• 로봇학회논문지
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• 제11권3호
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• pp.172-182
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• 2016

Lane-level vehicle positioning is an important task for enhancing the accuracy of in-vehicle navigation systems and the safety of autonomous vehicles. GPS (Global Positioning System) and DGPS (Differential GPS) are generally used in navigation service systems, which however only provide an accuracy level up to 2~3 m. In this paper, we propose a 3D vision based lane-level positioning technique which can provides accurate vehicle position. The proposed method determines the current driving lane of a vehicle by tracking the 3D position of traffic signs which stand at the side of the road. Using a stereo camera, the 3D tracking paths of traffic signs are computed and their projections to the 2D road plane are used to determine the distance from the vehicle to the signs. Several experiments are performed to analyze the feasibility of the proposed method in many real roads. According to the experimental results, the proposed method can achieve 90.9% accuracy in lane-level positioning.

• 대한교통학회지
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• 제19권6호
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• pp.161-170
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• 2001

차량검출은 교통량 관측(모니터링)을 위해서 필요한 가장 기본적인 요소이다. 영상을 기반으로 한 교통정보추출 시스템은 다른 방식을 이용하는 시스템들과 비교했을 때 몇 가지 두드러진 장점을 가지고 있다. 그러나 영상기반 시스템에서는 영상에 포함된 그림자가 차량검출의 정확도를 저해하는 요소로 작용하는 데, 특히 이동 중인 차량에 의해서 발생하는 환성 그림자는 심각한 성능저하를 야기할 수 있다. 본 논문에서는 차량검출과 그림자 영향 제거를 위해서 배경 빼기와 에지 검출을 결합한 새로운 접근방법을 제안하였다. 제안한 방법은 노변의 지형지물에 의해서 발생하는 비활성 그림자가 크게 증가하는 상황에서도, 98(%)이상의 차량검출 정확도를 나타내었다. 본 논문에서 제안한 차량검출 방법을 기반으로 하여, 차량 추적, 차량 계수, 차종 분류, 그리고 속도 측정을 수행하여 각 차로의 부하를 나타내는 데 사용되는 차량 흐름과 관련된 여러 가지 교통정보를 추출하였다.

• 자동차안전학회지
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• 제15권1호
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• pp.45-54
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• 2023

In the commercialization stage of level 4 or higher autonomous driving, the need for new legal system related to drive safely has increased in order to meet the improved level of technological development. Especially human drivers should not be legally accountable for road safety in the era of autonomous vehicles and thus safety standards for operation of autonomous vehicles are significant. To address this issue, the German Road Traffic Act was revised in 2021, adding provisions corresponding to the commercialization of self-driving vehicle of level 4 and in the similar context the Japanese Road Traffic Ac was amended in 2022. This Article draws implications for legislative discussions on driving-related responsibilities of driverless autonomous vehicle to ensure driving safety in Korea through recent amendments in Germany and Japan.

• 대한환경공학회지
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• 제28권12호
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• pp.1293-1303
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• 2006

본 연구에서는 식물군락이 조성된 일부 학교 정온시설을 선택하여 도로교통소음 특성을 파악하고 식물군락 유무에 따른 소음의 효과를 분석하였다. 차량을 4가지로 분류할 때 전체 교통량에 가장 기여하는 차량은 소형차로 나타났고 전체 교통량 대비 도로소음에 가장 영향을 미치는 차량은 오토바이로 나타났다. 교통량(Q)과 자롱차 속력(V) 관계에서 자동차 속력이 증가할수록 소음도는 감소하였다. 하지만 자동차를 4가지로 분류한 후 각 자동차 속력의 분포별로 분석한 결과, 소형차의 경우 교통량은 $2016{\leq}Q{\leq}2388$ 및 속력 67 km/h에서 소음도가 감소한 결과를 제외한 모든 구간의 교통량에 따른 속력에서 소음도가 증가하였다. 또한 다른 차종(중형차, 대형차, 오토바이 등)에서는 교통량에 따른 차량속력에 의해 모든 구간에서 소음도가 증가하였다. 식물군락 유무에 따른 두 집단 차이를 쌍체 t 검정을 수행한 결과 두 집단간 차이(p<0.05)가 있었고 식물군락이 존재하지 않는 지역에서 주간과 야간의 차이를 이표본 t 검정을 수행한 결과 두 집단 간 차이(p<0.05)가 있었다. 하지만 식물군락이 존재할 경우 주간과 야간의 차이를 비교시 두 집단 차이(p>0.05)가 없었다.

