• Journal of Biosystems Engineering
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• v.29 no.5 s.106
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• pp.419-424
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• 2004

In this study, a series of soil bin experiment was carried out to investigate experimentally the effect of the tire inflation pressure and axle load of tire on the steering torque for the off-road condition. The experiment was performed at the three levels of off-road conditions(ground I, ground II and ground III) and on-road condition(ground IV), four levels of tire inflation pressure(120 kPa, 170 kPa, 220 kPa and 270 kPa), and four levels of axle load(1470N, 1960N, 2450N and 2940N). The results of this study are summarized as follows: 1. Steering torque at the off-road conditions were higher than that on the on-road conditions for all levels of tire inflation pressure and axle load. 2. As the axle load increased, steering torque also increased f3r all experimental ground conditions. 3. For the axle load of 1470N the biggest steering torque was measured on the ground condition I, but as the axle load increased to the value of 2940N the biggest steering torque was measured on the ground condition III. From the above results, it was found that for the low axle load, steering torque gets higher on the soft ground condition, but for the high axle load, steering torque gets higher on hard ground condition for whole range of experimental conditions. 4. As the tire inflation pressure decreased, steering torque increased on the on-road condition, but no specific trend was not found at the off-road conditions.

• Journal of the Korean Society of Safety
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• v.27 no.5
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• pp.211-218
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• 2012

Two experiment are planed to identify driver's safe driving behaviour by curve radius, road surface condition in curve section. At four-lane and two-lane road, conducted experiments are check on driver's feeling of safety that 30 subjects do not feel discomfort. And using the data from these experiments, this study compare physical speed (not slipping, fall our of the road) with safety driving speed(drivers felt a comfortable and safe speed) each curve radius and fiver road surface condition(drying, wet, rain, snow and ice). As a result, safe driving behaviour factors that are derived to curve radius of 100m units, five road surface conditions enable to represent quantitative analysis of driver's discomfort. This study will develop road design method and evaluation reflected ergonomic aspects.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.113-120
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• 2010

In case the traffic accident occurs, skid mark is very important factor to calculate the car speed. Especially, for the purpose of objective and scientific inspection, traffic accidents should be appraised and inspected by righteous material evidences, computer simulation, and studies such as automobile engineering, traveling and collision accident dynamics, road and traffic engineering. In this paper, it displays the results of studying cases with the reasons of traffic accidents by analyzing and studying automobile kinetics, real traffic accidents and the results of in scientific and objective ways. After computer simulation result that it is proved that compared with unpacked road condition and packed road condition. unpacked road condition is shorter than packed road condition.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.121-132
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• 2018

Weather is an important factor affecting roadway transportation in many aspects such as traffic flow, driver 's driving patterns, and crashes. This study focuses on the relationship between weather and road surface condition and develops a model to estimate the road surface condition using machine learning. A road surface sensor was attached to the probe vehicle to collect road surface condition classified into three categories as 'dry', 'moist' and 'wet'. Road geometry information (curvature, gradient), traffic information (link speed), weather information (rainfall, humidity, temperature, wind speed) are utilized as variables to estimate the road surface condition. A variety of machine learning algorithms examined for predicting the road surface condition, and a two - stage classification model based on 'Random forest' which has the highest accuracy was constructed. 14 days of data were used to train the model and 2 days of data were used to test the accuracy of the model. As a result, a road surface state prediction model with 81.74% accuracy was constructed. The result of this study shows the possibility of estimating the road surface condition using the existing weather and traffic information without installing new equipment or sensors.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.3
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• pp.53-64
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• 2013

The car-following model is one of core models in Advanced Vehicle & Highway Systems (AVHS). The car-following model has been developed in aspects such as human factor and reduction error rates. However, the consideration of safety depending on weather condition has not been completed yet. In this paper, therefore, changes of driving condition for car-following due to different road condition were dealt with, and optimal safety distance corresponding to road condition such as dry, wet and snowy were computed. The GMIT(GM Model with Instantaneous T) model was picked over for simulation of adaptive cruise control applied the suggested optimal safety distance. As the results, the 1.7 times longer safety distance was required for wet road condition than dry road condition, and the 5.6 times longer safety distance was required for snowy road condition.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.4D
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• pp.291-303
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• 2012

