• The Journal of the Korea Contents Association
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• v.13 no.9
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• pp.400-409
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• 2013

In this paper, considering the characteristics of the driver at roundabouts by investigating the critical gap acceptance on various traffic conditions, multi-legged roundabouts were evaluated. The gap acceptance and rejection of 4-legged, 5-legged, 6-legged, and 7-legged roundabout were surveyed on real fields, and the critical gap acceptance was estimated using Raff's methods. Derived the critical gap acceptance was processed calibration and validation for micro-simulation, and then multi-legged roundabouts under variable conditions such as variations of traffic volume, turning ratio, and size of inscribed circle diameter were evaluated to verify operating conditions of roundabouts. As the results, according to the operating traffic volume and turning ratio, the inscribed circle diameters were proposed at each level of service. These inscribed circle diameters were able to reflect the guideline of geometric design for multi-legged roundabouts.

• Journal of Korean Society of Transportation
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• v.28 no.6
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• pp.147-158
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• 2010

Studies on the distribution of traffic demands have been proceeding by providing traffic information for reducing greenhouse gases and reinforcing the road's competitiveness in the transport section, however, since it is preferentially required the extensive studies on the driver's behavior changing routes and its influence factors, this study has been developed a discriminant model for changing routes considering driving conditions including traffic conditions of roads and driver's preferences for information media. It is divided into three groups depending on driving conditions in group classification with the CART analysis, which is statistically meaningful. And, elements of the driving conditions and the preferred media affecting the change of paths are classified into statistical meaningful groups through the CHAID analysis, and the major factors affecting the change of paths are examined. Finally, the extent that driving conditions and preferred media affect a route change is examined through a discriminant analysis, and it is developed a discriminant model equation to predict a route change. As a result of building the discriminant model equation, it is shown that driving conditions affect a route change much more, the entire discriminant hit ratio is derived as 64.2%, and this discriminant equation shows high discriminant ability more than a certain degree.

• Journal of Auto-vehicle Safety Association
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• v.7 no.3
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• pp.30-34
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• 2015

This study examined the Korean drivers' acceptance of SAS(Speed Assistance systems) and traffic sign conditions in Korea roads for SLIF(Speed Limit Information Function) that is a part of SAS. Exceeding the speed limit is a factor in the severity of many road accidents and SAS would help the driver to observe a speed limit by warning and/or effectively limiting the speed of the vehicle. SAS are in the initial phase in Korea, Korean drivers could not be familiar with automatical speed limiting during driving, SAS interface design would be considered to be more readily acceptable to the public. And advanced SAS have been introduced onto the market which are able to inform the driver of the current speed limit based on camera and/or digital maps based SLIF. These systems are based on external data using sensors, so environmental conditions are an important factor which could cause malfunction of SLIF functions.

• Journal of Korean Society of Transportation
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• v.30 no.4
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• pp.95-106
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• 2012

Driver's capability of identifying the change in freeway alignments and environments is one of important factors associated with traffic safety on freeways. In particular, driver's visibility and recognition capability are highly dependent on the altitude of the sun by sunset, sunrise, and nighttime. The purpose of this study is to identify the characteristics of geometric conditions affecting crash occurrences at sunset, sunrise, and nighttime. Poisson and negative binomial regressions were adopted to predict freeway crash frequency in this study. Freeway crash data during 2007~2010 were used for developing the crash frequency models. A set of variables representing the characteristics of geometric conditions were identified as significant ones affecting crash occurrences. The results of this study would be useful in deriving effective countermeasures for preventing traffic crashes that mainly occur at sunset, sunrise, and nighttime on freeways.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.29-39
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• 2020

Some drivers cannot meet the standards for a full driver's license and many countries allow them to drive a vehicle as long as they can satisfy certain conditions. Korea has mainly issued conditional driver's licenses to the disabled only after supplementary devices are attached either in the vehicle or in their bodies. However, it is becoming important to issue a conditional driver's license to other types of drivers, including the elderly as the population ages in the country. This study aims at improving the current practice of issuing conditional driver's licenses by benchmarking various types of conditional licenses in other countries. In particular, various conditions such as time, space, driving speed, road type, vehicle type, and specific individual conditions are compared. Issuing a conditional driver's license to various types of drivers should be beneficial, not only to elderly drivers but also to drivers who cannot live without a vehicle.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.195-205
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• 2001

The objective of the paper is to analyze the traffic characteristics for freeway merging area. Freeway merging area is different from basic section due to ramp vehicles. Therefore, to understand the traffic characteristics of (leeway merging area, this study focused on two factors including critical time headway required in merging maneuver and maximum possible merging volume. In this paper, new model that adopts critical time headway instead of critical time gap in calculating the maximum possible merging volume based on probability function was developed In previous studies, for calculating the maximum possible merging volume, it was considered that merging vehicles could merge freely if a given time gap was greater than the critical time gap. Also, the critical time gap was used as the same value in all traffic flow conditions. But, a time gap required in merging maneuver could be changed, even to the same driver, because difference of relative speed varies in different traffic flow conditions. So, in some cases, the critical time gap could be insufficient value in merging maneuver. Therefore, in this study. a calculating procedure for critical time headway in all traffic flow conditions was presented. Also, the maximum possible merging volume and capacity for freeway merging area were calculated by using the previously found critical time headway.

