Temporal and spatial analyses of rear-end crashes at signalized intersections

Area of Science:

• Traffic Engineering
• Transportation Safety
• Statistical Modeling

Background:

• Rear-end collisions are a common type of traffic accident, particularly at signalized intersections.
• Understanding the factors contributing to rear-end crash frequency is crucial for improving road safety.

Purpose of the Study:

• To model rear-end crash frequencies at signalized intersections using statistical methods.
• To identify intersection-specific variables that significantly influence the occurrence of rear-end crashes.

Main Methods:

• Generalized Estimating Equations (GEE) with a negative binomial link function were employed.
• Longitudinal data from 208 intersections over 3 years and spatially correlated data from 476 intersections in Florida were analyzed.

Main Results:

• High correlations were found between longitudinal and spatially correlated rear-end crashes.
• Factors such as heavy traffic, more turn lanes, higher speed limits, and urban population density correlate with increased rear-end crash frequency.
• Intersections with fewer legs, dedicated turn lanes, medians, and greater signal spacing showed lower rear-end crash rates.

Conclusions:

• Specific intersection characteristics significantly impact rear-end crash frequencies.
• The study provides valuable insights for traffic engineers and urban planners to design safer signalized intersections and mitigate rear-end collisions.