The COVID-19 pandemic, besides its human life costs, has locked down cities and has halted urban activities and therefore obviates traffic congestion and emission. With reopening the economy in progress, traffic congestion is slowly coming back to the urban areas, it is becoming evident that driving volume might increase after the full reopening phase.
A paper based on joint work between Cornell and New York University has been accepted for publication in the leading transportation journal, “Transportation Research Part A: Policy and Practice”.
The paper, “Mobility in Post-Pandemic Economic Reopening under Social Distancing Guidelines: Congestion, Emissions, and Contact Exposure in Public Transit”, was written by the research team of H. Oliver Gao, Director of the Systems Engineering Program and the Howard Simpson Professor in the School of Civil and Environmental Engineering, along with Kaan Ozbay and Joseph Chow ’00 M.Eng. ‘01 from NYU’s Tandon School of Engineering and Center for Urban Science and Progress.
“COVID-19 has raised new challenges for transportation in the post-pandemic era,” the paper states. “The social distancing requirement, with the aim of reducing contact risk in public transit, could exacerbate traffic congestion and emissions.”
The authors propose a simulation tool to evaluate the trade-offs between traffic congestion, emissions and policies impacting travel behavior to mitigate the spread of COVID-19 including social distancing and working from home. Open-source agent-based simulation models are used to evaluate the transportation system usage for the case study of New York City.
Finally, system-wide contact exposure on the subway is estimated from the traffic simulation output. The social distancing requirement in public transit is found to be effective in reducing contact exposure, but it has negative congestion and emission impacts on Manhattan and neighborhoods at transit and commercial hubs. While telework can reduce congestion and emissions citywide, in Manhattan the negative impacts are higher due to behavioral inertia and social distancing. The findings suggest that contact exposure to COVID-19 on subways is relatively low, especially if social distancing practices are followed.
“The proposed integrated traffic simulation models and air quality estimation model can help policymakers evaluate the impact of policies on traffic congestion and emissions as well as identifying hot spots, both temporally and spatially,” the authors say.