• 제목/요약/키워드: Automotive Detection

검색결과 336건 처리시간 0.023초

국방 분야의 인간-차량 인터랙션 연구 (A Survey of Research on Human-Vehicle Interaction in Defense Area)

  • 양지현;이상헌
    • 한국CDE학회논문집
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    • 제18권3호
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    • pp.155-166
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    • 2013
  • We present recent human-vehicle interaction (HVI) research conducted in the area of defense and military application. Research topics discussed in this paper include: training simulation for overland navigation tasks; expertise effects in overland navigation performance and scan patterns; pilot's perception and confidence on an overland navigation task; effects of UAV (Unmanned Aerial Vehicle) supervisory control on F-18 formation flight performance in a simulator environment; autonomy balancing in a manned-unmanned teaming (MUT) swarm attack, enabling visual detection of IED (Improvised Explosive Device) indicators through Perceptual Learning Assessment and Training; usability test on DaViTo (Data Visualization Tool); and modeling peripheral vision for moving target search and detection. Diverse and leading HVI study in the defense domain suggests future research direction in other HVI emerging areas such as automotive industry and aviation domain.

Vehicles Auto Collision Detection & Avoidance Protocol

  • Almutairi, Mubarak;Muneer, Kashif;Ur Rehman, Aqeel
    • International Journal of Computer Science & Network Security
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    • 제22권3호
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    • pp.107-112
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    • 2022
  • The automotive industry is motivated to provide more and more amenities to its customers. The industry is taking advantage of artificial intelligence by increasing different sensors and gadgets in vehicles machoism is forward collision warning, at the same time road accidents are also increasing which is another concern to address. So there is an urgent need to provide an A.I based system to avoid such incidents which can be address by using artificial intelligence and global positioning system. Automotive/smart vehicles protection has become a major study of research for customers, government and also automotive industry engineers In this study a two layered novel hypothetical approach is proposed which include in-time vehicle/obstacle detection with auto warning mechanism for collision detection & avoidance and later in a case of an accident manifestation GPS & video camera based alerts system and interrupt generation to nearby ambulance or rescue-services units for in-time driver rescue.

자율주행 자동차의 실 도로 차선 변경을 위한 장애물 검출 및 경로 계획에 관한 연구 (A Research of Obstacle Detection and Path Planning for Lane Change of Autonomous Vehicle in Urban Environment)

  • 오재석;임경일;김정하
    • 제어로봇시스템학회논문지
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    • 제21권2호
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    • pp.115-120
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    • 2015
  • Recently, in automotive technology area, intelligent safety systems have been actively accomplished for drivers, passengers, and pedestrians. Also, many researches are focused on development of autonomous vehicles. This paper propose the application of LiDAR sensors, which takes major role in perceiving environment, terrain classification, obstacle data clustering method, and local map building for autonomous driving. Finally, based on these results, planning for lane change path that vehicle tracking possible were created and the reliability of path generation were experimented.

전동식 조향 칼럼 장치의 전자 제어장치 및 오류 검출 알고리즘 개발에 관한 연구 (A Study on the Development of an Electronic Control Unit and the Fault Detection Algorithm for a Motor Driven Steering Column)

  • 선우명호;이용국;이재인
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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    • pp.448-450
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    • 1998
  • Global competition of automotive market and affordable prices of electronic components become the major reason that automotive industries rapidly employ a large number of electric and electronic systems to improve vehicle performance and to meet various regulations such as emission, fuel efficiency, and safety. Especially, the provision of a motor-driven steering column (MDSC) for luxury vehicle is getting popular for drivers' convenience. In this study, an MDSC is developed, which provides several intelligent features such as the manual operation for tilting and telescoping the steering wheel, and the save/recall operation for three different steering wheel positions. In addition, the fault detection algorithm is developed.

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DEVELOPMENT OF OCCUPANT CLASSIFICATION AND POSITION DETECTION FOR INTELLIGENT SAFETY SYSTEM

  • Hannan, M.A.;Hussain, A.;Samad, S.A.;Mohamed, A.;Wahab, D.A.;Ariffin, A.K.
    • International Journal of Automotive Technology
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    • 제7권7호
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    • pp.827-832
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    • 2006
  • Occupant classification and position detection have been significant research areas in intelligent safety systems in the automotive field. The detection and classification of seat occupancy open up new ways to control the safety system. This paper deals with a novel algorithm development, hardware implementation and testing of a prototype intelligent safety system for occupant classification and position detection for in-vehicle environment. Borland C++ program is used to develop the novel algorithm interface between the sensor and data acquisition system. MEMS strain gauge hermatic pressure sensor containing micromachined integrated circuits is installed inside the passenger seat. The analog output of the sensor is connected with a connector to a PCI-9111 DG data acquisition card for occupancy detection, classification and position detection. The algorithm greatly improves the detection of whether an occupant is present or absent, and the classification of either adult, child or non-human object is determined from weights using the sensor. A simple computation algorithm provides the determination of the occupant's appropriate position using centroidal calculation. A real time operation is achieved with the system. The experimental results demonstrate that the performance of the implemented prototype is robust for occupant classification and position detection. This research may be applied in intelligent airbag design for efficient deployment.

