• International Journal of Highway Engineering
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• v.17 no.6
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• pp.75-83
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• 2015

PURPOSES : This study deals with the traffic accidents classified by the traffic analysis zone. The purpose is to develop the accident density models by using zonal traffic and socioeconomic data. METHODS : The traffic accident density models are developed through multiple linear regression analysis. In this study, three multiple linear models were developed. The dependent variable was traffic accident density, which is a measure of the relative distribution of traffic accidents. The independent variables were various traffic and socioeconomic variables. CONCLUSIONS : Three traffic accident density models were developed, and all models were statistically significant. Road length, trip production volume, intersections, van ratio, and number of vehicles per person in the transportation-based model were analyzed to be positive to the accident. Residential and commercial area ratio and transportation vulnerability ratio obtained using the socioeconomic-based model were found to affect the accident. The major arterial road ratio, trip production volume, intersection, van ratio, commercial ratio, and number of companies in the integrated model were also found to be related to the accident.

• Journal of Korean Society of Transportation
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• v.18 no.5
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• pp.7-16
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• 2000

This paper is focused on verifying time-space repetition of the highway accident and finding the their causes and deterrents. We classify all months into several seasonal groups, develop the model for each seasonal group and analyze the results of these models for Joong-bu highway. The existence of seasonal effect is verified by the analysis or self-organizing map and the accident indices. Agglomerative hierarchical cluster analysis which is used to decide the seasonal groups in accordance with accident patterns, winter group, spring-fall group. and summer group. The accident features of winter group are that the accident rate is high but the severity rate is low. while those of summer group are that the accident rate is low but the severity rate is high. Also, the regression model which is developed to identify the accident Pattern or each seasonal group represents that the season-related factors, such as the amount of rainfall, the amount of snowfall, days of rainfall, days of snowfall etc. are strongly related to the accident pattern of evert seasonal group and among these factors the traffic volume, amount of rainfall. the amount of snowfall and days of freezing importantly affect the local accident Pattern. So, seasonal effect should be considered to the identification of high-risk road section. the development of descriptive and Predictive accident model, the resource allocation model of accident in order to make safety management plan efficient.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2437-2445
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• 2013

The objective of this study is finding the relationship between interstate highway accident frequencies and geometrics using Random Parameter Negative Binomial model. Even though it is impossible to take account of the same design criteria to the all segments or corridors on the road in reality, previous research estimated the fixed value of coefficients without considering each segment's characteristic. The drawback of the traditional negative binomial is not to explain the integrated variations in terms of time and the distinct characters specific segment has. This results in under-estimation of the standard error which inflates the t-value and finally, affects the modeling estimation. Therefore, this study tries to find the relationship of accident frequencies with the heterogeneous geometrics using 9-years and 7-interstate highway data in Washington State area. 16-types of geometrics are used to derive the model which is compared with the traditional negative binomial Model to understand which Model is more suitable. In addition, by calculating marginal effect and elasticity, heterogeneous variables' effect to the accidents are estimated. Hopefully, this study will help to estiblish the future policy of geometrics.

• International Journal of Highway Engineering
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• v.17 no.5
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• pp.39-46
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• 2015

PURPOSES: The operational characteristics of roundabouts are generally influenced by location as well as traffic volume. The goal of this study is to develop urban and rural roundabout accident models and to discuss safety improvement guidelines based on the model. METHODS : To analyze accidents, count data models are utilized in this study. This study used accident data from 2010 to 2013 for 56 roundabouts collected from the Traffic Accident Analysis System (TASS) of Road Traffic Authority. Poisson and negative binomial regression models were developed for this study using NLOGIT 4.0. RESULTS : The main results are as follows. First, the hypotheses that there are distributional differences in the number of accidents and injuries/fatalities among rural and urban roundabouts were accepted. Second, Poisson and negative binomial regression accident models, which were all statistically significant, were developed. Seven independent variables, which were statistically significant, were adopted. Third, the common variable of models was evaluated to be traffic volume. CONCLUSIONS : This study developed two negative binomial roundabout accident models and suggested some accident reduction strategies. The results are expected to give some implications to the safety improvement of roundabout.

