• 제목/요약/키워드: Auto-vehicle

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Encoder Type Semantic Segmentation Algorithm Using Multi-scale Learning Type for Road Surface Damage Recognition (도로 노면 파손 인식을 위한 Multi-scale 학습 방식의 암호화 형식 의미론적 분할 알고리즘)

  • Shim, Seungbo;Song, Young Eun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.2
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    • pp.89-103
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    • 2020
  • As we face an aging society, the demand for personal mobility for disabled and aged people is increasing. In fact, as of 2017, the number of electric wheelchair in the country continues to increase to 90,000. However, people with disabilities and seniors are more likely to have accidents while driving, because their judgment and coordination are inferior to normal people. One of the causes of the accident is the interference of personal vehicle steering control due to unbalanced road surface conditions. In this paper, we introduce a encoder type semantic segmentation algorithm that can recognize road conditions at high speed to prevent such accidents. To this end, more than 1,500 training data and 150 test data including road surface damage were newly secured. With the data, we proposed a deep neural network composed of encoder stages, unlike the Auto-encoding type consisting of encoder and decoder stages. Compared to the conventional method, this deep neural network has a 4.45% increase in mean accuracy, a 59.2% decrease in parameters, and an 11.9% increase in computation speed. It is expected that safe personal transportation will be come soon by utilizing such high speed algorithm.

Development of the Algorithm for Traffic Accident Auto-Detection in Signalized Intersection (신호교차로 내 실시간 교통사고 자동검지 알고리즘 개발)

  • O, Ju-Taek;Im, Jae-Geuk;Hwang, Bo-Hui
    • Journal of Korean Society of Transportation
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    • v.27 no.5
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    • pp.97-111
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    • 2009
  • Image-based traffic information collection systems have entered widespread adoption and use in many countries since these systems are not only capable of replacing existing loop-based detectors which have limitations in management and administration, but are also capable of providing and managing a wide variety of traffic related information. In addition, these systems are expanding rapidly in terms of purpose and scope of use. Currently, the utilization of image processing technology in the field of traffic accident management is limited to installing surveillance cameras on locations where traffic accidents are expected to occur and digitalizing of recorded data. Accurately recording the sequence of situations around a traffic accident in a signal intersection and then objectively and clearly analyzing how such accident occurred is more urgent and important than anything else in resolving a traffic accident. Therefore, in this research, we intend to present a technology capable of overcoming problems in which advanced existing technologies exhibited limitations in handling real-time due to large data capacity such as object separation of vehicles and tracking, which pose difficulties due to environmental diversities and changes at a signal intersection with complex traffic situations, as pointed out by many past researches while presenting and implementing an active and environmentally adaptive methodology capable of effectively reducing false detection situations which frequently occur even with the Gaussian complex model analytical method which has been considered the best among well-known environmental obstacle reduction methods. To prove that the technology developed by this research has performance advantage over existing automatic traffic accident recording systems, a test was performed by entering image data from an actually operating crossroad online in real-time. The test results were compared with the performance of other existing technologies.

A study on measurement and compensation of automobile door gap using optical triangulation algorithm (광 삼각법 측정 알고리즘을 이용한 자동차 도어 간격 측정 및 보정에 관한 연구)

  • Kang, Dong-Sung;Lee, Jeong-woo;Ko, Kang-Ho;Kim, Tae-Min;Park, Kyu-Bag;Park, Jung Rae;Kim, Ji-Hun;Choi, Doo-Sun;Lim, Dong-Wook
    • Design & Manufacturing
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    • v.14 no.1
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    • pp.8-14
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    • 2020
  • In general, auto parts production assembly line is assembled and produced by automatic mounting by an automated robot. In such a production site, quality problems such as misalignment of parts (doors, trunks, roofs, etc.) to be assembled with the vehicle body or collision between assembly robots and components are often caused. In order to solve such a problem, the quality of parts is manually inspected by using mechanical jig devices outside the automated production line. Automotive inspection technology is the most commonly used field of vision, which includes surface inspection such as mounting hole spacing and defect detection, body panel dents and bends. It is used for guiding, providing location information to the robot controller to adjust the robot's path to improve process productivity and manufacturing flexibility. The most difficult weighing and measuring technology is to calibrate the surface analysis and position and characteristics between parts by storing images of the part to be measured that enters the camera's field of view mounted on the side or top of the part. The problem of the machine vision device applied to the automobile production line is that the lighting conditions inside the factory are severely changed due to various weather changes such as morning-evening, rainy days and sunny days through the exterior window of the assembly production plant. In addition, since the material of the vehicle body parts is a steel sheet, the reflection of light is very severe, which causes a problem in that the quality of the captured image is greatly changed even with a small light change. In this study, the distance between the car body and the door part and the door are acquired by the measuring device combining the laser slit light source and the LED pattern light source. The result is transferred to the joint robot for assembling parts at the optimum position between parts, and the assembly is done at the optimal position by changing the angle and step.

