• Title/Summary/Keyword: advanced driver assistance system (ADAS)

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Study for Evaluation Standard of Longitudinal Active Safety System (종방향 능동안전장치의 평가기준 연구)

  • Jang, Hyunik;Yong, Boojoong;Cho, Seongwoo;Choi, Inseong;Min, Kyongchan;Kim, Gyuhyun
    • Journal of Auto-vehicle Safety Association
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    • v.4 no.1
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    • pp.12-17
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    • 2012
  • ADAS(Advanced Driver Assistance System) which is developed for alleviating driver's load has become improved with extending it's role. Previously, ADAS offered simple function just to make driver's convenience. However, nowadays ADAS also acts as Active Safety system which is made to release and/or prevent accidents. Longitudinal control system, as one of major parts of Active Safety System, is assessed as doing direct effect on avoiding accidents. Therefore, many countries such as Europe and America has pushed longitudinal control system as a government-wide project. In this paper, it covers the result of evaluation system and vehicle evaluation for development study in FCW, ACC and AEB.

Implementation of Linear Detection Algorithm using Raspberry Pi and OpenCV (라즈베리파이와 OpenCV를 활용한 선형 검출 알고리즘 구현)

  • Lee, Sung-jin;Choi, Jun-hyeong;Choi, Byeong-yoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.637-639
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    • 2021
  • As autonomous driving research is actively progressing, lane detection is an essential technology in ADAS (Advanced Driver Assistance System) to locate a vehicle and maintain a route. Lane detection is detected using an image processing algorithm such as Hough transform and RANSAC (Random Sample Consensus). This paper implements a linear shape detection algorithm using OpenCV on Raspberry Pi 3 B+. Thresholds were set through OpenCV Gaussian blur structure and Canny edge detection, and lane recognition was successful through linear detection algorithm.

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Implementation of Preceding Vehicle Break-Lamp Detection System using Selective Attention Model and YOLO (선택적 주의집중 모델과 YOLO를 이용한 선행 차량 정지등 검출 시스템 구현)

  • Lee, Woo-Beom
    • Journal of the Institute of Convergence Signal Processing
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    • v.22 no.2
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    • pp.85-90
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    • 2021
  • A ADAS(Advanced Driver Assistance System) for the safe driving is an important area in autonumous car. Specially, a ADAS software using an image sensors attached in previous car is low in building cost, and utilizes for various purpose. A algorithm for detecting the break-lamp from the tail-lamp of preceding vehicle is proposed in this paper. This method can perceive the driving condition of preceding vehicle. Proposed method uses the YOLO techinicque that has a excellent performance in object tracing from real scene, and extracts the intensity variable region of break-lamp from HSV image of detected vehicle ROI(Region Of Interest). After detecting the candidate region of break-lamp, each isolated region is labeled. The break-lamp region is detected finally by using the proposed selective-attention model that percieves the shape-similarity of labeled candidate region. In order to evaluate the performance of the preceding vehicle break-lamp detection system implemented in this paper, we applied our system to the various driving images. As a results, implemented system showed successful results.

Analysis for Traffic Accident of the Bus with Advanced Driver Assistance System (ADAS) (첨단안전장치 장착 버스의 사고사례 분석)

  • Park, Jongjin;Choi, Youngsoo;Park, Jeongman
    • Journal of Auto-vehicle Safety Association
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    • v.13 no.3
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    • pp.78-85
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    • 2021
  • Recently a traffic accident of heavy duty vehicles under the mandatory installation of ADAS (Advanced Driver Assistance System) is often reported in the media. Heavy duty vehicle accidents are normally occurring a high number of passenger's injury. According to report of Insurance Institute for Highway Safety, FCW (Forward Collision Warning) and AEB (Automatic Emergency Braking) were associated with a statistically significant 12% reduction in the rate of police-reportable crashes per vehicle miles traveled, and a significant 41% reduction in the rear-end crash rate of large trucks. Also many countries around the world, including Korea, are studying the effects of ADAS installation on accident reduction. Traffic accident statistics of passenger vehicle for business purpose in TMACS (Traffic safety information Management Complex System in Korea) tends to remarkably reduce the number of deaths due to the accident (2017(211), 2018(170), 2019(139)), but the number of traffic accidents (2017(8,939), 2018(9,181), 2019(10,095)) increases. In this paper, it is introduced a traffic accident case that could lead to high injury traffic accidents by being equipped with AEB in a bus. AEB reduces accidents and damage in general but malfunction of AEB could occur severe accident. Therefore, proper education is required to use AEB system, simply instead of focusing on developing and installing AEB to prevent traffic accidents. Traffic accident of AEB equipped vehicle may arise a new dispute between a driver's fault and vehicle defect. It is highly recommended to regulate an advanced event data recorder system.

Advanced Driver Assistance System for the Control of Turn Signal Indicator (방향지시등 제어를 위한 운전자 지원 시스템)

  • Kim, Dae-Soon
    • Journal of IKEEE
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    • v.22 no.1
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    • pp.143-148
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    • 2018
  • In this paper, a novel turn signal indication scheme is proposed and implemented to handle the turn signal of a vehicle automatically. By adopting accelerometer for the motion recognition of vehicle's momentum, the proposed way could control and manage turn signals according to the moving direction of a car when a driver forgot handling turn signal lever. The designed control system is plugged into the motorbike and tested to demonstrate improved driver's safety suitable for ADAS.

