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

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

Yina Wu
Mohamed Abdel-Aty
Jaeyoung Lee

Low visibility conditions (fog) have significant impacts on crash risk. Previous studies have been point out that the crash severity and multi-vehicles involved crash risks are prone to increase during low visibility conditions. This study analyzed the changes of traffic characteristic and safety conditions at the fog duration. Both weather data and real-time traffic data were collected from airports at two regions in Florida. The airports provides the visibility conditions information, while the Regional Integrated Transportation Information System (RITIS) provides the traffic information. The traffic patterns analysis shows that the average 5-minute speed and the average 5-minute volume were prone to decrease during fog. In order to study changes of the crash risks under fog conditions, a “Crash Risk Increase Indicator (CRII)” was proposed to explore the differences of crash risk between fog and clear conditions. A binary logistic regression model was applied to link the CRII values with traffic flow characteristics. The results shows that the crash risks were tend to increase at ramp vicinities in fog conditions. Also, the average 5-minute volume during fog and the lane location are important factors for crash risk increase. Meanwhile, the results indicated the crash risks characteristics are different by different regions.



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