• Title/Summary/Keyword: Random Parameter Negative Binomial Model

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A Development of Traffic Accident Model by Random Parameter : Focus on Capital Area and Busan 4-legs Signalized Intersections (확률모수를 이용한 교통사고예측모형 개발 -수도권 및 부산광역시 4지 교차로를 대상으로-)

  • Lee, Geun-Hee;Rho, Jeong-Hyun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.14 no.6
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    • pp.91-99
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    • 2015
  • This study intends to build a traffic accident predictive model considering road geometrics, traffic and enviromental characteristics and identify the relationship of 4-legs intersection accidents in Seoul and Busan metropolitan area. The RPNB(Random Parameter Negative Binomial) model shows improvement over the fixed NB(Negative Binomial) and out of 53 variables, 10 variables (main road number of lane, main road vehicle traffic volume(left), minor road vehicle traffic volume(right), main road drive restriction, minor road sight distance, minor road median strip, minor road speed limit, minor road speed restriction) showed to have significant variables affecting traffic accident occurrences in 4-legs signilized intersections. Also, among 10 significant variables, 2 variables(minor road sight distance, minor road speed restriction) found to be random parameters.

Relationship between Interstate Highway Accidents and Heterogeneous Geometrics by Random Parameter Negative Binomial Model - A case of Interstate Highway in Washington State, USA (확률적 모수를 고려한 음이항모형에 의한 교통사고와 기하구조와의 관계 - 미국 워싱턴 주(州) 고속도로를 중심으로)

  • Park, Minho
    • 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.

Random Parameter Negative Binomial Models of Interstate Accident Frequencies on Interchange Segment by Interchange Type/Region (RPNB 모형을 이용한 고속도로 인터체인지 구간에서의 교통사고모형 - 인터체인지 형태별/지역별로)

  • Lee, Geun Hee;Park, Minho;Roh, Jeonghyun
    • International Journal of Highway Engineering
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    • v.16 no.5
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    • pp.133-142
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    • 2014
  • 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.

A Development of Traffic Accident Models at 4-legged Signalized Intersections using Random Parameter : A Case of Busan Metropolitan City (Random Parameter를 이용한 4지 신호교차로에서의 교통사고 예측모형 개발 : 부산광역시를 대상으로)

  • Park, Minho;Lee, Dongmin;Yoon, Chunjoo;Kim, Young Rok
    • International Journal of Highway Engineering
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    • v.17 no.6
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    • pp.65-73
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    • 2015
  • 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).

A Development of Traffic Accident Estimation Model by Random Parameter Negative Binomial Model: Focus on Multilane Rural Highway (확률모수를 이용한 교통사고예측모형 개발: 지방부 다차로 도로를 중심으로)

  • Lim, Joon Beom;Lee, Soo Beom;Kim, Joon-Ki;Kim, Jeong Hyun
    • Journal of Korean Society of Transportation
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    • v.32 no.6
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    • pp.662-674
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    • 2014
  • In this study, accident frequency prediction models were constructed by collecting variables such as geometric structures, safety facilities, traffic volume and weather conditions, land use, highway design-satisfaction criteria along 780km (4,372 sections) of 4 lane-highways over 8 areas. As for models, a fixed parameter model and a random parameter model were employed. In the random parameter model, some influences were reversed as the range was expressed based on specific probability in the case of no fixed coefficients. In the fixed parameter model, the influences of independent variables on accident frequency were interpreted by using one coefficient, but in the random parameter model, more various interpretations were took place. In particular, curve radius, securement of shoulder lane, vertical grade design criteria satisfaction showed both positive and negative influence, according to specific probability. This means that there could be a reverse effect depending on the behavioral characteristics of drivers and the characteristics of highway sections. Rather, they influence the increase of accident frequency through the all sections.