PURPOSES : The purpose of this study is to compare applicability, explanation power, and flexibility of traffic accident models between estimating model using the statistical method and the machine learning method. METHODS: In order to compare and analyze traffic accident models between model estimated using the statistical method and machine learning method, data acquisition was conducted, and traffic accident models were estimated using statistical methods such as negative binomial regression model, and machine learning methods such as a generalized regression neural network (GRNN). Then, the fitness of model as R2, root mean square error (RMSE), mean absolute percentage error (MAPE), accuracy, etc., were determined to compare the traffic accident models. RESULTS: The results showed that the annual average daily traffic (AADT), speed limits, number of lanes, land usage, exclusive right turn lanes, and front signals were significant for both traffic accident models. The GRNN model of total traffic accidents had been better statistical significant with R2: 0.829, RMSE: 2.495, MAPE: 32.158, and Accuracy: 66.761 compared with the negative binomial regression model with R2: 0.363, RMSE: 9.033, MAPE: 68.987, and Accuracy: 8.807. The GRNN model of injury traffic accidents also showed similar results of model’s statistical significance. CONCLUSIONS: Traffic accident models estimated with GRNN had better statistical significance compared with models estimated with statistical methods such as negative binomial regression model.

PURPOSES: The purpose of this study is to develop a crash prediction model at signalized intersections, which can capture the randomness and uncertainty of traffic accident forecasting in order to provide more precise results. METHODS: The authors propose a random parameter (RP) approach to overcome the limitation of the Count model that cannot consider the heterogeneity of the assigned locations or road sections. For the model’s development, 55 intersections located in the Daejeon metropolitan area were selected as the scope of the study, and panel data such as the number of crashes, traffic volume, and intersection geometry at each intersection were collected for the analysis. RESULTS: Based on the results of the RP negative binomial crash prediction model developed in this study, it was found that the independent variables such as the log form of average annual traffic volume, presence or absence of left-turn lanes on major roads, presence or absence of right-turn lanes on minor roads, and the number of crosswalks were statistically significant random parameters, and this showed that the variables have a heterogeneous influence on individual intersections. CONCLUSIONS : It was found that the RP model had a better fit to the data than the fixed parameters (FP) model since the RP model reflects the heterogeneity of the individual observations and captures the inconsistent and biased effects.

PURPOSES: The goal of this study is the development of roundabout accident models for urban and non-urban areas. METHODS: This study performed a comparative analysis of the regional factors affecting accidents. Traffic accident data were collected for the period 2010~2014 from the TAAS data set of the Road Traffic Authority. To develop the roundabout accident models, the Poisson and negative binomial regression models were used. A total of 25 explanatory variables such as geometry, and traffic volume were used. RESULTS : The key findings are as follows: First, it was found that the null hypotheses that the number of accidents is the same should be rejected. Second, three Poisson regression accident models, which are statistically significant (p2 of 0.154 and 0.385) were developed. Third, it was noted that although the common variable of the three models (models Ⅰ~Ⅲ) is the number of entry lanes, the specific variables are entry lane width, roundabout sign, number of circulatory roadways, splitter island, number of exit lanes, exit lane width, number of approach roads, and truck apron. CONCLUSIONS: The results of this study can provide suggestive countermeasures for decreasing the number of roundabout accidents.

PURPOSES : The purpose of this study is to develop models of accidents occurring at circular intersections related to the time of day and night and driver gender, and to provide countermeasures for safer circular intersections. METHODS: Seventy intersections built before 2008 were surveyed for inclusion in the modeling. Traffic accident data from 2008 to 2014 were collected from the TAAS data set of the Road Traffic Authority. Sixteen variables explaining the accidents including geometry and traffic volume were selected from the literature and seven multiple linear regression models were developed using SPSS 20.0. RESULTS: First, the null hypotheses, that the number of traffic accidents are not related to driver gender or time of day, were rejected at a 5% level of significance. Second, seven statistically significant accident models with R2 value of 0.643-0.890 were developed. Third, in daytime models by gender, when the right-turn-only lane was selected as the common variable, the number of lanes, presence of driveways and speed humps, diagrammatic exit destination sign, and total entering traffic volume were evaluated as specific variables. Finally, in nighttime models by gender, when the diagrammatic exit destination sign was selected as the common variable, total entering traffic volume, presence of right-turnonly lanes, number of circulatory road way lanes, and presence of splitter islands and driveways were identified as specific variables. CONCLUSIONS: This study developed seven accident models and analyzed the common and specific variables by time of day and gender. The results suggest approaches to providing countermeasures for safer circular intersections.

