• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.6
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• pp.133-144
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• 2012

This study focused on estimating influential factors of traffic accidents and analyzing traffic accident severity of elderly and non elderly using traffic accident data. In order to reclassify elderly and non elderly traffic accident by a statistical method from entire traffic accident data, multiple discriminant analysis was applied. Also ordered logit model was applied for analyzing traffic accident severities using traffic accident severities as an independent variable and transportation facilities, road conditions and human characteristics as dependent variables. As results of the comparison between elderly and non elderly traffic accident, the traffic accident severity was affected by the age, types of traffic accidents, human characteristics and road conditions as well. Also, transportation facilities and road conditions affected to more elderly traffic accident than non elderly. Therefore, traffic accident severity would be decreased with the improvement of transportation facilities and road conditions for the elderly.

• International Journal of Highway Engineering
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• v.17 no.2
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• pp.79-87
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• 2015

PURPOSES: According to accident statistics for road built in 2004, the ratio of accidents on frozen roads to normal roads is 0.9%, whereas the fatality ratio is 2.7%. The risk of accidents on frozen roads is very high. Measures taken every year to prevent traffic accidents of frozen roads in the winter season are still insufficient. Additionally, measures have been established mainly on rural roads. Therefore, for urban roads, analyses and measures to prevent accidents are lacking. In this study, data on accidents on frozen roads was used to search for the causes behind these accidents and measures to reduce accidents have been recommended. METHODS: In this study, collected data from the TAMS (Traffic Accident Management System), which were collected by the Seoul National Police Agency was used. The data were divided into vehicle, people, and condition of road. The analytical model used here was the Logistic Regression Model, which is frequently used for traffic safety and accident analysis. This study uses the odds ratio analysis to search for variables related to frozen road traffic accidents in each category. A total of 18 out of 47 variables were found to be the causes of accidents. RESULTS: From the results of the comparative analysis of 18 variables, the category of the condition of the road was found to be the most critical. Contrary to expectations, more accidents occurred in clear weather than in other conditions. Accidents on bridges occurred frequently, and its odds ratio was the highest compared with other road types. When BPT is operated, the probability of accidents on frozen roads is lower than in general conditions, and accidents occurred frequently on roads with less than four lanes. CONCLUSIONS : Based on the results of this study, suggestions for reducing the risk of future domestic road accidents in freezing conditions are indicated as follows. First, it is necessary to perform a technical review of the urban road traffic accidents caused by frozen roads. Second, it is necessary to establish criteria for the study of the road environment based on the major causes of road accidents on frozen roads. Third, improvements in urban road environmental factors should be made.

• International Journal of Highway Engineering
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• v.14 no.6
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• pp.103-110
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• 2012

PURPOSES : In Korea, over 70 percent of the land consists of mountainous and rolling area. Thus, tunnels continue its upward trend as road network are extended. In these circumstances, the importance of tunnel has been increased nowadays and then its safety investigation and research should be performed. This study is focus on confirming and improving the safety of tunnel. On tunnel hood, sunglare effect can irritate driver's behavior instantly and this can result in incident. METHODS : The study of this phenomenon is rarely conducted in domestic and foreign papers, so there is no proper measure for this. This study analyzes the driving environment of the effect of sunglare effect on tunnel hood. RESULTS : Traffic accidents stem from complex set of factors. This study build the Traffic Accident Prediction Models to find out the effect of sunglare effect on tunnel's hood. The independent variables are traffic volume, geometric design of road, length of tunnel and road side environment. Using these variables, this model estimates accident frequency on tunnel hood by Poisson regression model and Negative binomial regression model. Although Poisson regression model have more proper goodness of fit than Negative binomial regression model, Poisson regression model has overdipersion problem. So the Negative binomial regression model is used in this analysis. CONCLUSIONS : Consequently, the model shows that sunglare effect can play a role in driving safety on tunnel hood. As a result, the information of sunglare effect should be noticed ahead of tunnel hood so this can prevent drivers from being in hazard situation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.2
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• pp.30-38
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• 2015

In this study, to improve effectiveness of road management services and the safety of the road in winter, road surface temperature prediction model was developed. We have utilized the existing input data of meteorological data and additional traffic data. This Road surface temperature prediction model was utilizing a Heat-Balance Method additionally considering amount of traffic that produce heat radiation by vehicle-tire friction. This improved model was compared to the based model to check into influence of traffic affecting the road surface temperature. There were verified by comparing the real observed road surface temperature of the third Gyeong-In highway and road surface temperature from the two models. As a result, the error of real observed and the predicted value (RMSE) was found to average $1.97^{\circ}C$. Observed road surface temperature was dramatically affected by the sunlight from 6 a.m. to 2 p.m. and degree of influence decreases after that. The predictive value of the model is lower than the observed value in the afternoon, and higher at night. These results appear due to the shielding of solar radiation caused by the vehicle in the afternoon and at night, the vehicle appeared to cause thermal heat supply.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.129-134
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• 2017