• Journal of the Korean Society of Safety
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• v.31 no.3
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• pp.143-155
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• 2016

Recently, a massive loss of life and property is occurring in Korea due to traffic accidents, with the rapid increase in cars. For improvement of traffic safety, the Korea Transportation Safety Authority intensively analyzes accident data in local governments with low traffic safety index, performs a field investigation to extract problems and offers local governments improvements for problems, by conducting the 'Special Survey of Actual Conditions of Traffic Safety' each year, starting 2008. But local governments cannot strongly push forward the improvement projects due to the limited budget and the uncertainty of the improvement plan effects. Therefore, this study suggested a model which applied the Utility concept to the AHP theory, in order to efficiently decide a priority of the improvement plans in accident black spots in consideration of the limited budget of local governments. The number of accidents in each spot for improvement and accident severity, traffic volume, pedestrian volume, the improvement project cost and the accident reduction effect were chosen as evaluation factors for deciding a priority, and data about the improvement plan costs and the accident reduction effects, traffic accidents and traffic volume in the spots to undergo the special research on the real condition of traffic accident in the past were collected from the existing studies. Then, regression analysis was carried out and the Utility Curve of each evaluation factor was computed. Based on the AHP analysis findings, this study devised a priority decision method which calculated the weight and the utility function of each evaluation factor and compared the total utility values. The AHP analysis findings showed that among the evaluation factors, accident severity had the biggest importance and it was followed by the improvement plan cost, the number of accidents, the improvement effect, traffic volume and pedestrian volume. The calculated utility function shows a rise in utility, as the variables of the 5 evaluation factors; the number of accidents, accident severity, the improvement plan effect, traffic volume and pedestrian volume increase and a fall in utility, as the variables of the improvement plan cost increase, since the improvement plan cost is included in the budget spent by a local government.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.869-875
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• 2019

The service level of the roundabout is estimated through an analytic model using the geometrical characteristics and parameter values obtained from the observations. Although a lot of researches have been conducted on the rotational intersection through an analytical model, the case of variable combinations is enormous, suggesting the range and service level of appropriate traffic volume according to the case study or limited characteristics through simulation. Therefore, in this study, the roundabout analysis model was constructed by using Visual Basic Application to make variable adjustment more easily. The constructed model analyzes traffic conditions according to various situations and analyzes the characteristics of roundabouts. As the result of analysis, the more the ratio of left turn and U-turn, the more the traffic distribution of each approached road was biased to one side, the limit traffic volume of the roundabout decreased and congestion appeared quickly. In particular, the more uneven the distribution of traffic was, the less the Saturation traffic volume was affected by the turnover rate.

• Journal of Broadcast Engineering
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• v.22 no.1
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• pp.62-69
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• 2017

Accurate detection of traffic lights is very important for the advanced driver assistance system (ADAS). There have been many research developments in this area. However, conventional of image processing methods are usually sensitive to varying illumination conditions. This paper proposes a traffic light detection algorithm to overcome this situation. The proposed algorithm first detects the candidates of traffic light using the proposed color map and hue-saturation-value (HSV) Traffic lights are then detected using the conventional histogram of oriented gradients (HOG) descriptor and support vector machine (SVM). Finally, the proposed Multilayer HOG descriptor is used to determine the direction information indicated by traffic lights. The proposed algorithm shows a high detection rate in real-time.

• Journal of Convergence for Information Technology
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• v.10 no.8
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• pp.40-46
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• 2020

As interest in traffic safety increases, research on autonomous driving, which reduces the incidence of traffic accidents, is increased. Object recognition and detection are essential for autonomous driving. Therefore, research on object recognition and detection through traffic image big data is being actively conducted to determine the road conditions. However, because most existing studies use only daytime data, it is difficult to recognize objects on night roads. Particularly, in the case of a light source object, it is difficult to use the features of the daytime as it is due to light smudging and whitening. Therefore, this study proposes Yolo based light source object detection for traffic image big data processing. The proposed method performs image processing by applying color model transitions to night traffic image. The object group is determined by extracting the characteristics of the object through image processing. It is possible to increase the recognition rate of light source object detection on a night road through a deep learning model using candidate group data.