Random Parameter Negative Binomial Model Research Articles

Safety impacts of signal-warning flashers and speed control at high-speed signalized intersections

For many years, to reduce the crash frequency and severity at high-speed signalized intersections, warning flashers have been used to alert drivers of potential traffic-signal changes. Recently, more aggressive countermeasures at such intersections include a speed-limit reduction in addition to warning flashers. While such speed-control strategies have the potential to further improve the crash-mitigation effectiveness of warning flashers, a rigorous statistical analysis of crash data from such intersections has not been undertaken to date. This paper uses 10-year crash data from 28 intersections in Nebraska (all with intersection approaches having signal-warning flashers; some with no speed-limit reduction, and the others with either 5mi/h or 10mi/h reduction in speed limit) to estimate a random parameters negative binomial model of crash frequency and a nested logit model of crash-injury severity. The estimation findings show that, while a wide variety of factors significantly influence the frequency and severity of crashes, the effect of the 5mi/h speed-limit reduction is ambiguous—decreasing the frequency of crashes on some intersection approaches and increasing it on others, and decreasing some crash-injury severities and increasing others. In contrast, the 10mi/h reduction in speed limit unambiguously decreased both the frequency and injury-severity of crashes. It is speculated that, in the presence of potentially heterogeneous driver responses to decreased speed limits, the smaller distances covered during reaction time at lower speeds (allowing a higher likelihood of crash avoidance) and the reduced energy of crashes associated with lower speed limits are not necessarily sufficient to unambiguously decrease the frequency and severity of crashes when the speed-limit reduction is just 5mi/h. However, they are sufficient to unambiguously decrease the frequency and severity of crashes when the speed-limit reduction is 10mi/h. Based on this research, speed-limit reductions in conjunction with signal-warning flashers appear to be an effective safety countermeasure, but only clearly so if the speed-limit reduction is at least 10mi/h.

Relationship between Interstate Highway Accidents and Heterogeneous Geometrics by Random Parameter Negative Binomial Model - A case of Interstate Highway in Washington State, USA

이 연구는 확률적 모수를 고려한 음이항회귀분석을 이용하여 고속도로에서의 사고와 기하구조와의 관계를 파악하는데 목적이 있다. 고속도로에서의 기하구조는 모든 구간에 동일한 설계요소가 적용되기에는 현실적으로 불가능함에도 불구하고, 지금까지의 연구에서는 모형을 통해 도출되는 계수값이 구간에 설치된 기하구조의 특성에 관계없이 항상 고정된 값으로 추정되어왔다. 고정된 값을 이용한 일반적인 음이항모형은 시간적 변화 또는 각 대상구간이 가지고 있는 고유한 특성에 따른 변화를 통합하여 설명하지 못한다는 단점이 있으며, 이로 인해 추정된 계수의 표준오차가 과소추정되어 t-값이 부풀려지게 되며, 그 결과 모형의 설명력이 떨어지게 된다. 따라서, 이 연구에서는 워싱턴 주에 위치하고 있는 7개의 고속도로에서 발생한 9년동안의 사고자료 및 기하구조자료를 이용하여 구간별로 상이한 기하구조가 사고에 미치는 영향을 알아보고자 한다. 총 16개의 기하구조 관련 변수가 모형 도출에 이용되었으며, 기존의 음이항모형과의 비교를 통해 이 연구에서 제시하는 모형이 교통사고와 기하구조와의 관계파악에 더욱 적합함을 보이고자 한다. 그리고, 각 변수의 한계효용 및 탄력성 분석을 통해 이질성을 가지는 기하구조가 사고에 미치는 영향을 제시하고자 한다. 이는 향후 기하구조 관련 정책수립에 도움이 될 것으로 판단된다. 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.

Model of Relationship between Interstate Crash Occurrence and Geometrics

This paper proposes the use of a random parameter negative binomial (NB) model for the analysis of crash counts. With the use of a 9-year, continuous panel of histories of total crash frequencies on Interstate highways in Washington State for 1999 to 2007, a random parameter NB model was estimated to account for parameter correlations, panel effects that contributed to intrasegment temporal variations, and between-site effects. Interstate geometric variables, such as lighting type proportions by length, shoulder width proportions, lane cross-section proportions, and curvature variables, were used in the model specification. Curvature variables included the number of horizontal curves in a segment, the number of vertical curves in a segment, the shortest horizontal curve in a segment length, the largest degree of curvature in a segment, the smallest vertical curve gradient, and the largest vertical curve gradient in a segment. Segments were analyzed at the interchange and the noninterchange levels. A total of 1,153 directional segments of the seven Washington State Inter-states were analyzed. The analysis yielded a statistical model of crash frequency on the basis of 10,377 observations. Several curvature effects were found to be random, which meant that they varied from segment to segment. Although, for example, the numbers of horizontal and vertical curves in a segment were fixed-parameter effects, the largest degree of curvature, as well as the smallest and largest vertical curve gradient variables, were random parameters. The logarithm of average daily travel and the median and point lighting proportions were also found to be random parameters. These results suggested that segment-specific insights into crash frequency occurrence could be improved for appropriate design policy and prioritization.