• Asian Journal of Atmospheric Environment
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• 제1권1호
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• pp.1-8
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• 2007

Vehicle exhaust is a dominant source of air pollutants in urban areas. Since people are easily exposed to vehicle exhaust particles while driving a car and/or traveling via public transportation, air pollution near traffic has been extensively studied in developed countries. In this paper, investigations on vehicle-related fine particulate air pollution at roadsides and on roads in Seoul, Korea were reviewed to understand air pollution near traffic. Comparison of $PM_{10}$ concentrations in Seoul showed that roadside air is more contaminated than urban air, implying that exposure levels near vehicular emissions are more critical to sensitive persons. Concentrations of ultrafine particles and BC (black carbon) at roadsides of Seoul fluctuate highly for short durations, responding to traffic situations. Diurnal variations of ultrafine particles and BC concentrations at roadsides seem to be affected by traffic volume, mixing layer height, and wind speed. Concentrations of ultrafine particles and BC decrease as distance from the road increases due to dilution during transport. On-road air pollution seems to be more severe than roadside air pollution in Seoul. Since nearby traffic air pollution has not been well understood in Seoul, further studies including various vehicular air pollutants and representative locations are needed.

• 자동차안전학회지
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• 제12권2호
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• pp.40-46
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• 2020

Modern traffic accidents are a complex occurrence. Various indicators are needed to analyze traffic accidents. Countries that have been investigating traffic accidents for a long time accumulate various data to analyze traffic accidents. The Korean In-Depth Accident Study (KIDAS) database collected damaged vehicles and severity of injury caused by Collision Deformation Classification code (CDC code), Abbreviated Injury Scale (AIS), and Injury Severity Score (ISS). As a result of the investigation, data relating to the injuries of the occupants can be easily obtained, but it was difficult to analyze human severity based on the information of the damaged vehicle. This study suggests a method to measure the speed change at the time of an accident, which is one of the most important indicators in the vehicle crash database, to help advance KIDAS research.

• Journal of Communications and Networks
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• 제15권2호
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• pp.173-178
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• 2013

It is a concern that eco-driving vehicles, because their driving behavior differs from other vehicles due to e.g. e-start, may inhibit smooth traffic flow. Therefore, it is necessary to study the cooperative eco-driving done by a vehicle group, putting "vehicle-to-vehicle communication" and "road-to-vehicle communication" into perspective. Based on these factors, this study aimed to: 1) Analyze fuel consumption rates and driving behaviors of more than one vehicle following an Eco-Driving vehicle. 2) Examine the effect of information on the fuel consumption rate of the preceding vehicles on the following vehicles. As a result, the following findings were obtained: 1) By providing information to multiple following vehicles, the fuel consumption rate of the second vehicle was not lowered, while that of the third one was. 2) It is possible that, when information on fuel consumption of a preceding vehicle is provided to the following one, an inter-vehicular distance is shortened during deceleration to contribute to smooth traffic flow. From the above results, it is suggested that, when targeting a vehicle group, sharing the information on preceding vehicles is effective.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2006년도 추계학술대회 학술발표 논문집 제16권 제2호
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• pp.203-207
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• 2006

Nowadays, Cars are continuing to grow at an alarming rate but they also cause many problems such as traffic accident, pollutions and so on. One of the most effective methods that prevent traffic accidents is the use of traffic monitoring systems, which are already widely used in many countries. The monitoring system is beginning to be used in domestic recently. An intelligent monitoring system generates photo images of cars as well as identifies cars by recognizing their plates. That is, the system automatically recognizes characters of vehicle plates. An automatic vehicle plate recognition consists of two main module: a vehicle plate locating module and a vehicle plate number identification module. We study for a vehicle plate number identification module in this paper. We use image preprocessing, feature extraction, multi-layer neural networks for recognizing characters of vehicle plates and we present a feature-comparison method for improving the performance of vehicle plate number identification module. In the experiment on identifying vehicle plate number, 300 images taken from various scenes were used. Of which, 8 images have been failed to identify vehicle plate number and the overall rate of success for our vehicle plate recognition algorithm is 98%.

• 제어로봇시스템학회논문지
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• 제5권8호
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• pp.907-913
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• 1999

For an automated transportation system like PRT(Personal Rapid Transit) system or IVHS, an efficient vehicle-merging algorithm is required for smooth operation of the network. For management of merging, collision avoidance between vehicles, ride comfort, and the effect on traffic should be considered. This paper proposes an unmanned vehicle-merging algorithm that consists of two procedures. First, a longitudinal control algorithm is designed to keep a safe headway between vehicles in a single lane. Secondly, 'vacant slot and ghost vehicle' concept is introduced and a decision algorithm is designed to determine the sequence of vehicles entering a converging section considering energy consumption, ride comfort, and total traffic flow. The sequencing algorithm is based on fuzzy rules and the membership functions are determined first by an intuitive method and then trained by a learning method using a neural network. The vehicle-merging algorithm is shown to be effective through simulations based on a PRT model.