This study aims to develop the traffic accident models by circular intersection type using count data model. The number of accident, the number of fatal and injured persons(FSI), and EPDO are calculated from the traffic accident data of TAAS. The circular intersection accident models are developed through Poisson and negative binomial regression analysis. The main results of this study are as follows. First, the null hypotheses that there are differences in the number of traffic accidents, FSI and EPDO by type of circular intersections are rejected. Second, the scale of intersection(median, large), number of approach road, mean width and length of exit road, area of the circulating roadway and central island are selected as factors influencing the number of traffic accidents, FSI and EPDO in rotary. Third, the scale of intersection(median), guide signs(limited speed, direction, roundabout), number of approach road, entry angle, area of the intersection and central island are adopted as factors influencing the number of traffic accidents, FSI and EPDO in roundabout. Finally, transferring from rotary to roundabout could be expected to make the accident decrease.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.841-854
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• 2020

The paper explains the method to process, analyze and predict traffic patterns in Los Angeles county using Big Data and Machine Learning. The dataset is used from a popular navigating platform in the USA, which tracks information on the road using connected users' devices and also collects reports shared by the users through the app. The dataset mainly consists of information about traffic jams and traffic incidents reported by users, such as road closure, hazards, accidents. The major contribution of this paper is to give a clear view of how the large-scale road traffic data can be stored and processed using the Big Data system - Hadoop and its ecosystem (Hive). In addition, analysis is explained with the help of visuals using Business Intelligence and prediction with classification machine learning model on the sampled traffic data is presented using Azure ML. The process of modeling, as well as results, are interpreted using metrics: accuracy, precision and recall.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.8
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• pp.581-588
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• 2002

Precise highway traffic noise simulation and reduction require the accurate data for sound power levels omitted by vehicles, varied to road surface, traffic speed, vehicle types and makers, different from countries to countries. In this study, we have elaboratively measured Korea highway traffic noise and parameters affecting noise levels at the nearside carriageway edge. From numerical simulation using the measured results for highway traffic noise, we propose not only two correction factors to enhance the accuracy of Korea highway traffic sound power estimation using ASJ Model-1998 but also its typical power spectrum according to road surface type. The measured and predicted highway traffic noise levels using the proposed sound power show little difference within 1 dB.

• International Journal of Highway Engineering
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• v.17 no.6
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• pp.11-18
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• 2015

PURPOSES : The purpose of this thesis is to evaluate the effectiveness of an active noise cancellation (ANC) system in reducing the traffic noise level against frequencies from the predictive model developed by previous research. The predictive model is based on ISO 9613-2 standards using the Noble close proximity (NCPX) method and the pass-by method. This means that the use of these standards is a powerful tool for analyzing the traffic noise level because of the strengths of these methods. Traffic noise analysis was performed based on digital signal processing (DSP) for detecting traffic noise with the pass-by method at the test site. METHODS : There are several analysis methods, which are generally divided into three different types, available to evaluate traffic noise predictive models. The first method uses the classification standard of 12 vehicle types. The second method is based on a standard of four vehicle types. The third method is founded on 5 types of vehicles, which are different from the types used by the second method. This means that the second method not only consolidates 12 vehicle types into only four types, but also that the results of the noise analysis of the total traffic volume are reflected in a comparison analysis of the three types of methods. The constant percent bandwidth (CPB) analysis was used to identify the properties of different frequencies in the frequency analysis. A-weighting was applied to the DSP and to the transformation process from analog to digital signal. The root mean squared error (RMSE) was applied to compare and evaluate the predictive model results of the three analysis methods. RESULTS : The result derived from the third method, based on the classification standard of 5 vehicle types, shows the smallest values of RMSE and max and min error. However, it does not have the reduction properties of a predictive model. To evaluate the predictive model of an ANC system, a reduction analysis of the total sound pressure level (TSPL), dB(A), was conducted. As a result, the analysis based on the third method has the smallest value of RMSE and max error. The effect of traffic noise reduction was the greatest value of the types of analysis in this research. CONCLUSIONS : From the results of the error analysis, the application method for categorizing vehicle types related to the 12-vehicle classification based on previous research is appropriate to the ANC system. However, the performance of a predictive model on an ANC system is up to a value of traffic noise reduction. By the same token, the most appropriate method that influences the maximum reduction effect is found in the third method of traffic analysis. This method has a value of traffic noise reduction of 31.28 dB(A). In conclusion, research for detecting the friction noise between a tire and the road surface for the 12 vehicle types needs to be conducted to authentically demonstrate an ANC system in the Republic of Korea.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.782-785
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• 2004

In the Well-being age, many people use a city park for rest deeply think and constitutional walk. The city park is located at near side by traffic road in urban. Citizens are not satisfied with it's fuction as a haven of peace due to road traffic noise. Thus, this study is for a research on the actual noise condition of a city park in Nowon go. This study uses a prediction method called ASJ-model in order to calculate PWLs of road traffic noise. Using calculated PWLs, noise levels in a park are predicted and compared with measured values.

• 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.