Best Practices for Road Weather Management Version 2.0
Title:
Assessing Weather, Environment, and Loop Data for Real-Time Freeway Incident Prediction
Abstract:
This paper evaluated weather, environment, and loop data conditions that are promising indicators for real-time freeway incident prediction. First, the ability to predict the likelihood of selected incident types using weather and environment data was examined. Then, loop detector data were analyzed for conditions useful for in-lane incident prediction. Non-nested and nested multinomial logit models were estimated using the data from the selected freeways in Austin, Texas. The estimation results revealed that factors such as visibility, time of day, and lighting condition are significant determinants of incident type while five-minute average occupancy and coefficient of variation in speed are strong predictors of in-lane freeway accidents.
Source(s):
85th Transportation Research Board (TRB) Annual Meeting, Texas Transportation Institute. For an electronic copy of this resource, please direct your request to WeatherFeedback@dot.gov.
Date: 2006
Author:
Songchitruksa, Balke
Keywords:
Adverse weather
Visibility
Traffic management
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