• Journal of Korean Society of Transportation
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• v.21 no.4
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• pp.133-144
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• 2003

The current procedure of estimating accident reduction benefit shows fixed accident rates for each level of roads without considering the various characteristics of roadway geometries, and traffics. In this study, in order to solve the problems mentioned in the above, models were developed considering the characteristics of roadway alignments and traffic characteristics. The developed models can be used to estimate the accident rates on new or improved roads, In this study, only urban highways were included as a beginning stage. First of all. factors influencing accident rates were selected. Those factors such as traffic volumes. number of signalized intersections, the number of connecting roads, number of pedestrian traffic signals, existence of median barrier, and the number of road lane are also selected based upon the obtainability at the planning stage of roads. The relationship between the selected factors and accident rates shows strong correlation statistically. In this study, roads were classified into 4 groups based on number of lanes, level of roads and the existence of median barriers. The regression analysis had been performed for each group with actual data associated with traffic, roads. and accidents. The developed regression models were verified with another data set. In this study, in order to develop the proposed models, only data on a limited area were used. In order to represent whole area of the country with the developed models. the models should be re-analyzed with vast data.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.167-173
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• 2009

It is important to study on the traffic accident severity reduction because traffic accident is an issue that is directly related to human life. Therefore, this research developed countermeasure to reduce traffic accident severity considering various factors that affect the accident severity. This research developed the Accident Severity Prediction Model using the collected accident data from Seohaean Expressway in 2004~2006. Through this model, we can find the influence factors and methodology to reduce accident severity. The results show that speed limit violation, vehicle defects, vehicle to vehicle accident, vehicle to person accident, traffic volume, curve radius CV(Coefficient of variation) and vertical slope CV were selected to compose the accident severity model. These are certain causes of the severe accident. The accidents by these certain causes present specific sections of Seohaean Expressway. The results indicate that we can prevent severe accidents by providing selected traffic information and facilities to drivers at specific sections of the Expressway.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.29-40
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• 2008

Police agency is indicated that the number of children's traffic accident is tending downwards, however about one child is dead every day due to traffic accident. Major parts of the accidents happen during walking; among the rest, jaywalking is the biggest reason. Many accidents take plate on the road to school or near the home so government legislate children safeguard zone at 1995. According to the legislation, drivers have to reduce speed and there are safety facilities for children at children safeguard zone. This study finds the problems of children safeguard zone and suggest more effective and quantitative method for children safeguard zone. Firstly this study grasps the characters of children's pattern movement and children's traffic accident at children safeguard zone and then divides specific danger factors of children's traffic accident at children safeguard zone. Secondly, each factor is given danger level depending on danger degree and suggests effective method for assignment standard of children safeguard zone using all of these things.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.2
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• pp.3-9
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• 2015

Since changes in land use in urban space cause traffic volume and it is closely related to traffic accidents. Therefore, an analysis on the causes of traffic accidents is judged to be an essential factor to establish the measure to reduce traffic accidents. In this regard, the analysis was conducted on the clustering by using the nearest neighbor indexes with regard to the occurrence frequencies of commercial and residential zone based on traffic accident data of the past five years (2009-2013) with the target of local small-medium sized city, Jinju-si. The analysis results, obtained in this study, are as follows: the occurrence frequency of traffic accidents was the highest in spring and the lowest in winter respectively. The clustering of traffic accident occurrence at nighttime was stronger than at daytime. In addition, terms of the analysis on the clustering of traffic accident according to land use, changes according to the seasons was not significant in commercial areas, while clustering density in winter tended to become significantly lower in residential areas. The analysis results of traffic accident types showed that the side-right angle collision of cars was the highest in frequency occurrence, and widespread in both commercial areas and residential areas. These results can provide us with important information to identify the occurrence pattern of traffic accidents in the structure of urban space, and it is expected that they will be appropriately utilized to establish measures to reduce traffic accidents.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.47-54
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• 2021

The number of freeway traffic accidents in Korea is about 4,000 as of 2020, and deaths per traffic accident is about 3.7 times higher than other roads due to non-recurring congestion and high driving speed. Most of the accident types on freeways are side and rear-end collisions, and one of the main factors is hazard traffic flow caused by merge, diverge and accidents. Therefore, the hazard traffic flow, which appears in a continuous flow such as a freeway, can be said to be important information for the driver to prevent accidents. This study tried to classify hazard traffic flows, such as the speed change point and the section where the speed difference by lane, using individual vehicle information. The homogeneous segment of speed was classified using spatial separation based on geohash and space mean speed that can indicate the speed difference of individual vehicles within the same section and the speed deviation between vehicles. As a result, I could extract the diverging influence segment and the hazard traffic flow segment that can provide dangerous segments information of freeways.

