1663322 - Modeling travel time reliability for non-interstate national highway system routes

Abstract: The objective of this study was to investigate travel time reliability on non-interstate National Highway System (NHS) arterials, focusing particularly on identifying the influencing factors of travel time reliability performance and formulating methods for estimating this reliability at a planning level. The necessity of this study stems from the escalating integration of travel time reliability measures into system planning and performance measurement by transportation agencies. This trend underscores the need for accurate predictions and realistic performance target setting with a data-driven approach. A review of the literature reveals a predominance of studies focusing on interstate highways, highlighting a research gap with respect to non-interstate highways, which this study has sought to address.
In this investigation, our attention was specifically directed towards the non-interstate NHS arterials maintained by the Virginia Department of Transportation (VDOT), approximately 5,700 directional miles and representing 77% of all non-interstate NHS arterials within the commonwealth of Virginia. We proposed and implemented a data-driven target-setting process, designed to provide an accurate reflection of both current and predicted future conditions, thereby producing realistic targets and enabling progressive tracking.
Data for this study was sourced from a variety of databases, including probe speed data, traffic incident and work zone information, traffic control device records, traffic volumes, roadway geometry specifications, urban and rural designations, and weather data. Recognizing the intricate nature of arterial travel times, our study also embarked on an exploration of the temporal and spatial variations of travel time reliability measures, correlating these changes with a wide range of variables. We found traffic signals to have a significant impact on travel time distribution and observed a strong correlation with variables such as Average Annual Daily Traffic (AADT) and urban-rural designation. Accordingly, we delved into the compound effect of multiple factors on travel time distributions.
Supporting our analysis were a suite of visualizations and a clustering analysis, the latter grouping roadway segments based on homogeneity in travel time distributions. The findings of this research, therefore, represent a significant step towards a more comprehensive understanding of travel time reliability on non-interstate highways.