• Journal of Information Processing Systems
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• 제12권2호
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• pp.183-195
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• 2016

This paper presents a complete method for vehicle detection and tracking in a fixed setting based on computer vision. Vehicle detection is performed based on Scale Invariant Feature Transform (SIFT) feature matching. With SIFT feature detection and matching, the geometrical relations between the two images is estimated. Then, the previous image is aligned with the current image so that moving vehicles can be detected by analyzing the difference image of the two aligned images. Vehicle tracking is also performed based on SIFT feature matching. For the decreasing of time consumption and maintaining higher tracking accuracy, the detected candidate vehicle in the current image is matched with the vehicle sample in the tracking sample set, which contains all of the detected vehicles in previous images. Most remarkably, the management of vehicle entries and exits is realized based on SIFT feature matching with an efficient update mechanism of the tracking sample set. This entire method is proposed for highway traffic environment where there are no non-automotive vehicles or pedestrians, as these would interfere with the results.

• 한국안전학회지
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• 제27권4호
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• pp.121-127
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• 2012

Vehicle Inspection System is to examine the condition of vehicle regularly at the national level to protect lives and properties of the people from traffic accidents due to vehicle's fault. However, the vehicle inspection method, criteria, period and effectiveness have become a controversial issue, because of examining safety management of vehicle by drivers regardless of regular vehicle inspection. Therefore, the aim of this study is to investigate vehicle inspection timeliness and risk level of inspection items through basic statistical survey and portfolio analysis. The results of the research through practical analysis are: (1) The inspection failure rates between 3 and 6 model year tend to increase. (2) The failure of inspection items for safety highly impacts on traffic accident rate in terms of accident risks. (3) According to the result of portfolio analysis, faulty items located 1st quadrant are riding device, driveline system, controlling device, steering actuator, and fuel system.

• Journal of the Optical Society of Korea
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• 제20권1호
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• pp.107-117
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• 2016

We develop a new method to globally calibrate the feature points that are derived from the binocular systems at different positions. A three-DOF (degree of freedom) global calibration system is established to move and rotate the 3D calibration board to an arbitrary position. A three-DOF global calibration model is constructed for the binocular systems at different positions. The three-DOF calibration model unifies the 3D coordinates of the feature points from different binocular systems into a unique world coordinate system that is determined by the initial position of the calibration board. Experiments are conducted on the binocular systems at the coaxial and diagonal positions. The experimental root-mean-square errors between the true and reconstructed 3D coordinates of the feature points are 0.573 mm, 0.520 mm and 0.528 mm at the coaxial positions. The experimental root-mean-square errors between the true and reconstructed 3D coordinates of the feature points are 0.495 mm, 0.556 mm and 0.627 mm at the diagonal positions. This method provides a global and accurate calibration to unity the measurement points of different binocular vision systems into the same world coordinate system.

• 대한교통학회지
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• 제14권4호
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• pp.49-76
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• 1996

Until recently, the inductive loop detecters(ILD) have been used to collect a traffic information in a part of traffic manangment and control. The ILD is able to collect a various traffic data such as a occupancy time and non-occupancy time, traffic volume, etc. The occupancy time of these is very important information for traffic control algorithms, which is required a high accuracy. This accuracy may be improved by classifying a vehicle type with ILD. To classify a vehicle type based on a Analog Digital Converted data collect form ILD, this study used a typical and modifyed statistic method and General Learning Vector Quantization unsuperviser neural network model and a hybrid model of GLVQ and statistic method, As a result, the hybrid model of GLVQ neural network model is superior to the other methods.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2956-2958
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• 2000

This paper describes the design of a real time traffic data acquisition system using loop detector and piezzo sensor. Loop detector is the cheapest method to measure the speed and piezzo is used to detect the vehicle axle information. A ISA slot based I/O board is designed for data acquisition and PC process the raw traffic data and transfer the data to the host system. Simulation kit is designed with toy car kits. simulated loop detector and piezzo sensor. The data acquisition system collects up to 10 lane highway traffic data such as vehicle count. speed. length axle count. distance between the axles. The data is processed to generate traffic count, vehicle classification, which are to be used for ITS. The system architecture and simulation data is included and the system will be tested for field operation.

• Journal of Information Processing Systems
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• 제15권5호
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• pp.1218-1230
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• 2019

This study proposes a novel video traffic flow detection method based on machine vision technology. The three-frame difference method, which is one kind of a motion evaluation method, is used to establish initial background image, and then a statistical scoring strategy is chosen to update background image in real time. Finally, the background difference method is used for detecting the moving objects. Meanwhile, a simple but effective shadow elimination method is introduced to improve the accuracy of the detection for moving objects. Furthermore, the study also proposes a vehicle matching and tracking strategy by combining characteristics, such as vehicle's location information, color information and fractal dimension information. Experimental results show that this detection method could quickly and effectively detect various traffic flow parameters, laying a solid foundation for enhancing the degree of automation for traffic management.