• 한국ITS학회 논문지
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• 제14권6호
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• pp.21-36
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• 2015

최근 활발히 개발되고 있는 자율주행차량은 현대사회의 다양한 교통문제를 해결하기 위한 근본적인 대안으로 주목 받고 있으며, 그 효과를 예측하기 위한 연구 또한 지속적으로 진행되어왔다. 하지만 기존연구는 주로 가상의 도로를 대상으로 하여 현 도로교통시스템에 가져올 다양한 편익에 대한 검토는 미비한 상태이다. 이에 본 연구는 자율주행차량 테스트베드 구축 예정구간인 경부고속도로 서울-신갈 기본구간을 대상으로, 자율주행차량 도입에 따른 속도 및 밀도 등 다양한 교통류의 변화를 분석하였다. 분석 결과, 교통량이 적은 서비스수준 A, B 상황에서는 자율주행차량 혼입이 교통류에 부정적인 영향을 미치는 것으로 나타났다. 반면, 교통량이 많아지는 서비스수준 C 이상의 상황에서는 자율주행차량 도입에 따라 평균속도가 증가하고 밀도가 감소하여 교통류에 긍정적인 영향을 미치는 것으로 분석되었다. 이에 따라, 자율주행차량 도입이 교통혼잡 등 다양한 교통문제를 효과적으로 해결할 수 있을 것이라 기대된다.

• Wind and Structures
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• 제20권2호
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• pp.117-142
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• 2015

The performance of bridges under strong wind and traffic is of great importance to set the traveling speed limit or to make operational decisions for severe weather, such as controlling traffic or even closing the bridge. Meanwhile, the vehicle's safety is highly concerned when it is running on bridges or highways under strong wind. During the past two decades, researchers have made significant contributions to the simulation of the wind-vehicle-bridge system and their interactive effects. This paper aims to provide a comprehensive review of the overall performance of the bridge and traffic system under strong wind, including bridge structures and vehicles, and the associated mitigation efforts.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2005년도 춘계학술대회 학술발표 논문집 제15권 제1호
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• pp.161-165
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• 2005

최적 교통 주기를 산출하기 위해서는 하위교차로에 대기차량이 얼마나 있는지를 점검해야 한다. 왜냐하면 대기차량이 상위교차로의 길이보다 크면 출발 지연 시간 및 승용차 대기시간이 발생하기 때문이다. 승용차 대기시간을 단축시키기 위해서 본 논문에서는 퍼지 신경망을 이용한 최적 연동 녹색시간 알고리즘을 제안한다. 컴퓨터 모의실험을 통해서, 서로 다른 교차로 조건을 고려하지 않은 고정 교통신호등 보다 평균 주행속도가 향상 된 것을 입증하였다.

• 자동차안전학회지
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• 제12권4호
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• pp.70-77
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• 2020

In this study, we estimate the vehicle speed by analyzing the acoustic data recorded in a single microphone of a surveillance camera. The frequency analysis of the acoustic data corrects the Doppler effect, which is a characteristic of the moving sound source, and reflects the geometric relationship according to the location of the sound source and the microphone on the two-dimensional plane. The acoustic data is selected from the horn sound that is mainly observed in an urgent situation among various sound sources that may occur in a traffic accident, and the characteristics of the monotone source are considered. We verified the reliability of the proposed method by time domain acoustic analysis and actual vehicle evaluation. This method is effective and can be used for traffic accident analysis in the blind spot of the camera using a single microphone built into the existing surveillance camera.

• 한국ITS학회 논문지
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• 제18권6호
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• pp.110-123
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• 2019

교통 데이터는 교통계획이나 교통시스템 운영에 필요한 기초 자료이며 최근 ADAS 카메라로 측정한 선행 차량과의 거리를 이용하여 교통류를 파악하는 방법이 시도되고 있다. 본 연구는 영상기반 차량인식의 거리오차를 반영한 미시적 시뮬레이션 분석을 통해 교통류를 추정하기 위한 ADAS 차량의 활용 가능성을 살펴보았다. 차로수, 교통수요, 프로브 차량의 점유율(MPR), 시공간 검지영역 등에 따른 교통류 추정치의 표준 평균 제곱근 오차를 통해 분석을 수행하였다. 분석결과, ADAS 카메라의 최대 인식거리의 한계로 저밀도 교통류(LOS A, LOS B)의 추정치는 신뢰할 수 없는 수준이다. 다차로나 교통수요가 크고 점유율(MPR)이 높을 경우 추정치의 신뢰성이 개선될 수 있지만, 인위적으로 점유율(MPR)을 높이는 것은 현실적으로 어려움이 있다. 또한, 검지영역의 시간범위를 연장함으로써 추정치의 신뢰성을 개선할 수 있지만, 가장 크게 영향을 미치는 것은 ADAS 차량의 주행행태로서 해당 차량이 도로의 교통류와 상이한 주행행태를 보일 경우 그 추정치는 신뢰할 수 없게 된다. 결론적으로 모든 교통류를 정확히 추정하지는 못 하지만 ADAS 카메라의 성능이나 기능을 개선함으로써 ADAS 차량의 활용 가능성은 확대될 것이다.