시각물체 추적 시스템을 위한 멀티코어 프로세서 기반 태스크 스케줄링 방법 (A Task Scheduling Strategy in a Multi-core Processor for Visual Object Tracking Systems)

  • 이민채;장철훈;선우명호
    • 한국자동차공학회논문집
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    • 제24권2호
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    • pp.127-136
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    • 2016
  • The camera based object detection systems should satisfy the recognition performance as well as real-time constraints. Particularly, in safety-critical systems such as Autonomous Emergency Braking (AEB), the real-time constraints significantly affects the system performance. Recently, multi-core processors and system-on-chip technologies are widely used to accelerate the object detection algorithm by distributing computational loads. However, due to the advanced hardware, the complexity of system architecture is increased even though additional hardwares improve the real-time performance. The increased complexity also cause difficulty in migration of existing algorithms and development of new algorithms. In this paper, to improve real-time performance and design complexity, a task scheduling strategy is proposed for visual object tracking systems. The real-time performance of the vision algorithm is increased by applying pipelining to task scheduling in a multi-core processor. Finally, the proposed task scheduling algorithm is applied to crosswalk detection and tracking system to prove the effectiveness of the proposed strategy.

고안전 에어백의 승객 분류를 위한 체압감지 센서를 위한 알고리즘 개발 (Algorithm development of a body pressure detection sensor for the occupant classification system)

  • 윤득선;오성록;송정훈;김병수;부광석
    • 센서학회지
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    • 제18권5호
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    • pp.385-392
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    • 2009
  • This paper describes the algorithm development of a new body pressure detection sensor for occupant classification system. U.S. Government has required that advanced airbag system should be installed to every automobiles after 2006 according to FMVSS 208 regulation. Therefore, Occupant Classification System should be provided the passenger with safety in order to protect the infants or children that sit in the front passenger seat. When an occupant sits on the chair of the vehicle, deployment of the airbag depends on passenger's weigh distribution and postures. Authors have been developed a new pattern recognition of passenger and weight distribution at the same time by Force Sensing Resistor for the safety.

안전운전 관리시스템 개발 (Development of a Safe Driving Management System)

  • 조준희;이운성
    • 한국자동차공학회논문집
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    • 제15권1호
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    • pp.71-77
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    • 2007
  • Dangerous driving is a major cause of traffic accidents in Korea. It becomes more serious for commercial vehicles due to higher fatality rates. The Safe Driving Management System (SDMS), developed in this research, is a comprehensive solution that monitors and stores driving conditions of vehicles, detects dangerous driving situations, and analyzes the results in real time. The Safe Driving Management System consists of a vehicle movement information controller, a dangerous driving detection algorithm and a vehicle movement data report and analysis program. The dangerous driving detection algorithm detects and classifies dangerous driving conditions into representative cases such as sudden acceleration, sudden braking, sudden lane change, and sudden turning. Both computer simulation and vehicle test have been conducted to develop and verify the algorithm. The Safe Driving Management System has been implemented on commercial buses to verify its reliability and objectivity. It is expected that the system can contribute to prevention of traffic accidents, systemization of safe driving management and reduction of commercial vehicle operation costs.

Imaging of a Defect in Thin Plates Using the Time Reversal of Single Mode Lamb Wave: Simulation

  • Jeong, Hyun-Jo;Lee, Jung-Sik;Bae, Sung-Min;Lee, Hyun-Ki
    • 비파괴검사학회지
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    • 제30권3호
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    • pp.261-270
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    • 2010
  • This paper presents an analytical investigation for a baseline-free imaging of a defect in plate-like structures using the time-reversal of Lamb waves. We first consider the flexural wave (A0 mode) propagation in a plate containing a defect, and reception and time reversal process of the output signal at the receiver. The received output signal is then composed of two parts: a directly propagated wave and a scattered wave from the defect. The time reversal of these waves recovers the original input signal, and produces two additional side bands that contain the time-of-flight information on the defect location. One of the side band signals is then extracted as a pure defect signal. A defect localization image is then constructed from a beamforming technique based on the time-frequency analysis of the side band signal for each transducer pair in a network of sensors. The simulation results show that the proposed scheme enables the accurate, baseline-free detection of a defect, so that experimental studies are needed to verify the proposed method and to be applied to real structure.

IMAGE PROCESSING TECHNIQUES FOR LANE-RELATED INFORMATION EXTRACTION AND MULTI-VEHICLE DETECTION IN INTELLIGENT HIGHWAY VEHICLES

  • Wu, Y.J.;Lian, F.L.;Huang, C.P.;Chang, T.H.
    • International Journal of Automotive Technology
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    • 제8권4호
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    • pp.513-520
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    • 2007
  • In this paper, we propose an approach to identify the driving environment for intelligent highway vehicles by means of image processing and computer vision techniques. The proposed approach mainly consists of two consecutive computational steps. The first step is the lane marking detection, which is used to identify the location of the host vehicle and road geometry. In this step, related standard image processing techniques are adapted for lane-related information. In the second step, by using the output from the first step, a four-stage algorithm for vehicle detection is proposed to provide information on the relative position and speed between the host vehicle and each preceding vehicle. The proposed approach has been validated in several real-world scenarios. Herein, experimental results indicate low false alarm and low false dismissal and have demonstrated the robustness of the proposed detection approach.