• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.1 s.12
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• pp.27-37
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• 2007

The automatic speed enforcement system is expected to play an important role as intelligent transport system (ITS) or advanced franc management system (ATMS). It must be a reliable system checking the overspeedy vehicles automatically, while savine the police manpower and ensuring a safe traffic flow. In terms of traffic engineering, the automatic speed enforcement system may serve to improve driver's violent behaviors, facilitate the smooth and safe traffic flow and thereby, reduce the traffic accident. This study was aimed at analyzing the accident before and after installation of the automatic speed enforcement systems at the frequency, EPDO(equivalent property damage only) and accident cost, analyzing the effects of the automatic system on the traffic flow and accident. As a result, when we equip the automatic speed enforcement system on the downward slope section or after middle section comparing with whole section. We should consider the location of automatic speed enforcement system.

• Journal of Korean Society of Transportation
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• v.34 no.4
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• pp.341-353
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• 2016

Highway is mainly in charge of middle-long distance of vehicular travel. Trip length has shown a growing trend due to increased commute distances by the relocation of public agencies. For this reason, the proportion of driver-driven accidents, caused by their fatigue or sleepiness, are very high on highways. However, existing studies related to accident prediction have mainly considered external factors, such as road conditions, environmental factors and vehicle factors, without driving behavior. In this study, we suggested an accident index (FDR, Fatigued Driving Rate) based on traffic behavior using large-scale Car Navigation path data, and exlpored the relationship between FDR and traffic accidents. As a result, FDR and traffic accidents showed a high correlation. This confirmed the need for a paradigm shift (from facilities to travel behavior) in traffic accident prediction studies. FDR proposed in this study will be utilized in a variety of fields. For example, in providing information to prevent traffic accidents (sleepiness, reckless driving, etc) in advance, utilization of core technologies in highway safety diagnostics, selection of priority location of rest areas and shelter, and selection of attraction methods (rumble strips, grooving) for attention for fatigued sections.

• International Journal of Highway Engineering
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• v.12 no.2
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• pp.43-49
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• 2010

This study deals with the traffic accident of the Cheongju arterial link sections. The purpose of the study is to develop the traffic accident model. In pursuing the above, this study gives particular attentions to developing the ZAM(zero-altered model) model using the accident data of arterial roads devided by 322 small link sections. The main results analyzed by ZIP(zero inflated Poisson model) and ZINB(zero inflated negative binomial model) which are the methods of ZAM, are as follows. First, the evaluation of various developed models by the Vuong statistic and t statistic for overdispersion parameter ${\alpha}$ shows that ZINB is analyzed to be optimal among Poisson, NB, ZIP(zero-inflated Poisson) and ZINB regression models. Second, ZINB is evaluated to be statistically significant in view of t, ${\rho}$ and ${\rho}^2$ (0.63) values compared to other models. Finally, the accident factors of ZINB models are developed to be the traffic volume(ADT), number of entry/exit and length of median. The traffic volume(ADT) and the number of entry/exit are evaluated to be the '+' factors and the length of median to be '-' factor of the accident.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.3
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• pp.102-111
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• 2012

Expresway traffic accident is fatal accident by high speed, especially human injury is a great social issue. This paper aims to identify characteristic differences of highway accidents that involve human injuries or not. To analysis the elements that affect the two types of accidents used the logistic regression model. The analysis showed that human injury accident rate is increased in case of straight road, flat, or cut-slope areas, barriers, male driver, and older driver. These results provide the ground for actions to counter the problems. By discovering factors for accidents leading to fatality, this study can provide important implications for authorities that establish highway safety measures and policies in preventing human injuries or deaths from car accidents.

• International Journal of Highway Engineering
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• v.10 no.4
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• pp.117-125
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• 2008

Recently, users of bicycles as a green mode are rising sharply, but there are few efforts to increase bicycle safety and to decrease the number of accidents between vehicles and bicycle users. Therefore, this research seeks to improve bicycle safety at intersections by analysing causation factors of bicycle accidents pattern and providing optimal intersection design guidelines. For this study, real bicycle accident data of fifty six occurred in the Incheon metropolitan area in the year of 2005 were collected and field surveys were conducted. In addition, this research developed a bicycle accident pattern model with using multinomial logit model. The model results showed that presence of fatality, presence of traffic islands on the minor road, highway_type, weather, presence of traffic bus_stop on the major road, minor road lane width, victim induce factor are significant for bicycle safety.

• Journal of Korean Society of Transportation
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• v.33 no.5
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• pp.497-507
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• 2015

Nonrecurrent congestion of freeway was primarily caused by incident. The main cause of incident was known as a traffic accident. Therefore, accurate prediction of traffic incident clearance time is very important in accident management. Traffic accident data on freeway during year 2008 to year 2014 period were analyzed for this study. KNN(K-Nearest Neighbor) algorithm was hired for developing incident clearance time prediction model with the historical traffic accident data. Analysis result of accident data explains the level of accident significantly affect on the incident clearance time. For this reason, incident clearance time was categorized by accident level. Data were sorted by classification of traffic volume, number of lanes and time periods to consider traffic conditions and roadway geometry. Factors affecting incident clearance time were analyzed from the extracted data for identifying similar types of accident. Lastly, weight of detail factors was calculated in order to measure distance metric. Weight was calculated with applying standard method of normal distribution, then incident clearance time was predicted. Prediction result of model showed a lower prediction error(MAPE) than models of previous studies. The improve model developed in this study is expected to contribute to the efficient highway operation management when incident occurs.

