• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.6
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• pp.34-42
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• 2014

This study is a fundamental research to determine the emergency evacuation roads considering road network function and connectivity. First of all, the functional aspects of the road networks are analyzed in the target area, Sejong city, by using degree centrality(DC) and closeness centrality(CC) from GIS based database. Secondly, how network connectivity makes a change in user's travel pattern and travel time and how it affects the whole network are analyzed using TransCAD simulation program. Finally, after performing cluster analysis of index, first and second emergency evacuation roads are determined by judging the characteristics of clusters. The results of this research will be helpful for making a decision to diminish secondary damages when confronting unexpected disasters.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.2
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• pp.100-109
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• 2008

Traffic accidents at night occur more than any other time because of improper road light facility and delineators. Therefore, cost-effective criteria of installing delineators are needed instead of expensive road light facility, especially, on rural road including light volume of traffic. This paper presents the criteria of installing 'Chevron Alignment Sign' considering driver's visual behavior characteristics and 'Raised Pavement Marker' considering critical encroachment angie of both straight section and curve one in order to reduce both the number of accidents on curve sections and the number of road encroachment accidents, respectively. The characteristics of visual behaviors can be expressed by visual angle involving curve radius and intersection angle. The estimated installing angles are $1^{\circ}{\sim}2.5^{\circ}$ by radii, which is based on changes in sensitivity across visual field by exogenous attention. Also, the raised pavement marker is installed every 2m, 3m, and 4m considering critical encroachment angles by radii.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.3
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• pp.1-14
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• 2017

Recently, the automobile industry is rapidly changing due to autonomous vehicles based on advanced ICT technology. As a result, studies related to autonomous vehicles have also been actively conducted. However, most studies are focusing on the autonomous driving technology so that the prediction of changes in road traffic safety and associated legal system due to the introduction of autonomous vehicles are lacking. The purpose of this study is to suggest improvement methods and priorities of road traffic safety projects according to the introduction of autonomous vehicles. As a result of the AHP analysis using the results of the questionnaire surveyed for autonomous driving car experts, it was analyzed that revision of the traffic safety inspection law and development of education system for autonomous driving motor drivers and operators should be given top priority.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.6
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• pp.133-144
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• 2012

This study focused on estimating influential factors of traffic accidents and analyzing traffic accident severity of elderly and non elderly using traffic accident data. In order to reclassify elderly and non elderly traffic accident by a statistical method from entire traffic accident data, multiple discriminant analysis was applied. Also ordered logit model was applied for analyzing traffic accident severities using traffic accident severities as an independent variable and transportation facilities, road conditions and human characteristics as dependent variables. As results of the comparison between elderly and non elderly traffic accident, the traffic accident severity was affected by the age, types of traffic accidents, human characteristics and road conditions as well. Also, transportation facilities and road conditions affected to more elderly traffic accident than non elderly. Therefore, traffic accident severity would be decreased with the improvement of transportation facilities and road conditions for the elderly.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.130-145
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• 2021

As part of the Smart Seoul policy, the importance of using big urban data is being highlighted. Furthermore interest in the impact of transportation-related urban environmental factors such as PM10 and noise on citizen's quality of life is steadily increasing. This study established the integrated DB by matching IoT big data with transportation data, including traffic volume and speed in the microscopic Spatio-temporal scope. This data analyzed the impact of a spatial unit in the road-effect zone on environmental risk level. In addition, spatial units with similar characteristics of road traffic and environmental factors were clustered. The results of this study can provide the basis for systematically establishing environmental risk management of urban spatial units such as PM10 or PM2.5 hot-spot and noise hot-spot.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.4
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• pp.71-79
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• 2019

By using convolutional neural networks (CNNs) based on semantic segmentation, road surface damage detection has being studied. In order to generate the CNN model, it is essential to collect the input and the corresponding labeled images. Unfortunately, such collecting pairs of the dataset requires a great deal of time and costs. In this paper, we proposed a road surface damage detection technique based on semi-supervised learning using pseudo labels to mitigate such problem. The model is updated by properly mixing labeled and unlabeled datasets, and compares the performance against existing model using only labeled dataset. As a subjective result, it was confirmed that the recall was slightly degraded, but the precision was considerably improved. In addition, the $F_1-score$ was also evaluated as a high value.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.50-61
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• 2022

Snow, rain, fog, and particulate matter interfere with the vehicle driver's vision, which causes a non-secure safety distance and an increase in speed deviation, causing repetitive large-scale traffic accidents. This study developed a road environment sensor capable of measuring 11 types of fog, snow, rain, temperature, humidity, direction of wind, speed of wind, Insolation, atmospheric pressure, fine particles, rainfall, etc. and compared the visibility measured by the infrared signal value of the development sensor. The relationship between the existing fog visibility sensor and the development sensor measurement was derived from data measured at a visibility of 500m or less that directly affects road safety.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.4
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• pp.97-113
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• 2023

Swift and appropriate responses in emergency situations like objects falling on the road can bring convenience to road users and effectively reduces secondary traffic accidents. In Korea, current intelligent transportation system (ITS)-based detection systems for emergency road situations mainly rely on loop detectors and CCTV cameras, which only capture road data within detection range of the equipment. Therefore, a new detection method is needed to identify emergency situations in spatially shaded areas that existing ITS detection systems cannot reach. In this study, we propose a ResNet-based algorithm that detects and classifies emergency situations from vehicle camera footage. We collected front-view driving videos recorded on Korean highways, labeling each video by defining the type of emergency, and training the proposed algorithm with the data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.62-72
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• 2023

Recently, the importance of monitoring and management measures for bicycle road related facilities has been increasing. However, research on the monitoring and evaluation of users' safety and convenience in walking spaces including bicycle path is insufficient. In this study, we would like to construct health monitoring data for cylists-pedestrians mixed road using a mobile mapping system, and propose a plan to calculate the level of service of the mixed roads from the perspective of pedestrians and cyclists using artificial intelligence based object detection techniques. The monitoring and level of service calculation method of cylists-pedestrians mixed roads proposed in this study is expected to be used as basic information for planning and management such as maintenance and reconstruction of walking spaces in preparation for the increase of electric bicycles and personal mobility in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.37-48
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• 2020

Eight colors prescribed by the Enforcement Rules of the Road Traffic Act and the group standard were tested to secure the minimum recursive reflectance performance standards when drying and wetting. The results were calculated to be 260.8 (mcd/㎡·lux) when drying white and 154.6 (mcd/㎡·lux) when wet. Yellow was 67% compared to the white reflective performance when drying. Wet poetry was 79 % and 59 %, respectively. In the case of blue, it was 64% in the case of white versus 72% in the case of white. Wet poetry was 63 % and 72 %, respectively. The range of changes in reflective performance during wetting was higher than when drying, and the absence of glass grains was similar to the previous results. The new colors also have a standard value of more than 50% compared to the white color in red, orange, pink, light green, and green. Based on this, it was estimated that the minimum reflective performance criteria according to the color of the road markings would form the basis for the enforcement rules of the Road Traffic Act.