Algorithm of Generating Adaptive Background Modeling for crackdown on Illegal Parking (불법 주정차 무인 자동 단속을 위한 환경 변화에 강건한 적응적 배경영상 모델링 알고리즘)

  • Joo, Sung-Il;Jun, Young-Min;Choi, Hyung-Il
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.6
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    • pp.117-125
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    • 2008
  • The Object tracking by real-time image analysis is one of the major concerns in computer vision and its application fields. The Object detection process of real-time images must be preceded before the object tracking process. To achieve the stable object detection performance in the exterior environment, adaptive background model generation methods are needed. The adaptive background model can accept the nature's phenomena changes and adapt the system to the changes such as light or shadow movements that are caused by changes of meridian altitudes of the sun. In this paper, we propose a robust background model generation method effective in an illegal parking auto-detection application area. We also provide a evaluation method that judges whether a moving vehicle stops or not. As the first step, an initial background model is generated. Then the differences between the initial model and the input image frame is used to trace the movement of object. The moving vehicle can be easily recognized from the object tracking process. After that, the model is updated by the background information except the moving object. These steps are repeated. The experiment results show that our background model is effective and adaptable in the variable exterior environment. The results also show our model can detect objects moving slowly. This paper includes the performance evaluation results of the proposed method on the real roads.

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Implementation and Verification of Lateral Navigation Algorithm for Korean Utility Helicopter (기동헬기 측면항법 알고리즘 구현 및 검증)

  • Kim, Sung-woo;Go, Eun-kyoung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.2
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    • pp.354-361
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    • 2018
  • This paper describe the Lateral Navigation algorithm design and verification that implementation on Mission Computer's OFP for Korean Utility Helicopter(KUH) instead of Auto Flight Control System(AFCS) Vehicle Management System. The LNAV function transmits Roll command into the AFCS System. The Roll command value will be calculated by control algorithms in MC. The Operational Flight Program(OFP) shall use for its calculations different measurements of the aircraft's attitude and place. Using these inputs, the OFP will translate a navigational demand(for example-to perform the selected flight plan) into Roll commands to the autopilot. By conducting integration test using SIL and ground test, flight test, it is confirmed that the introduced algorithm meets the requirements of the Mission Equipment Package(MEP) system. LNAV function is verified through the System Integration Laboratory(SIL) test, ground and flight test.

Automotive Recycling System and Recycling Business of Dismantler in Japan (일본(日本)의 자동차 리싸이클링시스템과 해체업계(解體業界) 경영동향(經營動向_)

  • Oh, Jae-Hyun;Kim, Joon-So;Moon, Suk-Min;Min, Ji-Won
    • Resources Recycling
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    • v.20 no.1
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    • pp.14-27
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    • 2011
  • In order to review the End-of Life Vehicle(ELV) recycling system and recycling business of dismantlers in Japan, scheme of the automobile recycling law, status of ELV recycling, exports of used cars, ELV marketing business of dismantler and upgrading of used parts net work were studied. On the other hand, field survey in details for dismantling works were conducted at West-Japan Auto Recycling Co.. Although the ELV recycling system has been operating smoothly without any noticeable trouble, recycling business is running under severe circumstance. Exports of used cars have been increasing day by day through worldwide 176 countries. Finally, reuse parts of ELV concerning innovation marketing was discussed.

Auto-Analysis of Traffic Flow through Semantic Modeling of Moving Objects (움직임 객체의 의미적 모델링을 통한 차량 흐름 자동 분석)

  • Choi, Chang;Cho, Mi-Young;Choi, Jun-Ho;Choi, Dong-Jin;Kim, Pan-Koo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.8 no.6
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    • pp.36-45
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    • 2009
  • Recently, there are interested in the automatic traffic flowing and accident detection using various low level information from video in the road. In this paper, the automatic traffic flowing and algorithm, and application of traffic accident detection using traffic management systems are studied. To achieve these purposes, the spatio-temporal relation models using topological and directional relations have been made, then a matching of the proposed models with the directional motion verbs proposed by Levin's verbs of inherently directed motion is applied. Finally, the synonym and antonym are inserted by using WordNet. For the similarity measuring between proposed modeling and trajectory of moving object in the video, the objects are extracted, and then compared with the trajectories of moving objects by the proposed modeling. Because of the different features with each proposed modeling, the rules that have been generated will be applied to the similarity measurement by TSR (Tangent Space Representation). Through this research, we can extend our results to the automatic accident detection of vehicle using CCTV.

