title: Modeling left-turn crash occurrence at signalized intersections by conflicting patterns.
abstract: In order to better understand the underlying crash mechanisms, left-turn crashes occurring at 197 four-legged signalized intersections over 6 years were classified into nine patterns based on vehicle maneuvers and then were assigned to intersection approaches. Crash frequency of each pattern was modeled at the approach level by mainly using Generalized Estimating Equations (GEE) with the Negative Binomial as the link function to account for the correlation among the crash data. GEE with a binomial logit link function was also applied for patterns with fewer crashes. The Cumulative Residuals test shows that, for correlated left-turn crashes, GEE models usually outperformed basic Negative Binomial models. The estimation results show that there are obvious differences in the factors that cause the occurrence of different left-turn collision patterns. For example, for each pattern, the traffic flows to which the colliding vehicles belong are identified to be significant. The width of the crossing distance (represented by the number of through lanes on the opposing approach of the left-turning traffic) is associated with more left-turn traffic colliding with opposing through traffic (Pattern 5), but with less left-turning traffic colliding with near-side crossing through traffic (Pattern 8). The safety effectiveness of the left-turning signal is not consistent for different crash patterns; "protected" phasing is correlated with fewer Pattern 5 crashes, but with more Pattern 8 crashes. The study indicates that in order to develop efficient countermeasures for left-turn crashes and improve safety at signalized intersections, left-turn crashes should be considered in different patterns.
authors.affiliation: Department of Civil & Environmental Engineering, University of Central Florida, Orlando, FL 32816-2450, United States.
authors.forename: Xuesong
authors.initials: X
authors.lastname: Wang
authors.forename: Mohamed
authors.initials: M
authors.lastname: Abdel-Aty
mesh_terms: D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D000465:Algorithms; D001334:Automobile Driving / Q000523:psychology*; D016010:Binomial Distribution; D004779:Environment Design; D005431:Florida; D006801:Humans; D016014:Linear Models; D008960:Models, Psychological; D010364:Pattern Recognition, Visual; D012307:Risk Factors