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https://www.nationalacademies.org/trb/events

Experimental Approaches for Integrating External Factors into Pathway for Planning (P4P) Traffic Volume Forecasting

Traffic volume forecasts are critical for effective transportation planning, helping to assess future roadway demand and allocate resources efficiently. Virginia’s Department of Transportation (VDOT) uses the Pathway for Planning (P4P) web-based application to provide historical and forecasted traffic volume data. However, P4P’s current trend-based approach, which relies on linear regression, may either under- or over-predict future traffic volumes due to the lack of consideration for socioeconomic changes. The purpose of this study is to evaluate alternative methods for forecasting annual traffic volumes by incorporating external socioeconomic factors such as population growth, employment trends, and a forecast change in personal income from reliable sources. This research focuses on annual average daily traffic volumes (AADT) only and excludes daily, seasonal, and project induced traffic variations. The research will include a literature review, a survey focused on segment-level traffic forecasting, an exploration of available external data, and the development of a pilot forecast model in VDOT Fredericksburg District as a case study. Statistical analyses will be conducted to ensure region-specific predictions and to evaluate the effectiveness of alternative models for enhancing the P4P platform. The goal of this work is to incorporate socioeconomic factors into what are currently trend-based traffic volume forecasts. If this modification improves forecast accuracy, it may also improve infrastructure planning and policy decisions across Virginia.