Effect of the Weather Events on Travel Time Reliability and Crash Occurrence

On average, nearly 5,000 people are killed, and more than 418,000 people are injured in weather-related crashes every year in the United States (Ten-year averages from 2007 to 2016, FHWA). About 23% of the non-recurring road delay around the nation can be attributed to snow, ice, and fog. The precipitation, which occurs more frequently than the snow and fog leads to more traffic delay. In other words, weather events like precipitation, high winds, fog, and other extreme events like snowfall, flooding, hurricane, etc. disrupt the operational performance of roads. They result in a reduction in road capacity, a reduction in travel speed, and a decrease in safety performance. The magnitude of the effect on operational performance measures (for example, travel time and travel time reliability) and safety (crash occurrence) varies with the type of weather event and road characteristics of the subject link and adjacent links. Ensuring higher levels of travel time reliability and safety are critical for efficient transportation system management. Therefore, there is a need to analyze the travel time fluctuations (deviations from normal traffic conditions) and crashes during weather events. Besides, understanding the effect on travel time reliability by the type of weather event and its duration, identifying the most affected links is important to proactively plan and disseminate the effect and influence travel patterns over space and time. A key challenge to achieving this objective is the integration of the weather-related information and traffic conditions during the weather event from disparate data sources. For example, Integrated Surface Database (ISD) includes numerous parameters such as wind speed and direction, wind gust, temperature, dew point, cloud data, sea level pressure, altimeter setting, station pressure, present weather, visibility, precipitation amounts for various periods, snow depth, and various other elements as observed at over 230 active stations in and near North Carolina. Advancements in data collection technologies made it possible to collect and archive real-world travel time data at the link-level by public and private agencies. Integrating the weather events information, crashes, and the travel time by time-of-the-day (TOD) and day-of-the-week (DOW) will serve as a valuable database for assessing and modeling the effect of weather events. Further, analyzing the historical pattern of travel times, computing and comparing travel time reliability measures and crash frequency/severity before, during, and after the weather event will help quantify and understand the spatiotemporal effects of such events on road traffic.

    Language

    • English

    Project

    • Status: Active
    • Funding: $75000
    • Contract Numbers:

      69A3551747127

    • Sponsor Organizations:

      Office of the Assistant Secretary for Research and Technology

      University Transportation Centers Program
      Department of Transportation
      Washington, DC  United States  20590
    • Managing Organizations:

      Office of the Assistant Secretary for Research and Technology

      University Transportation Centers Program
      Department of Transportation
      Washington, DC  United States  20590
    • Performing Organizations:

      Mineta Consortium for Transportation Mobility

      San Jose State University
      San Jose, CA  United States  95112
    • Principal Investigators:

      Pulugurtha, Srinivas

    • Start Date: 20200601
    • Expected Completion Date: 20211231
    • Actual Completion Date: 0
    • USDOT Program: University Transportation Centers

    Subject/Index Terms

    • TRT Terms: Crash rates; Forecasting
    • Subject Areas: Data and Information Technology; Highways; Planning and Forecasting; Safety and Human Factors; Vehicles and Equipment;

    Filing Info

    • Accession Number: 01784491
    • Record Type: Research project
    • Source Agency: Mineta Consortium for Transportation Mobility
    • Contract Numbers: 69A3551747127
    • Files: UTC, RIP
    • Created Date: Oct 8 2021 6:49PM