Predictor variables influencing merging speed change lane crash risk by interchange type in urban areas

• Main Authors: Synthia Tagar, Srinivas S. Pulugurtha
• Format: Article
• Language: English
• Published: Elsevier 2021-06-01
• Series: Transportation Research Interdisciplinary Perspectives
• Subjects: Crash; Risk; Speed change Lane; Merging; Multinomial Logistic Regression
• Online Access: http://www.sciencedirect.com/science/article/pii/S2590198221000828

The objective of this research is to model and examine the influence of predictor variables on merging speed change lane crash risk by interchange type in urban areas. Data for selected merging speed change lanes in Charlotte, North Carolina, USA, for five-years, were collected and used in this research. Multinomial logistic regression models were developed to examine the risk of getting involved in a fatal or injury crash and property damage only (PDO) crash by interchange type. The findings indicate that merging speed change lanes at multi-lane ramps are safer than single-lane ramps (odds ratio > 50). The ramp average daily traffic (ADT) and the speed difference between the freeway and the ramp influence merging speed change lane crash risk at a cloverleaf interchange while the freeway annual average daily traffic (AADT) and the speed change lane length influence merging speed change lane crash risk at a diamond interchange (odds ratio > 1.4). The risk of getting involved in a fatal-injury crash in the merging speed change lane increases (odds ratio > 1.6) if an upstream or downstream ramp is too close to the subject cloverleaf interchange ramp or if a downstream ramp is too close to the subject diamond interchange ramp. Contrarily, the upstream ramp distance does not influence the merging speed change lane PDO crash risk at a cloverleaf or diamond interchange. It can be concluded that predictor variables influencing the merging speed change lane crash severity risk are different for cloverleaf, diamond, and other interchange types.