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 (ρ2 = 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.

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.

PURPOSES : This study tries to develop the accident models of 4-legged signalized intersections in Busan Metropolitan city with random parameter in count model to understanding the factors mainly influencing on accident frequencies. METHODS: To develop the traffic accidents modeling, this study uses RP(random parameter) negative binomial model which enables to take account of heterogeneity in data. By using RP model, each intersection’s specific geometry characteristics were considered. RESULTS : By comparing the both FP(fixed parameter) and RP modeling, it was confirmed the RP model has a little higher explanation power than the FP model. Out of 17 statistically significant variables, 4 variables including traffic volumes on minor roads, pedestrian crossing on major roads, and distance of pedestrian crossing on major/minor roads are derived as having random parameters. In addition, the marginal effect and elasticity of variables are analyzed to understand the variables’impact on the likelihood of accident occurrences. CONCLUSIONS :This study shows that the uses of RP is better fitted to the accident data since each observations’specific characteristics could be considered. Thus, the methods which could consider the heterogeneity of data is recommended to analyze the relationship between accidents and affecting factors(for example, traffic safety facilities or geometrics in signalized 4-legged intersections).

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.

PURPOSES : The purposes of this study are to compare the day and night characteristics and to develop the models of traffic accidents. in Rural Signalized Intersections METHODS : To develop day and night traffic accident models using the Negative Binomial Model, which was constructed for 156 signalized intersections of rural areas, through field investigations and casualty data from the National Police Agency. RESULTS : Among a total of 17 variances, the daytime traffic accident estimate models identified a total of 9 influence factors of traffic accidents. In the case of nighttime traffic accident models, 11 influence factors of traffic accidents were identified. CONCLUSIONS: By comparing the two models, it was determined that the number of main roads was an independent factor for daytime accidents. For nighttime accidents, several factors were independently involved, including the number of entrances to sub-roads, whether left turn lanes existed in major roads, the distances of pedestrian crossings to main roads and sub-roads, lighting facilities, and others. It was apparent that if the same situation arises, the probability of an accident occurring at night is higher than during the day because the speed of travel through intersections in rural areas is somewhat higher at night than during the day.

PURPOSES : The objective was to develop the advanced method which could not explain each observation’s specific characteristic in the present negative binomial method that results in under-estimation of the standard error(t-value inflation) and affects the confidence of whole derived results. METHODS : This study dealt with traffic accidents occurring within interchange segment on highway main line with RPNB(Random Parameter Negative Binomial) method that enables to take account of heterogeneity. RESULTS : As a result, AADT and lighting installation type on the road were revealed to have random parameter and in terms of other geometric variables, all were derived as fixed parameter(same effect on every segment). Also, marginal effects were adapted to analyze the relative effects on traffic accidents. CONCLUSIONS : This study proves that RPNB method which considers each observation’s specific characteristics is better fitted to the accident data with geometrics. Thus, it is recommended that RPNB model or other methods which could consider the heterogeneity needs to be adapted in accident analysis.

PURPOSES: This study deals with the pedestrian accidents in case of Cheongju. The goals are to develop the pedestrian accident model. METHODS: To analyze the accident, count data models, truncated count data models and Tobit regression models are utilized in this study. The dependent variable is the number of accident. Independent variables are traffic volume, intersection geometric structure and the transportation facility. RESULTS : The main results are as follows. First, Tobit model was judged to be more appropriate model than other models. Also, these models were analyzed to be statistically significant. Second, such the main variables related to accidents as traffic volume, pedestrian volume, number of Entry/exit, number of crosswalk and bus stop were adopted in the above model. CONCLUSIONS: The optimal model for pedestrian accidents is evaluated to be Tobit model.

PURPOSES : This study deals with the traffic accidents of rotary in Korea. The objective of this study is to develop the accident models by age group based on the various data of rotaries. METHODS : In pursuing the above, this study gives particular attentions to classifying the accident data of 17 rotaries by age, collecting the data of geometric structure, traffic volume and others, and developing the models using SPSS 17.0 and EXCEL. RESULTS : First, 3 multiple linear regression models which were all statistically significant were developed. The value of model of under 30-49 age group were, however, evaluated to be 0.688 and be less than those of other models. Second, the most powerful variables were analyzed to be traffic volume in the model of under 30 age group, circulatory roadway width in the model of 30-49 age group, and the number of approach lane in the model of above 50 age group. Finally, the test results of accident models using RMSE were all evaluated to be fitted to the given data. CONCLUSIONS : This study propose install streetlights, speed humps and widen Circulatory as effective improvements for reduction of accident in rotary.