• International Journal of Highway Engineering
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• v.18 no.4
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• pp.93-102
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• 2016

PURPOSES : There are many recently constructed roundabouts in Jeollabuk-do province. This study analyzed how roundabouts reduce the risk of accidents and improve safety in the province. METHODS : This study analyzed safety improvement at roundabouts by using an accident prediction model that uses an Empirical Bayes method based on negative binomial distribution. RESULTS : The results of our analysis model showed that the total number of accidents decreased from 130 to 51. Roundabouts also decreased casualties; the number of casualties decreased from 7 to 0 and the seriously wounded from 87 to 16. The effectiveness of accident reduction as analyzed by the accident prediction model with the Empirical Bayes method was 60%. CONCLUSIONS : The construction of roundabouts can bring about a reduction in the number of accidents and casualties, and make intersections safer.

• International Journal of Highway Engineering
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• v.14 no.6
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• pp.121-129
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• 2012

PURPOSES : Traffic accidents at intersections have been increased annually so that it is required to examine the causations to reduce the accidents. However, the current existing accident models were developed mainly with non-linear regression models such as Poisson methods. These non-linear regression methods lack to reveal complicated causations for traffic accidents, though they are right choices to study randomness and non-linearity of accidents. Therefore, to reveal the complicated causations of traffic accidents, this study used structural equation methods(SEM). METHODS : SEM used in this study is a statistical technique for estimating causal relations using a combination of statistical data and qualitative causal assumptions. SEM allow exploratory modeling, meaning they are suited to theory development. The method is tested against the obtained measurement data to determine how well the model fits the data. Among the strengths of SEM is the ability to construct latent variables: variables which are not measured directly, but are estimated in the model from several measured variables. This allows the modeler to explicitly capture the unreliability of measurement in the model, which allows the structural relations between latent variables to be accurately estimated. RESULTS : The study results showed that causal factors could be grouped into 3. Factor 1 includes traffic variables, and Factor 2 contains turning traffic variables. Factor 3 consists of other road element variables such as speed limits or signal cycles. CONCLUSIONS : Non-linear regression models can be used to develop accident predictions models. However, they lack to estimate causal factors, because they select only few significant variables to raise the accuracy of the model performance. Compared to the regressions, SEM has merits to estimate causal factors affecting accidents, because it allows the structural relations between latent variables. Therefore, this study used SEM to estimate causal factors affecting accident at urban signalized intersections.

• International Journal of Highway Engineering
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• v.15 no.2
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• pp.131-138
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• 2013

PURPOSES : The intents of the study are to identify the accident factors and to demonstrate the potentials of tobit model as a tool to study the number of accidents on arterial roads segments. METHODS : This paper uses a tobit regression as a methodology to analyze the factors affecting the number of accidents. In pursuing the above goal, this study gives particular attentions to analyzing the data of 2,446 accidents (1,610 in major arterial roads and 836 in minor arterial roads) occurred on arterial roads in 2007 to 2010. RESULTS : First, 3 accident models which were classified by total arterial roads, major arterial roads and minor arterial roads, and were all statistically significant were developed. Second, the exclusive right-turn lane as common variable, and the number of accident, traffic volume, number of lanes, link length, rate of median, number of entrances, number of pedestrian crossings, number of curves, number of bus stops and exclusive left-turn as specific variables of the models were selected. Finally, the paired sample t-test could not be rejected the null hypotheses of three types of models. CONCLUSIONS : Using data from vehicle accidents on arterial roads, the estimation results show that many factors related to roadway geometrics and traffic characteristics significantly affect to the number of accidents.

• International Journal of Highway Engineering
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• v.14 no.1
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• pp.95-102
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• 2012

This study has been conducted to characterize the relations between the accident rate and the overlap section elements where the horizontal alignment and vertical alignment are overlapped. The researches were performed on Horizontal curve sections of 4-lane highways with 100km/h of design speed and speed limit. Korea Highway Corporation's Geographic Figurative Information System was adopted for geometric organization and Highway Traffic Accident Statistics was used. The results reveal that sections made of a single slope without vertical curve has greater accident rate than those with vertical curve, and that sections with 1 vertical curve are higher in the accident rate than those with over 2 vertical curve. For the sections with 1 vertical curve, SAG sections are higher than CREST sections and for the previous straight section of horizontal curve are higher than curved ones. In particular, when the road surface is wet, the accident rate is closely related with SAG vertical curves or leftward horizontal curved sections. This study will have meanings that it proposes the importance of design of road alignment by taking consideration of 3D synthetic alignment conditions for improvement of the road safety.