• Sleep Medicine and Psychophysiology
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• v.10 no.2
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• pp.84-87
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• 2003

Drowsy driving is a major cause of automobile crashes and can lead to more serious injuries than other causes of traffic accidents. Factors increasing the risk of drowsy driving and related crashes include sleep loss, late night driving, untreated or unrecognized sleep disorders, use of sedating medications and consumption of alcohol. Young people, especially young males, shift workers, and people with untreated sleep apnea syndrome and narcolepsy are well known as the population groups at highest risk. To prevent drowsy driving and its consequences, getting adequate and quality sleep is both easier and much more successful than any remedial measure. Other helpful behaviors include avoidance of alcoholic beverages and limiting late night driving. Taking a short nap or consuming caffeine can make a short-term difference in driving alertness. In addition, information should be actively provided to the public about the importance of sleep disorders and their consequences. To reduce injuries and death caused by drowsy driving, it is a prerequisite to increase public awareness that drowsy driving can cause serious automobile crashes and has morbidity and mortality rates as high as those of drunk driving.

• International Journal of Highway Engineering
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• v.15 no.4
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• pp.135-146
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• 2013

PURPOSES : This study aimed to analyze the impact the operation of pre-signals at 4-leg signalized intersections and present primary environmental factors of roads that need to be considered in the installation of pre-signals. METHODS : Shift of proportions safety effectiveness evaluation method which assesses shifts in proportions of target collision types to determine safety effectiveness was applied to analyze traffic crash by types. Also, Empirical Bayes before/after safety effectiveness evaluation method was adapted to analyze the impact pre-signal installation. Negative binomial regression was conducted to determine SPF(safety performance function). RESULTS : Pre-signals are effective in reducing the number of head on, right angle and sideswipe collisions and both the total number of personal injury crashes and severe crashes. Also, it is deemed that each factor used as an independent variable for the SPF model has strong correlation with the total number of personal injury crashes and severe crashes, and impacts general traffic crashes as a whole. CONCLUSIONS: This study suggests the following should be considered in pre-signal installation on intersections. 1) U-turns allowed in the front and rear 2) A high number of roads that connect to the intersection 3) Many right-turn traffic flows 4) Crosswalks installed in the front and rear 5) Insufficient left-turn lanes compared to left-turn traffic flows or no left-turn-only lane.

• International Journal of Highway Engineering
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• v.19 no.6
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• pp.201-212
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• 2017

PURPOSES : The objective of this study is to identify the characteristics affecting traffic accidents that have occurred in 564 industrial complexes nationwide from 2011 to 2015. METHODS : The traffic accidents were specified using various factors such as industrial complex type (national VS. general), industrial complex degradation (old VS. non-old), location of complex (capital VS. non-capital), and traffic law violation (speeding, signal violation, and median invasion). The average number of crashes and accident ratio (fatal, severe, and both) in terms of characteristics of industrial complexes were calculated. With a sample of crashes of the industrial complexes for 5 years, statistical significances were tested to analyze and compare the differences based on industrial complex and traffic law characteristics using parametric and non-parametric methods. RESULTS : From statistical results, it is observed that the crash frequency occurring in old industrial complexes is three times higher than that in non-old industrial complexes. Old industrial complexes located in a capital area, old national industrial complexes, and old general industrial complexes are considerably related to higher crash frequency, but the fatal accident ratio appeared to have no statistical difference across industrial complex characteristics. Severe crashes are more likely to occur in non-old industrial complexes on an average. CONCLUSIONS : It is necessary to eliminate potential threats to roads and traffic in the same manner as illegal parking in industrial complexes through the restoration of old industrial complexes. To improve the efficiency of road infrastructure, efforts should be made to improve traffic safety in accordance with industrial characteristics such as planning and operation of relevant local government programs.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.1-7
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• 2020

This study is a study on the development of AEBS test scenarios for traffic accidents in Korea, and was compared and analyzed using the Traffic Accident Analysis Program. To ensure the safety of passengers and pedestrians in traffic accidents, the number of cars equipped with ADAS is increasing rapidly at all car manufacturers in each country. For traffic accidents used in this study, the domestic traffic accident database (ACCC) produced by SAMSONG was used. Domestic traffic accidents differ from overseas traffic accidents in terms of road type, signal system, driver's seat location and number of vehicles. ACCC databases, which supplemented and reinforced these differences, built a database based on the PC-CRASH program. In the study, we analyze the types of accidents to develop comparative scenarios for each type of road and collision type of traffic accidents. When the road types of traffic accidents in Korea were divided into five types and the collision types were divided into six, it was confirmed that the most types of FRONT-SIDE crashes appeared at the intersection. It is expected that the frequency of possible traffic accidents and collision types can be predicted according to the road type in the accident database, we that it can be used as an AEBS test scenario development suitable for the domestic road environment.

