Multivariate Poisson-lognormal model for analysis of crashes on urban signalized intersections approach. Issue 3 (4th May 2018)

• Record Type: Journal Article
• Authors: Zhao, Mo; Liu, Chenhui; Li, Wei; Sharma, Anuj
• Is Part Of: Journal of transportation safety & security. Volume 10:Issue 3(2018)
• Page Start: 251
• Page End: 265
• Publication Date: 2018-05-04
• Subjects: Multivariate Poisson log-normal -- signalized intersection -- crash analysis -- traffic safety -- intersection approach; Transportation -- United States -- Safety measures -- Periodicals; Transportation -- Security measures -- United States -- Periodicals; Transportation -- Safety measures; Transportation -- Security measures; United States; Periodicals; 353.9805
• DOI: 10.1080/19439962.2017.1323059
• Languages: English
• ISSNs: 1943-9970

Abstract

ABSTRACT: Many studies investigate contributing factors of intersection crashes, but very limited studies focus on cashes on the intersection approach. It is important to address the characteristics of intersection-approach crashes to better understand intersection safety. This article analyzes the crashes on signalized intersection approach on urban arterials with a focus on traffic and geometric elements. The intersection approach is defined as the segment between stop bar and the location 200 ft upstream from the stop bar. The multivariate Poisson log-normal (MVPLN) model is used to model crash counts by severity. Ten-year crash data collected from 643 signalized intersections in Nebraska are used for analysis. One-way road is found to be negatively related to all three severity levels (light crash, moderate crash, and severe crash) of crashes. Compared to the 12 ft lane width, narrower lane widths generally lead to fewer crashes. The intersection approaches on urban arterials are expected to have more crashes than collector roads. The numbers of right-turn, left-turn, and through lanes, as well as the annual average daily traffic on the intersection approach and its crossing approach are statistically significant factors increasing crash frequency. The MVPLN model is compared to univariate and zero-inflated Poisson models. The results reveal that the MVPLN model provides a superior fit over the univariate Poisson model.