• Journal of Korean Society of Transportation
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• v.23 no.7 s.85
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• pp.77-86
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• 2005

Level of service(LOS) is a quantify measure describing operational conditions within a traffic stream, generally, in terms of such service measures as speed, travel time, freedom to measures, traffic interruptions, comfort and convenience. The LOS is leveled by highway facilities according to measure of effectiveness(MOE) and then used to evaluate performance capacity. The current evaluation of a urban road is performed by only a aspect of traffic operation without any concepts of safety. Therefore, this paper presents a method for evaluation of risk order for urban road with new MOE, user cost analysis, considering both smooth traffic operation(congestion) and traffic safety(accident). The user coat is included traffic accident cast by traffic safety and traffic congestion cost by traffic operation. First of all, a number of traffic accident and accident rate by highway geometric is inferred from urban road traffic accident prediction model (Poul Greibe(2001)) Secondly, a user cost is inferred as traffic accident cast and traffic congestion cost is putting together. Thirdly, a method for evaluation of a urban road is inferred by user cost analysis. Fourthly a accident rate by segment predict with traffic accidents and data related to the accidents in $1996{\sim}1998$ on 11 urban road segments, Gwang-Ju, predicted accident rate. Traffic accident cost predict using predicted accident rate, and, traffic congestion cost predict using predicted average traffic speed(KHCM). Fifthly, a risk order are presented by predicted user cost at each segment in urban roads. Finally, it si compared and evaluated that LOS of 11 urban road segments, Gwang-Ju, by only a aspect of traffic operation without any concepts of safety and risk order by a method for evaluation of urban road in this paper.

• 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.

• International Journal of Highway Engineering
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• v.17 no.3
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• pp.133-141
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• 2015

PURPOSES : This study dealt with traffic accidents occurring within roundabouts. The objective of this study was to analyze safety effect by introduction of roundabouts. METHODS : In pursuing the above, traffic accident data on roundabouts are collected and compared. For the analysis, collected data were separated as all intersection points, turning lane accident, approach lane accident by geometric design. RESULTS : Through the study results, it was found that the total accidents decreased by 55 accidents/2 year with safety effect of roundabouts. Also the result shows that accidents by point of two-lane roundabout at turning lane(0.26) and approach lane(0.27) is risky than total accidents by point(0.09). Moreover, accidents by point shows high value as diameter of a roundabout is bigger. CONCLUSIONS : When a roundabout is introduced at the intersections there are safety effects by reduction of traffic accidents.

• Proceedings of the KIEE Conference
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• 2008.04c
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• pp.175-177
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• 2008

The level crossing collision accident which comprises more than 90 percent of all level crossing accidents is one of the most serious safety problems. There is a critical need for providing safe strategy and is focusing on the level crossing information rather than measures at a grade crossing. This study is intended to develop technology for accident prevention and damage reduction based on accident cases analysis result and improvement direction to complement shortcomings of safety equipment of conventional level crossing and to establish safety of travelers(train, motor vehicle, person).

• International Journal of Highway Engineering
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• v.19 no.4
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• pp.53-59
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• 2017

PURPOSES : This study deals with traffic accidents involving trucks. The objective of this study is to develop a traffic accident model for trucks at roundabouts. METHODS : To achieve its objective, this study gives particular attention to develop appropriate models using Poisson and negative binomial regression models. Traffic accident data from 2007 to 2014 were collected from TAAS data set of road traffic authority. Thirteen explanatory variables such as geometry and traffic volume were used. RESULTS : The main results can be summarized as follows: (1) two statistically significant Poisson models (${\rho}^2=0.398$ and 0.435) were developed, and (2) the analysis revealed the common variables to be traffic volume, number of exit lanes, speed breakers, and truck apron width. CONCLUSIONS : Our modeling reveals that increasing the number of speed breakers and speed limit signs, and widening the truck apron width are important for reducing the number of truck accidents at roundabouts.

• International Journal of Highway Engineering
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• v.17 no.6
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• pp.85-95
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• 2015

PURPOSES : The objective of this study is to analyze factors affecting traffic accident severity for determining countermeasures on freeway climbing lanes. METHODS : In this study, an ordered probit model, which is a widely used discrete choice model for categorizing crash severity, was employed. RESULTS : Results suggest that factors affecting traffic accident severity on climbing lanes include speed, drowsy driving, grade of uphill 3%, gender (male offender and male victim), and cloud weather. CONCLUSIONS : Several countermeasures are proposed for improving traffic safety on freeway climbing lanes based on the analysis of crash severity. More extensive analysis with a larger data set and various modeling techniques are required for generalizing the results.