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The contents of this report reflect the views of the author(s), who is responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the Virginia Department of Transportation, the Commonwealth Transportation Board, or the Federal Highway Administration. This report does not constitute a standard, specification, or regulation. Any inclusion of manufacturer names, trade names, or trademarks is for identification purposes only and is not to be considered an endorsement.


Feasibility of Adapting VisionEval for Scenario Planning
John S. Miller, Ph.D., P.E., Dan F.B. Flynn, Ph.D., Eric Englin, Jeremy Raw, P.E., Sayed H. Adel, and Lance E. Dougald
Lance E. Dougald
Lance E. Dougald
John S. Miller
John S. Miller
Year: 2019
VTRC No.: 22-R21

Transportation investment decisions require consideration of uncontrolled events (e.g., changes in family size, vehicle technology, population, fuel prices, or societal norms such as telecommuting) along with possible policy responses to achieve desired goals.  Although the possibility of these multiple alternative futures suggests one should explicitly consider them when making investment decisions, using more detailed models to support scenario planning is hampered by extensive data requirements and difficulty evaluating many different scenarios.  One tool that has the potential to fill this gap is the VisionEval platform, which has less detail than an operational model with a transportation network but more detail than sketch approaches. VisionEval is an open-source scenario planning platform under development as part of a Federal Highway Administration–led pooled fund study in which Virginia is participating.

The purpose of this study was to determine the benefits, staff time requirements, and feasibility of applying VisionEval to explore 43 scenarios of interest to VDOT planning staff and planning partners with respect to their impact on vehicle miles traveled and carbon dioxide equivalent emissions.  The primary benefit of this scenario planning tool is the rapid identification of which areas merit greater examination; in this case study region, telecommuting, truck electrification, and household vehicle electrification have relatively large potential impacts on emissions(on the order of 13%, 6%, and 4%, respectively) such that these areas merit greater study.  By contrast, changes in household size, population, transit vehicle technology, and increased availability of carsharing vehicles had lesser impacts.   Presently, VisionEval appears deployable with about 500 hours of staff time for a case study area with three localities,1.43 million people, and 712 transportation analysis zones. 

The tool addresses two key obstacles to enabling scenario planning in the VDOT environment: multiple potential inputs and substantial data requirements, although a limitation is that some scenarios, such as those relating to the density of pedestrian-friendly intersections, are not feasible with the current iteration of VisionEval.  The study thus recommends the use of this platform for scenarios where sensitivity analyses how it is appropriate.  The study further recommends changes to this platform in order to address these limitations.  Two action items for putting these two recommendations into practice are given in the Implementation subsection of this report.