Abstract

The Indiana Department of Transportation (INDOT) adopted the Maintenance Decision Support System (MDSS) for user-defined plowing segments in the winter of 2008–2009. Since then, many new data sources, including connected vehicle data, enhanced weather data, and fleet telematics have been integrated into INDOT winter operations activities. The objective of this study was to use these new data sources to conduct a systematic evaluation of the robustness of the MDSS forecasts. During the 2023–2024 winter season, 26 unique MDSS forecast data attributes were collected at 0-, 1-, 3-, 6-, 12-, and 23-hour intervals from the observed storm time for 6 roadway segments during 13 individual storms. In total, over 888,000 MDSS data points were archived for this evaluation. This study developed novel visualizations to compare MDSS forecasts to multiple other independent data sources, including connected vehicle data, National Oceanic and Atmospheric Administration (NOAA) weather data, road friction data and snowplow telematics. Three Indiana storms, with varying characteristics and severity, were analyzed in detailed case studies. Those storms occurred on January 6th, 2024, January 13th, 2024, and February 16th, 2024. Incorporating these visualizations into winter weather after-action reports increased the robustness of post-storm performance analysis and allowed road weather stakeholders to better understand the capabilities of MDSS. The results of this analysis will provide a framework for future MDSS evaluations and implementations and training tools for winter operation stakeholders in Indiana and beyond.

Keywords

weather forecasting, winter weather, connected vehicle data, after-action report

Report Number

FHWA/IN/JTRP-2024/31

SPR Number

4704

Performing Organization

Joint Transportation Research Program

Publisher Place

West Lafayette, Indiana

Date of Version

2024

DOI

10.5703/1288284317805

Additional Files
SPR-4704 Technical Summary.pdf (1121 kB)
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