• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.2
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• pp.43-57
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• 2021

The Forward Collision Warning, a representative technology of the Advanced Driver Assistance Systems, was selected as the target technology. The cognitive response time, deceleration, and impact were selected as the measures of effectiveness. And the amount of change with and without the Forward Collision Warning was measured. The experimental scenarios included a sudden stop event (1) of the vehicle in front of the driver and an event (2) in which the vehicle intervened in the next lane. All experiments were divided into day and night. As a result of the analysis, response time and the deceleration rate decreased when the forward collision warning system was installed. It was analyzed that the driver's risk situation could be detected quickly and the number of front-end collisions could be reduced as a result. Reflecting the driver's operating habits and diversifying the experimental scenarios will increase the installation effectiveness of ADAS and be used to estimate the effectiveness of other technologies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.147-161
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• 2021

The purpose of this study was to investigate the psychological state and driving safety of drivers driving around the truck platoon driving. Using the driving simulator, the experimental environment was constructed with the situation of changing lanes to the platoon and driving within the platoon. We tried to qualitatively and quantitatively analyze the driver's psychological state and driving safety through simulation driving experiments. As a result, in the case of the older driver group, there were many cases where they judged themselves to be driving safely, even though they were driving dangerously in the actual lane change to the platoon or driving within the platoon. In particular, this group showed that the narrower the distance between vehicles, the greater the misrecognition. The results of this study are expected to be useful in deriving the optimum interval when the interval between platooning of trucks needs to be temporarily extended.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.66-83
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• 2021

Vehicles experience changes in driving behavior due to the various facilities on the freeway. These sections may cause repetitive traffic congestion when the traffic volume increases, so safety issues may be raised. Therefore, the purpose of this study is to perform microscopic traffic analysis on these sections using drone images and to identify the causes of traffic problems. In the case of drone image, since trajectory data of individual vehicles can be obtained, empirical analysis of driving behavior is possible. The analysis section of this study was selected as the weaving section of Pangyo IC and the sag section of Seohae Bridge. First, the trajectory data was extracted through the drone image. And the microscopic traffic analysis performed on the speed, density, acceleration, and lane change through cell-unit analysis using Generalized definition method. This analysis results can be used as a basic study to identify the cause of the problem section in the freeway. Through this, we aim to improve the efficiency and convenience of traffic analysis.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.97-114
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• 2022

Unlike ground roads, the on-ramp merging section of underground roads cannot be seen by drivers of main road due to tunnels. In this study, a driving simulator was used for analysis, and virtual driving experiments were carried out to assess the driver's visibility for different design factors. The driver's driving behavior was analyzed by setting scenarios considering the length of chevron markings and the approach speed from the main road. The results of the analysis were used to determine the design factors for ensuring visibility when constructing the virtual driving environment for each scenario. These factors, including speed, lane change points, and driver's gaze ratios, were reviewed for significance using a statistical approach. As a result, in scenarios with a higher approach speed from the main road, it was discovered that there was a difference in driver's behavior between specific scenarios depending on the length of the section with chevron markings. Based on these findings, this study suggests implications and feasible solutions to improve driver safety on the on-ramp merging section of underground roads.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.132-145
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• 2022

This study was based on the black box images of traffic accidents on highways, cluster analysis and prediction model comparisons were carried out. As analysis data, vehicle driving behavior and road surface conditions that can grasp road and traffic conditions just before the accident were used as explanatory variables. Considering that traffic accident data is affected by many factors, cluster analysis reflecting data heterogeneity is used. Each cluster classified by cluster analysis was divided based on the ratio of the severity level of the accident, and then an accident prediction evaluation was performed. As a result of applying the Logit model, the accident prediction model showed excellent predictive ability when classifying groups by cluster analysis and predicting them rather than analyzing the entire data. It is judged that it is more effective to predict accidents by reflecting the characteristics of accidents by group and the severity of accidents. In addition, it was found that a collision accident during stopping such as a secondary accident and a side collision accident during lane change act as important driving behavior variables.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.1
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• pp.95-107
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• 2017