• Journal of Korean Society of Transportation
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• v.34 no.2
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• pp.123-134
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• 2016

Traffic accident at intersections takes 44.3% of total number of accidents on entire road network of Korea in 2014. Although several studies addressed contributory factors of accidents at signalized intersection, very few is known about the factors at rural unsignalized intersections. The objective of this study is therefore to investigate specific characteristics of crashes at rural unsignalized intersection and to identify contributory factors in causing crashes by statistical approach using the Ordered Logistic Regression Model. The results show that main type of car crashes at unsignalized intersection during the daytime is T-bone crashes and the number of crashes at 4-legged intersections are 1.53 times more than that at 3-legged intersections. Most collisions are caused by negligence of drivers and violation of Right of Way. Based upon the analysis, accident severity is modeled as classified by two types such as 3-legged intersection and 4-legged intersection. It shows that contributory factors in causing crashes at rural unsignalized intersections are poor sight distance problem, average daily traffic, time of day(night, or day), angle of intersection, ratio of heavy vehicles, number of traffic violations at intersection, and number of lanes on minor street.

• International Journal of Highway Engineering
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• v.9 no.2 s.32
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• pp.77-87
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• 2007

Traffic accidents on freeway are occurred by various factors, and driver inattention is one of the most important factors causing traffic accidents. To warn drivers about unexpected dangerous events and diminish driver inattention problems, traffic safety facilities including warning and regulatory traffic signs; delineators; rumble strips are installed. In this study, the traffic safety effect of shoulder rumble sips were investigated using "Comparison Croup (C-G)" method developed by Hauer. Through the analyses, it was found that numbers of run-off-the road crashes were reduced as 2.43 crashes per year after the installation of shoulder rumble strips on the freeway. Based on the analysis results in this study, it was concluded that shoulder rumble strips on the freeway contribute to reduce traffic accidents, especially run-off-the road crashes.

• Journal of Korean Society of Transportation
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• v.29 no.3
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• pp.93-101
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• 2011

In 2008, Korea has observed total 215,822traffic accidents Although the number has decreased since then, the crash rate is still higher than those of other advanced countries. In particular, high rate of pedestrian accidents occurred on urban streets is recognized as a serious problem. The previous studies, however, are not entirely considerate of accident factors by accident type. Inspired by the fact, this study analyzes factors affecting traffic accident by accident type. Using the accident data collected on urban streets in Seodaemun-gu, this paper classifies the accidents into two groups (i.e., vehicle-vs-vehicle and vehicle-vs-person crashes), and analyzes relationships between severity and exogenous variables. For the analysis, Structural Equation Modeling (SEM) is employed to estimate relationships among exogenous factors of traffic accident by each type on urban streets. The resulting model reveals that roadway related factors are highly correlated with the severity of vehicle-vs-vehicle crashes whereas environment factors are with vehicle-vs-person crashes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.1-7
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• 2015

The traffic accidents in Korea have been increasing every year due to various reasons and simultaneously causing socioeconomic cost at the national level. This study has analyzed the correlation between meteorological factors and the traffic accidents in Seoul during 2013. Especially, we have selected season, rain and temperature among the meteorological factors to identify their significance with the traffic accidents. In addition, analysis of variance, t-test and a multiple regression technique is applied. Major findings from the analyses are discussed at the district point of view, including the different effect of weather condition and the interaction effect of rain and temperature in winter. The results of this study would be useful for developing management strategies to reduce car crashes and injury severity in Seoul.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.33-43
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• 2022

The number of car crashes increases along with the increasing number of vehicles. Hence, diverse initiatives on traffic accidents have been implemented, targeting zero crash fatalities. According to the 3rd Traffic Safety Master Plan of 2016, the current standard selecting road accident black spots prioritizes locations with the high cumulative death toll. While this standard is suitable for roads that a city government manages to some extent, it is not suitable for roads less than 20 meters that a borough (Gu) handles. The roads under the supervision of a borough do not have enough death toll, and thus improvements on its road accident black spots are highly limited. In addition, discovering the causes of traffic accidents is not easy when the number of car accidents is obtained by considering only fatal accidents, which are relatively low in number. Therefore, including all traffic accidents might identify causes of accidents and result in better advancements. Therefore, this research follows rational decision-making and suggests new National Traffic Safety Master Plan standards. These new standards are obtained by comparing accident costs between the location of fatal crashes and road accident black spots. The analysis result shows that considering all types of accidents yields better results. For example, a Three-way Intersection in front of Zion Day Care Center, one of the selected spots under the current standard, has lower road crash costs than Sinchon Intersection, a selected spot under a new standard. Therefore, the study concludes that the standards to select road accident black spots need to include traffic accident severity and road crash costs.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1123-1130
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• 2020

This study aims to classify the severity in car crashes using five classification learning models. The dataset used in this study contains 21,013 vehicle crashes, obtained from Korea Expressway Corporation, between the year of 2015-2017 and the LightGBM(Light Gradient Boosting Model) performed well with the highest accuracy. LightGBM, the number of involved vehicles, type of accident, incident location, incident lane type, types of accidents, types of vehicles involved in accidents were shown as priority factors. Based on the results of this model, the establishment of a management strategy for response of highway traffic accident should be presented through a consistent prediction process of accident severity level. This study identifies applicability of Machine Learning Models for Predicting of the Severity of Car Traffic Accidents on a Highway and suggests that various machine learning techniques based on big data that can be used in the future.