Night-to-Day Road Image Translation with Generative Adversarial Network for Driver Safety Enhancement (운전자 안정성 향상을 위한 Generative Adversarial Network 기반의 야간 도로 영상 변환 시스템)

  • Ahn, Namhyun;Kang, Suk-Ju
    • Journal of Broadcast Engineering
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    • v.23 no.6
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    • pp.760-767
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    • 2018
  • Advanced driver assistance system(ADAS) is a major technique in the intelligent vehicle field. The techniques for ADAS can be separated in two classes, i.e., methods that directly control the movement of vehicle and that indirectly provide convenience to driver. In this paper, we propose a novel system that gives a visual assistance to driver by translating a night road image to a day road image. We use the black box images capturing the front road view of vehicle as inputs. The black box images are cropped into three parts and simultaneously translated into day images by the proposed image translation module. Then, the translated images are recollected to original size. The experimental result shows that the proposed method generates realistic images and outperforms the conventional algorithms.

A Study on the Accident Reconstruction Simulation about AEBS of ADAS Vehicle using Prescan (Prescan을 활용한 ADAS 차량의 AEBS에 대한 사고 재현 시뮬레이션 연구)

  • Jonghyuk Kim;Jaehyeong Lee;Songhui Kim;Jihun Choi;Woojeong Jeon
    • Journal of Auto-vehicle Safety Association
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    • v.15 no.4
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    • pp.23-31
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    • 2023
  • In recent years, the technology for autonomous driving has been advancing rapidly, ADAS (Advanced Driver Assistance System) functions, which improve driver convenience and safety performance, are mostly equipped in recently released vehicles and range from level 0 to level 2 in autonomous driving technology. Among the various functions of ADAS, AEBS (Autonomous Emergency Braking System), which analyzes traffic accidents, is the most closely related to the vehicle's braking. This study developed a simulation technique for reproducing accidents related to AEBS based on real vehicle experimental data, and it was applied to the analysis of actual ADAS vehicle accidents to identify the causes of accidents.

Neighboring Vehicle Maneuver Detection using IMM Algorithm for ADAS (지능형 운전보조시스템을 위한 IMM 기법을 이용한 전방차량 거동추정기법)

  • Jung, Sun-Hwi;Lee, Woon-Sung;Kang, Yeonsik
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.8
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    • pp.718-724
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    • 2013
  • In today's automotive industry, there exist several systems that help drivers reduce the possibility of accidents, such as the ADAS (Advanced Driver Assistance System). The ADAS helps drivers make correct and quick decisions during dangerous situations. This study analyzed the performance of the IMM (Interacting Multiple Model) method based on multiple Kalman filters using the data acquired from a driving simulator. An IMM algorithm is developed to identify the current discrete state of neighboring vehicles using the sensor data and the vehicle dynamics. In particular, the driving modes of the neighboring vehicles are classified by the cruising and maneuvering modes, and the transition between the states is modeled using a Markovian switching coefficient. The performance of the IMM algorithm is analyzed through realistic simulations where a target vehicle executes sudden lane change or acceleration maneuver.

A Study on Traffic Light Detection (TLD) as an Advanced Driver Assistance System (ADAS) for Elderly Drivers

  • Roslan, Zhafri Hariz;Cho, Myeon-gyun
    • International Journal of Contents
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    • v.14 no.2
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    • pp.24-29
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    • 2018
  • In this paper, we propose an efficient traffic light detection (TLD) method as an advanced driver assistance system (ADAS) for elderly drivers. Since an increase in traffic accidents is associated with the aging population and an increase in elderly drivers causes a serious social problem, the provision of ADAS for older drivers via TLD is becoming a necessary(Ed: verify word choice: necessary?) public service. Therefore, we propose an economical TLD method that can be implemented with a simple black box (built in camera) and a smartphone in the near future. The system utilizes a color pre-processing method to differentiate between the stop and go signals. A mathematical morphology algorithm is used to further enhance the traffic light detection and a circular Hough transform is utilized to detect the traffic light correctly. From the simulation results of the computer vision and image processing based on a proposed algorithm on Matlab, we found that the proposed TLD method can detect the stop and go signals from the traffic lights not only in daytime, but also at night. In the future, it will be possible to reduce the traffic accident rate by recognizing the traffic signal and informing the elderly of how to drive by voice.

Design and Implementation of Optical Flow Estimator for Moving Object Detection in Advanced Driver Assistance System (첨단운전자보조시스템용 이동객체검출을 위한 광학흐름추정기의 설계 및 구현)

  • Yoon, Kyung-Han;Jung, Yong-Chul;Cho, Jae-Chan;Jung, Yunho
    • Journal of Advanced Navigation Technology
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    • v.19 no.6
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    • pp.544-551
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    • 2015
  • In this paper, the design and implementation results of the optical flow estimator (OFE) for moving object detection (MOD) in advanced driver assistance system (ADAS). In the proposed design, Brox's algorithm with global optimization is considered, which shows the high performance in the vehicle environment. In addition, Cholesky factorization is applied to solve Euler-Lagrange equation in Brox's algorithm. Also, shift register bank is incorporated to reduce memory access rate. The proposed optical flow estimator was designed with Verilog-HDL, and FPGA board was used for the real-time verification. Implementation results show that the proposed optical flow estimator includes the logic slices of 40.4K, 155 DSP48s, and block memory of 11,290Kbits.