In this study, a preliminary study was undertaken for development of a tunnel incident automatic detection system based on a machine learning algorithm which is to detect a number of incidents taking place in tunnel in real time and also to be able to identify the type of incident. Two road sites where CCTVs are operating have been selected and a part of CCTV images are treated to produce sets of training data. The data sets are composed of position and time information of moving objects on CCTV screen which are extracted by initially detecting and tracking of incoming objects into CCTV screen by using a conventional image processing technique available in this study. And the data sets are matched with 6 categories of events such as lane change, stoping, etc which are also involved in the training data sets. The training data are learnt by a resilience neural network where two hidden layers are applied and 9 architectural models are set up for parametric studies, from which the architectural model, 300(first hidden layer)-150(second hidden layer) is found to be optimum in highest accuracy with respect to training data as well as testing data not used for training. From this study, it was shown that the highly variable and complex traffic and incident features could be well identified without any definition of feature regulation by using a concept of machine learning. In addition, detection capability and accuracy of the machine learning based system will be automatically enhanced as much as big data of CCTV images in tunnel becomes rich.

• Journal of Korean Society of Transportation
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• v.33 no.5
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• pp.441-448
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• 2015

This study aims to suggest a reasonable signal operation method for right-turn traffic management. It was found that the right-turn vehicle supplementary signal is currently operated without clear regulations or criteria. It was also analyzed that right-turn supplementary signals are used without consistency, there is a risk of traffic accidents due to the discordance between supplementary signals and traffic signals of forward vehicles, there is a lack of basis for prohibition of a right turn when right-turn vehicle's supplementary signal is red and the flashing red signal is used in a different sense from the law. In order to see the effect of the installed right-turn vehicle supplementary signals on traffic signal violation, a field investigation was conducted. As the result, there was a high proportion of signal violation on the approach lane with right-turn supplementary signals and this means that right-turn supplementary signals hardly influenced the reduction in proportion of signal violation during a right turn. Additionally, a survey was carried out to see if there were differences in driver's interpretation of traffic signals depending on the installation of right-turn supplementary signals. As the result of the survey, there were no differences in interpretation of traffic signals depending on the installation of right-turn supplementary signals or the types of right-turn supplementary signals. A right turn when the signal was red did not lead to serious traffic accidents, so it is thought that there should be a careful consideration of a total ban on a right turn when the signal is red, in order to prevent driver's confusion due to the change of the signal system. Unless there is a disturbance to cars and pedestrians after a temporary stop when the signal is red, there is a need to specify that vehicles must stop temporarily in the Road Traffic Act to facilitate a right turn. What this study finally suggested is to use tri-colored arrow signals for right-turn car supplementary signals to convey a signal to a driver clearly.

• Journal of the Korean GEO-environmental Society
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• v.15 no.2
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• pp.67-74
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• 2014

Recently, the number of road construction is increasing by industrial development. According to this industrial tendency, the number of traffic accidents are consistently increasing due to increasing number of vehicle on the road. This is mainly because traffic accidents are occurred by various parameter such as negligence of driver, vehicle defects, state of unstable road, natural environment etc. Lane department of vehicles from guardrail is occurring frequently. This type of accident is caused by vehicle performance improvement and shape of vehicle, weak guardrail installation and maintenance. Guardrail has the purpose on prevention such as prevention of traffic accident and prevention of deviating out of road, minimizing damage of driver and vehicle by collision as well as entry into the road through guardrail. Stability evaluation test of guardrail verifies the behavior of guardrail through the crash of truck. At this time, the crash condition has 100 km/h of velocity and $15^{\circ}$ of impact angle. In the case of ground condition, filling slope condition has relatively high bearing capacity of infinite ground towards the test. Guardrail is generally installed on road of shoulder in fill slope in korea. It is possible for stability problem to deteriorate ground bearing capacity in Guardrail in fill slope. The existed study towards stability of guardrail has been carried out in the infinite ground. However, the study on the behavior of fill slope with guardrail is not performed by vehicle collision. Therefore, In this study, the numerical analysis using LS-DYNA was executed for verification on behavior of fill slope with guardrail through vehicle collision. This numerical analysis was carried out with change of embedded depth on installed guardrail post in shoulder of fill slope by vehicle collision and 8 tonf truck crash providing at NCAN (National Crash Analysis Center). As the result, displacement and stress on fill slope are decreased in accordance with the increase of embedded depth of guardrail post. Ground bearing capacity is deteriorated at depth of 450 mm form shoulder of road on fill slope.