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Evaluation of Adhesiveness with Current Flow Time in the Indirect Heating of an Asphalt Pad using Joule Heating (줄 히팅을 이용한 아스팔트패드 간접가열에 있어서 통전시간별 융착성 평가)

  • Bae, Ki-Man;Choi, Han-Suk;Oh, Bo-Ra-Mi;Baek, Jong-Jin;Park, Seong-Hwan;Kang, Myungchang;Lee, Jae-Jin
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.19 no.8
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    • pp.104-109
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    • 2020
  • Recently, vibration and noise have become an important issue in the auto industry. Asphalt vibration damping pads are used to reduce the noise and vibration of automobile bodies, and asphalt is used for many mass-produced parts due to its simple attachment process and low processing costs. In this study, the self-adhesion of asphalt pads using Joule heating was evaluated. To create the asphalt pad for the experiment, the asphalt pad was molded into a specific thickness by using SGACC material and rubber used in the vehicle body as a main component and a modified resin and filler. The SGACC material was 200 mm in length, 200 mm in width, and 0.7 mm in thickness. The asphalt pad was 200 mm in length, 100 mm in width, and 3 mm in thickness. The equipment was composed of a TR (Transformer) DC254kVA and a TC (Time controller) for a current of up to 20,000 A. The current for the Joule heating was set to 7.0 kA and a 3/1 cycle, for which the adhesion of the asphalt pad over the current flow time was evaluated.

BATHYMETRIC MODULATION ON WAVE SPECTRA

  • Liu, Cho-Teng;Doong, Dong-Jiing
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.344-347
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    • 2008
  • Ocean surface waves may be modified by ocean current and their observation may be severely distorted if the observer is on a moving platform with changing speed. Tidal current near a sill varies inversely with the water depth, and results spatially inhomogeneous modulation on the surface waves near the sill. For waves propagating upstream, they will encounter stronger current before reaching the sill, and therefore, they will shorten their wavelength with frequency unchanged, increase its amplitude, and it may break if the wave height is larger than 1/7 of the wavelength. These small scale (${\sim}$ 1 km changes is not suitable for satellite radar observation. Spatial distribution of wave-height spectra S(x, y) can not be acquired from wave gauges that are designed for collecting 2-D wave spectra at fixed locations, nor from satellite radar image which is more suitable for observing long swells. Optical images collected from cameras on-board a ship, over high-ground, or onboard an unmanned auto-piloting vehicle (UAV) may have pixel size that is small enough to resolve decimeter-scale short gravity waves. If diffuse sky light is the only source of lighting and it is uniform in camera-viewing directions, then the image intensity is proportional to the surface reflectance R(x, y) of diffuse light, and R is directly related to the surface slope. The slope spectrum and wave-height spectra S(x, y) may then be derived from R(x, y). The results are compared with the in situ measurement of wave spectra over Keelung Sill from a research vessel. The application of this method is for analysis and interpretation of satellite images on studies of current and wave interaction that often require fine scale information of wave-height spectra S(x, y) that changes dynamically with time and space.

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Missing Data Imputation Using Permanent Traffic Counts on National Highways (일반국토 상시 교통량자료를 이용한 교통량 결측자료 추정)

  • Ha, Jeong-A;Park, Jae-Hwa;Kim, Seong-Hyeon
    • Journal of Korean Society of Transportation
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    • v.25 no.1 s.94
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    • pp.121-132
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    • 2007
  • Up to now Permanent traffic volumes have been counted by Automatic Vehicle Classification (AVC) on National Highways. When counted data have missing items or errors, the data must be revised to stay statistically reliable This study was carried out to estimate correct data based on outoregression and seasonal AutoRegressive Integrated Moving Average (ARIMA). As a result of verification through seasonal ARIMA, the longer the missed period is, the greater the error. Autoregression results in better verification results than seasonal ARIMA. Traffic data is affected by the present state mote than past patterns. However. autoregression can be applied only to the cases where data include similar neighborhood patterns and even in this case. the data cannot be corrected when data are missing due to low qualify or errors Therefore, these data shoo)d be corrected using past patterns and seasonal ARIMA when the missing data occurs in short periods.