The proportion of government funding allocated to state transportation budgets has declined as a result of budgetary constraints. This has necessitated a disciplined and efficient allocation of funds for various infrastructure development and rehabilitation projects. Annual average crash costs are typically estimated at the national level to inform resource allocation. These resources can then be used to implement measures to mitigate crashes and the associated costs through development of new technologies for continued improvement of road safety. This study specifically considers 10-year cost predictions associated with injuries, fatalities, and property damage resulting from crashes on highway US-16 in Wyoming. For each of these major crash types, cost predictions are generated from forecasts obtained from appropriately specified Seasonal Autoregressive Moving Average (SARIMA) models that identify important predictors, and which select a temporal correlation structure. The resulting cost projections can be used to inform the Wyoming Department of Transportation on the annual dollar amount associated with these major crash outcomes, along with identified risk factors that can then be used for planning and management of limited infrastructure development funds. This study of US-16 over the 10-year period identified winter months, driving under the influence of alcohol or drugs, heavy trucks, and a few road characteristics as risk factors, which resulted in a total average annual cost estimate of around 865 million dollars.
Predicted Average Annual Cost of Crashes on the US-16 Wyoming Downgrade Using Time Series Analysis and Forecasting
Int. J. ITS Res.
International Journal of Intelligent Transportation Systems Research ; 22 , 1 ; 53-68
2024-04-01
16 pages
Article (Journal)
Electronic Resource
English
ARIMA modeling , Crash cost predictions , Injuries , Fatalities , Property damage , Seasonality , Time series regression Engineering , Electrical Engineering , Automotive Engineering , Robotics and Automation , Computer Imaging, Vision, Pattern Recognition and Graphics , Civil Engineering , User Interfaces and Human Computer Interaction
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