Crash risk analysis during fog conditions using real-time traffic data

Area of Science:

• Traffic Engineering
• Transportation Safety
• Environmental Impacts on Transportation

Background:

• Fog significantly impacts road safety by altering traffic dynamics.
• Understanding these changes is crucial for developing effective traffic management strategies.

Purpose of the Study:

• To investigate traffic characteristic changes during fog.
• To quantify crash risks under foggy conditions using a novel indicator.
• To identify factors contributing to increased crash risks in fog.

Main Methods:

• Analysis of real-time traffic flow and weather data from Florida.
• Comparison of traffic patterns during fog vs. clear conditions.
• Development and application of a binary logistic regression model with a Crash Risk Increase Indicator (CRII).

Main Results:

• Fog leads to decreased average speeds and traffic volumes.
• The CRII effectively evaluates increased crash risk in fog.
• Ramp vicinities, higher traffic volumes, and specific lane positions (closer to median) are associated with increased crash risks in fog.

Conclusions:

• The CRII is a valuable tool for assessing fog-related crash risks.
• Identifying high-risk traffic statuses under fog can inform the implementation of Intelligent Transportation Systems (ITS).
• Targeted safety enhancements are needed for specific locations and traffic conditions during fog.