilizes local memory and a LUT(Look-Up Table) in the kernel code to accelerate the program. For performance evaluation, the developed algorithm is compared with the mobile CPU-based OpenCV(Open Computer Vision) for Android function. The experimental results show that the processing speed is 25% faster than the OpenCV hogcascade.

Real Time Traffic Light Detection Algorithm Based on Color Map and Multilayer HOG-SVM (색상지도와 멀티 레이어 HOG-SVM 기반의 실시간 신호등 검출 알고리즘)

  • Kim, Sanggi;Han, Dong Seog
    • Journal of Broadcast Engineering
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    • v.22 no.1
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    • pp.62-69
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    • 2017
  • Accurate detection of traffic lights is very important for the advanced driver assistance system (ADAS). There have been many research developments in this area. However, conventional of image processing methods are usually sensitive to varying illumination conditions. This paper proposes a traffic light detection algorithm to overcome this situation. The proposed algorithm first detects the candidates of traffic light using the proposed color map and hue-saturation-value (HSV) Traffic lights are then detected using the conventional histogram of oriented gradients (HOG) descriptor and support vector machine (SVM). Finally, the proposed Multilayer HOG descriptor is used to determine the direction information indicated by traffic lights. The proposed algorithm shows a high detection rate in real-time.

A Study on Evaluation Method of the LKAS Test in Domestic Road Environment (국내도로환경을 고려한 LKAS 시험평가 방법에 관한 연구)

  • Yoon, Pil-Hwan;Lee, Seon-Bong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.12
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    • pp.628-637
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    • 2017
  • The automobile industry has developed Advanced Driver Assistance Systems (ADASs) to prevent traffic accidents and reduce the burden for drivers. One example is the Lane Keeping Assistance System (LKAS), which was developed for automotive vehicle systems for safety and better driving. The main system of the LKAS supports the driver while maintaining the vehicle within a lane. LKAS uses a radar sensor and camera sensor to collect information about the vehicle's position in the lane and send commands to the actuator to influence the lateral movement of the vehicle if necessary. Recently, vehicles equipped with LKAS have become commercially available. Test procedures for international LKAS evaluation are being discussed and developed by international committees, such as the International Organization for Standardization and United Nations Economic Commission for Europe. In Korea, an evaluation of LKASs for car safety is being planned by the Korean New Car Assessment Program. Therefore, test procedures should be developed for LKASs that are suitable for the domestic road environment while accommodating international standards. We developed a test scenario for LKASs and propose a formula for obtaining the target relative distance. To validate the methods, a series of experiments were conducted using commercially available vehicles equipped with LKAS.