In order to lead safe driving, it is better to provide dynamic and detailed information on how the driver using the relevant road should behave as concerning movements of individual car rather than providing monotone and static information of reducing of speed to unspecified drivers. Assuming road and communication of highway where real-time collection and transfer of information on vehicles and road traffic status is possible, the purpose of this study was to provide real-time safe distance by considering road traffic condition such as road condition and driving condition, travel speed and distance between preceding/following vehicles. We intended to provide basic information about dangerous situation by defining different values of condition based column ($C_{condition}$) in accordance with the road surface condition, based on which Real-time Safety Distance Index(RSDI) is to be calculated comprehensively reflecting speed of preceding and following vehicles, distance between vehicles, vertical alignment and road surface condition on the scope of expression column ($C_n$). We intended to enable the driver to secure safety by providing the calculated Real-time Safety Distance Index (RSDI) so that the driver can intuitively sense and sufficiently cope with a dangerous situation where collision of vehicles may occur. The calculated RSDI value is comprised of 30 unit columns and will be provided to the driver being divided into risk evaluation grades of 3 predetermined steps, 'warning', 'dangerous' and 'normal'.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1398-1400
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• 1996

In this paper, a method of the decision of the road direction for ALV(Autonomous Land Vehicle) road following by region-based segmentation is presented. The decision of the road direction requires extracting road regions from images in real-time to guide the navigation of ALV on the roadway. Two thresholds to discriminate between road and non-road region in the image are easily decided, using knowledge of problem region and polygonal approximation that searches multiple peaks and valleys in histogram of a road image. The most likely road region of the binary image is selected from original image by these steps. The location of a vanishing point to indicate the direction of the road can be obtained applying it to X-Y profile of the binary road region again. It can successfully steer a ALV along a road reliably, even in the presence of fluctuation of illumination condition, bad road surface condition such as hidden boundaries, shadows, road patches, dirt and water stains, and unusual road condition. Pyramid structure also saves time in processing road images and a real-time image processing for achieving navigation of ALV is implemented. The efficacy of this approach is demonstrated using several real-world road images.

• Journal of the Korean Society of Safety
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• v.28 no.5
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• pp.71-77
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• 2013

This Study aims at investigating actual condition on attending school road of children and analyzing empirically the characteristics of cognition and the influence of safety on school road. This study findings are as follows : 1) Walking alone to go to school is the highest rates among Commuting Mode, and Commuting distance to school is nearly doubles than range of school zone(300 m). 2) Among characteristics of urban spatial structure affecting on influence classify safety of school road, 'Commuting Distance' has been drawn to most influential variable. Especially, there are 4 types classified by commuting distance and it became obvious that the longer the distance, the lower the safety score(under 127 m=76.9 points, Over 451 m=58.3 points). 3) As a result of investigating the influence of Safety on attending school road, Vehicle commuting speed urder 127 m as internal of school zone, and Walking and crossing convenience over 451 m as external of school zone have a lot of influence on safety cognition on school road. Therefore Safety on school road should be considering the commuting distance to school among surrounding characteristics, needed for improvement plan and program based on real safety cognition of children.

• Journal of the Korean Applied Science and Technology
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• v.37 no.6
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• pp.1507-1516
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• 2020

This study analyzed the scenario for road freezing section by applying the road freezing evaluation algorithm. To apply road freezing algorithm, the influencing factors on road freezing were reviewed. Observation data from four points, Mokgam IC, Jeongneung tunnel, Seongsan bridge, and Yeomchang bridge were used for analysis. All observatories are installed on the expressway, and they are classified for the analysis of road freezing characteristics. When the difference between the road surface temperature and dew-point temperature of the road freezing evaluation algorithm was 3℃ or less, the section where road freezing occurred was checked. In addition, road freezing evaluation was derived through the change of the road surface condition and water film thickness of the freezing section.

• Journal of Korean Society of Rural Planning
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• v.16 no.1
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• pp.21-33
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• 2010

Although there have been carrying out various rural development projects related with village road improvement, most of village roads in Korea are under much poor condition. However, until now, their actual conditions have not been surveyed at all. So, this study aimed at analysing the actual conditions and characteristics of rural village roads in the general terms to provide the basic information for the proper improvement policy-making. Case study villages were chosen in flat/mountainous/seashore/suburban areas, which be then classified as improved and not. In terms of road length per household, mountainous villages are highly dispersed and suburban ones moderately dispersed, while flat ones aggregated. Road widths in seashore/suburban/structure improved villages are narrower than flat/mountainous ones. Because about a quarter of road sites are registered as non-road, more positive scheme for transferring non-road sites into road ones.