Traffic growth forecasting plays a pivotal role in achieving a variety of PennDOT goals and objectives, including transportation planning by PennDOT and its planning partners, air quality planning and conformity analyses, calculation of performance measures, and operation and management of the roadway transportation system for both passengers and freight. In this study, the Michael Baker Jr., Inc. Team (Baker Team) developed a traffic growth forecasting system that incorporates traffic data from PennDOT's Traffic Information System and socioeconomic data. In particular, the Baker Team: Finalized and prioritized goals and objectives for improved traffic growth forecasting in Pennsylvania and established criteria for evaluating candidate forecasting methods against PennDOT goals and objectives; Synthesized the state and the art research on forecasting traffic growth from a variety of literature and surveyed the state of practice among states and transportation planning organizations; Identified available data sources; including traffic information and socioeconomic data and forecasts and PennDOT's Traffic Information System, and recommended a consistent set of socioeconomic forecasts; Evaluated the candidate methods versus the PennDOT approved decision criteria and developed consensus on a short list of preferred traffic forecasting approaches for detailed study; Conducted a detailed study to test several models. Specifically, analyzed historical traffic growth patterns and historical socioeconomic growth patterns at different levels of geography, developed regression models based on historical traffic and socioeconomic growth, and evaluated the predictive power, validity, and reliability of statically models; and Identified a preferred traffic growth forecasting method for implementation.
Statistical Evaluation of Projected Traffic Growth
2004
172 pages
Report
Keine Angabe
Englisch
Transportation & Traffic Planning , Transportation , Traffic forecasting , Traffic growth , Statistical models , Evaluation , Traffic control , Traffic congestion , Transportation planning , Intermodal transportation systems , Traffic count , Performance measures , Socioeconomic data , Pennsylvania , Implementation , Rural areas , Urban areas
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