Lead Presenter Biography

Mark is a Transportation Modeling Manager at Gannett Fleming, based in their Baltimore, Maryland office. With a tenure of 23 years at Gannett Fleming, Mark has spent the past 12 years providing on-site technical support at the Maryland State Highway Administration. In this role, he manages various activities related to the Maryland Statewide Transportation Model. Prior to joining Gannett Fleming, Mark served as a Senior Transportation Engineer at the Metropolitan Washington Council of Governments for 9 years.

Co-Authors

Presentation Description

In the Spring of 2020, when COVID-19 began to spread in the United States, a series of restrictions were put into place in an attempt to curtail the spread. These restrictions varied from jurisdiction to jurisdiction, but generally included shutting down locations used for recreational purposes, limiting in-person work to essential services, and closing classrooms to in-person instruction. In response, a number of strategies to cope with these restrictions were employed by the public such as increased work from home, remote learning, and a greater reliance on e-commerce. As a result, Maryland experienced a 60% reduction in traffic during that March and April from pre-pandemic levels. As restrictions eased, traffic increased. By the end of the Summer of 2020, traffic levels were sustaining at 15% to 20% below pre-pandemic levels. The sustained nature of these lower levels of traffic at the time prompted many to question whether the societal impacts of COVID-19 (greater adoption of e-commerce, employers’ willingness to accept work from home, and remote delivery of school instruction) would persist longer than the pandemic and have long term implications for transportation planning. In response, the Travel Forecasting and Analysis Division (TFAD) of the Maryland State Highway Administration (SHA) undertook a scenario-based analysis designed to understand the range of potential long-term effects and what, if any, impacts to Maryland’s transportation program could be discerned. Having successfully done so, TFAD has begun to employ the same methodology for dealing with other long-term uncertainties such as the adoption of CAV technology as well as project-level traffic forecasting.
This paper will discuss the approach used by TFAD to deal with uncertain futures. Emphasis will be placed on the strong reliance of observed data and the bounding of uncertain futures within realistic probabilities. The presentation will also explore the interaction of quantitative analysis with qualitative approaches to uncertainty such as the use of Delphi methods to generate a consensus. The Maryland Statewide Transportation Model (MSTM) was a key component of the scenario testing process. The presentation will address the suitability of trip-based models for this purpose as well as why the MSTM was preferred over other scenario analysis tools available. The paper will discuss the implications of the findings for Maryland’s transportation program. Despite concerns by some that the long-term impacts of COVID-19 could result in levels of future traffic low enough to significantly reduce the need to invest in transportation infrastructure, this study shows that in all likely futures, continued investment in transportation infrastructure and long-range planning will be crucial to serving the needs of the people of Maryland. Finally, the presentation will show how the same approach is being used to inform Maryland’s CAV planning initiatives as well as addressing uncertainties in traffic forecasting for US 15. 

Presentation File