Trip Generation and Traffic Prediction: Evaluating Alternative Traffic Prediction Methods for Traffic Impact Analysis
Traffic impact analysis (TIA) forecasts how a proposed development will affect the surrounding transportation system and what improvements, if any, are needed to improve safety and efficiency. In addition to trips generated by the proposed development (typically based on rates published by the Institute of Transportation Engineers [ITE], a TIA will include “background traffic” which is traffic on the roadway generated from other sources. The assumption is that background traffic growth is not driven by the proposed development, nor by other parcels approved but not yet built within the study area. The purpose of this research is twofold: (1) to determine the extent to which this assumption is valid and (2) if the assumption is not valid, to identify best practices to account for this. This research will thus (1) review practices from other states regarding ways to combine background traffic growth and site-specific trip generation in the TIA process; (2) compare forecast and observed trip generation for a selected set of developments; and (3) conduct an additional case study to compare the traditional approach of doing a TIA (based on ITE rates) and an approach based on a travel demand model. Lessons learned from this effort may inform Virginia Department of Transportation (VDOT)’s Traffic Impact Analysis guidelines. This research need tied with another for being the top-ranked research need by the Transportation Planning Research Advisory Committee (TPRAC).
Language
- English
Project
- Status: Active
- Funding: $17,964.00
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Contract Numbers:
129950
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Sponsor Organizations:
Virginia Transportation Research Council
530 Edgemont Road
Charlottesville, VA United States 22903 -
Managing Organizations:
Virginia Transportation Research Council
530 Edgemont Road
Charlottesville, VA United States 22903 -
Project Managers:
Miller, John
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Performing Organizations:
School of Engineering
CEIE Dept., MSN-6C1
Faifax, VA United States 22030 -
Principal Investigators:
Zhu, Shanjiang
- Start Date: 20260706
- Expected Completion Date: 20280131
- Actual Completion Date: 0
Subject/Index Terms
- TRT Terms: Predictive models; Traffic forecasting; Travel demand; Trip generation
- Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting;
Filing Info
- Accession Number: 01994949
- Record Type: Research project
- Source Agency: Virginia Department of Transportation
- Contract Numbers: 129950
- Files: RIP, STATEDOT
- Created Date: Jul 2 2026 11:02AM