• Journal of Korean Society of Transportation
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• v.32 no.3
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• pp.198-206
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• 2014

According to the statistics of the National Police Agency, red light running (RLR) crashes represent a significant safety issue throughout Korea. This study deals with the RLR crashes occurred at signalized intersections in Cheongju. The objectives of this study are to comparatively analyze the characteristics of between RLR crashes and the Non-RLR crashes, and to find out factors using a Binary Logistic Regression(BLR) model. In pursuing the above, the study gives particular attentions to testing the differences between the above two groups with the data of 2,246 RLR/ 3,884 Non-RLR crashes (2007-2011). The main results are as follows. First, many RLR crashes were occurred in the nighttime and in going straight. Second, the difference between RLR and Non-RLR crashes were clearly defined by crash type, maneuver of vehicle before crash, age of driver (30s, 50s), alcohol use and accident pattern. Finally, a statistically significant model (Hosmer and Lemeshow test : 7.052, p-value : 0.531) was developed through the BLR model.

• Transportation Technology and Policy
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• v.13 no.2
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• pp.74-82
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• 2016

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.149-160
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• 2007

Automobile black boxes store and provide accident and driving information. The accident and driving information can be utilized to build scientific traffic-event database and can be applied in various industries. The objective of this study is to develop a recognition system of dangerous driving through analyzing the driving characteristic patterns. In this paper, possible dangerous driving models are classified into four models on the basis of vehicle behaviors(acceleration, deceleration, rotation) and accident types from existing statistical data. Dangerous driving data have been acquired through vehicle tests using automobile black boxes. Characteristics of driving patterns have been analyzed in order to classify dangerous driving models. For the recognition of dangerous driving, this study selected critical value of each dangerous driving model and developed the recognition algorithm of dangerous driving. The study has been verified by the application of recognition algorithm of dangerous driving and vehicle tests using automobile black boxes. The presented recognition methods of dangerous driving can be used for on-line/off-line management of drivers and vehicles.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.111-117
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• 2017

The purpose of forecasting the traffic accident is to reduce the traffic accident. Therefore, the goal of this study is to provide severity of the accident by Forecasting of Probability of Accident. In Korea, accident data are distributed to the public via internet that includes numbers of accident and fatality as well. And crude level of accident severity in accordance with weather information for metropolitan city level are available by weekly. However, It can not reflect personal needs at specific origin of the travel for a certain traveller. This study aims to consider 68 major intersections with precipitation data, and eventually introduces link based accident severity. In estimating the accident severity both dynamic data such as drivers' characteristics, driving conditions and static data such as geometry of road, intersection characteristics are considered. Also, we identifies accident severity according to the accident type - 'vehicle to vehicle,' 'vehicle to person.' Finally, the outcomes of this study suggests taylor-made accident severity information for a specific traveller for a certain route.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.577-585
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• 2010

Traffic accidents are caused by several factors such as drivers, vehicles, and road environment. It is necessary to investigate and analyze them in advance to prevent similar and repetitive traffic accidents. Especially, the human factor is most significant element and traffic accidents by drinking-driving caused from human factor have become social problem to be paid attention to. The study analyzes traffic accidents resulting from drinking-driving and the effects of driver's attributes and environmental factors on them. The study is composed as two parts. First, the log-linear model is applied to analyze that accidents by drinking or non-drinking driving associate with road geometry, weather condition and personal characteristics. Probability is tested for drinking-driving accidents relative to non-drinking drive accidents. The study analyzes probability differences between genders, between ages, and between kinds of vehicles through odds multipliers. Second, traffic accidents related to drinking are classified into property damage, minor injury, heavy injury, and death according to their severity. Heavy injury is more serious than minor one and death is more serious than heavy injury. The ordinal regression models are established to find effecting factors on traffic accident severity.