PURPOSES : This study deals with Rotary by Accident Occurrence Location. The purpose of this study is to develop the accident models of rotary by location. METHODS : In pursuing the above, this study gives particular attentions to developing the appropriate models using multiple linear, Poisson and negative binomial regression models and statistical analysis tools. RESULTS : First, four multiple linear regression models which are statistically significant(their R2 values are 0.781, 0.300, 0.784 and 0.644 respectively) are developed, and four Poisson regression models which are statistically significant(their σ2 values are 0.407, 0.306, 0.378 and 0.366 respectively) are developed. Second, the test results of fitness using RMSE, %RMSE, MPB and MAD show that Poisson regression model in the case of circulatory roadway, pedestrian crossing and others and multiple linear regression model in the case of entry/exit sections are appropriate to the given data. Finally, the common variable that affects to the accident is adopted to be traffic volume. CONCLUSIONS : 8 models which are all statistically significant are developed, and the common and specific variables that are related to the models are derived.

이 연구는 국내 원형교차로에서 발생한 교차로 사고를 다루고 있다. 연구의 목적은 ZAM을 이용하여 원인별 사고모형을 개발하는데 있다. 주요결과는 다음과 같다. 첫째, 교차로 운행방법 위반에서는 ZINB 모형이 적합한 것으로 분석되었다. 둘째, 안전거리 미확보에서도 ZINB 모형이 적합한 것으로 분석되었다. 마지막으로 공통변수로는 교통량과 회전차로 폭이 선정되었다. 교통량이 많을수록 그리고 회전차로 폭이 좁을수록 사고가 많이 발생하는 것으로 분석되었다. 특정변수로는 접근로수와 감속 시설수가 채택되었고, 접근로수가 증가할수록 그리고 감속시설수가 적을수록 사고가 증가하는 것으로 분석되었다. 이 연구는 원형교차로 사고연구에 기여할 것으로 기대된다.

이 논문은 사고유형에 따른 교통사고를 다루고 있다. 연구의 목적은 두 가지 사고유형의 특성을 분석하고, 유형별 모형을 개발하는데 있다. 이를 위해 이 연구는 두 집단 사이의 차이점을 분석하고, 국내 원형교차로 자료를 사용하여 포아송 및 음이항 회귀모형을 개발하는데 그 목적이 있다. 주요 결과는 다음과 같다. 첫째, 차대차 사고가 73.41%로 가장 많은 비중을 차지하는 것으로 분석되었다. 둘째, 차대사람과 차대차 사고건수 및 EPDO를 종속변수로 통계적으로 의미 있는 2개의 포아송 모형과 2개의 음이항 모형이 개발되었다. 셋째, 사고유형별 심각도모형의 공통변수는 교통량, 그리고 특정변수로는 우회전 별도차로 수, 과속방지턱, 진출입구 수 및 횡단보도 수가 채택되었다.

이 연구는 청주시의 가로구간 교통사고를 다루고 있다. 연구의 목적은 가로구간의 기능별 사고모형을 개발하는 데 있다. 이를 위해서 이 연구는 전체 472개의 세부구간으로 분리된 주간선도로와 보조간선도로의 사고 자료를 이용하여 적합한 모형을 개발하는데 중점을 두고 있다. 연구의 주요 결과는 다음과 같다. 첫째, 주간선과 보조간선도로의 사고특성에 대한 t 검정은 두 도로의 사고건수와 EPDO에 차이가 있는 것으로 나타나 기능별 사고모형 개발이 적절한 것으로 분석된다. 둘째, 주간선도로의 EPDO와 사고건수는 모두 ZINB모형이 적합한 것으로 분석된다. 셋째, 보조간선도로 EPDO는 ZINB모형, 그리고 사고건수는 ZIP모형이 최적인 것으로 분석된다. 마지막으로 주간선도로 사고모형(ZINB)의 공통변수는 교통량과 굴곡점수, 보조간선도로의 EPDO모형(ZINB)과 사고건수모형(ZIP) 공통변수는 평균종단경사인 것으로 평가된다.