Forecasting Congestion Scenarios using a Travel Time Index (August 16, 2017)


Date: August 16, 2017

Description:  This Webinar will describe the results of the FHWA research project "Guide to Developing Congestion Scenarios for Long Range Plans using Travel Demand Models." The webinar will describe a major problem faced by long range travel demand modelers - that the long range future may be significantly disrupted by social, economic, and technological changes and existing models lack methods to reasonably forecast such futures. Although it is relatively simply to assert changes into existing travel demand model structures - it is difficult to assess the forecasted outcomes of such assertions - such as major reductions to trip tables, changes in trip length or friction factor curves, wholesale shifts in modality or auto occupancy, and land use and urban form changes. A method proposed is the use of baseline calibrated Travel Time Indices on a regional or corridor basis, as a systematic means of putting boundaries on asserted changes to long range travel demand models. An example of the method will be described using a major metropolitan area trip based model.

Presenter: Mr. Williams has 30 years of experience as a professional transportation planner, including over 10 years in university research, 5 years in the public sector, and 15 years in consulting. Mr. Williams has an AICP certification. Throughout his career, Mr. Williams has focused in the areas of travel modeling and travel forecasting with an emphasis on supporting excellence in transportation planning. His background is diverse, including travel modeling and GIS, demographic forecasting, data collection, systems design, transportation planning, policy planning, training, teaching, project management, and business management. He has developed several regional, sub-regional, and statewide travel demand and demographic models, and tailored many models for specific use in transportation plans and studies. Mr. Williams is currently a Research Scientist at the Texas A&M Transportation Institute's Austin, Texas, office location. In that capacity he is focusing on research in transportation forecasting and modeling with an emphasis on automated and connected transportation.