Across the world, mobility fell dramatically as a result of the lockdown measures introduced by governments to slow the spread of covid-19. This resulted in significant improvements in air pollution as traffic plummeted. New research from Vanderbilt University explores what might happen to traffic levels as the pandemic continues.
The research looks at traffic levels both during and after the pandemic, before using mathematical modelling to predict changes in traffic in the months ahead.
“We put together the models in about ten days,” the researchers say. “Our team worked around the clock to wrangle the data, build the tools, and analyze the results. After connecting on one of our daily research calls and discovering the potential issue, we knew we had to switch gears and figure out which cities are most at risk.”
Travel patterns
The research used publicly available data to plot both the number of cars on the road, together with the average travel time. This data was then used to gauge the road capacity of each city and the “empty-road travel time”, which the researchers define as the average time commuters would experience on practically empty roads.
The researchers were able to compare the capacity for each city, together with the average travel time, and from this plotted four scenarios for traffic in the aftermath of covid:
- 25% of those who would ordinarily take public transport drive instead
- 50% of those who would ordinarily take public transport drive instead
- 75% of those who would ordinarily take public transport drive instead
- And 100% of those who would ordinarily take public transport drive instead
“Thanks to the models for each city we see that generally speaking, the increases in car traffic are more severe for larger metro areas,” the researchers say. “However, keeping transit systems open is critical for staving off the highest traffic risks, and a rebound of up to an additional 10 minutes in each direction is still highly possible in high-transit cities.”
As part of the research, a tool was developed that allows the public to assess the potential for extreme traffic in their own city. Users adjust the sliders for a range of parameters, such as the unemployment rate, number of remote workers, and so on.
While it’s debatable how many people would have access to that kind of information, it’s nonetheless a nice example of the kind of data being made available to guide both official and public decision making.
“Each city has unique circumstances for an increase in traffic,” the researchers conclude. “But it is still likely that a significant switch in the mode of transport could add up to hundreds of thousands of hours of additional travel time each day.”
