News from National Science Foundation

Do electric scooters reduce car use?

Research finds reduction in traffic congestion and carbon emissions with greater scooter use

Banning scooters may reduce sidewalk congestion and keep would-be riders and pedestrians safer, but it comes at a cost, according to a new study by Georgia Tech researchers.

In research examining the impact of Atlanta's 2019 ban on e-scooters and e-bikes in the city, researchers found that average commute times increased by about 10%.

The ban in Atlanta, one of many U.S. cities put in place in response to increased accidents and hospitalizations from micromobility devices, was in effect between 9 p.m. and 4 a.m. A moratorium during peak rush hour would cause even more congestion, the study's lead investigator, Omar Asensio, said. "These are fairly significant congestion effects that most travelers will feel as an unintended consequence of the safety regulation."

A paper from the study is published in Nature Energy. Asensio's work was supported through the U.S. National Science Foundation's CAREER program, which funds early-career faculty with the potential to serve as academic role models in research and education, and to lead advances in the mission of their department or organization.

The study uses high-resolution data from Uber Movement to understand how micromobility infrastructure such as e-bikes, e-scooters and bike lanes can reduce traffic congestion and carbon emissions in cities. Previous studies on micromobility relied on travel surveys, which can be unreliable and are subject to biases resulting from self-reported data, Asensio said.

When Atlanta banned scooters in 2019, it was done with a remote shutdown on all scooters within a certain perimeter, which ensured compliance across the city. Previous moratoriums in other places relied on people to choose to cooperate and follow the rules. "That created a great natural experiment, to be able to precisely measure the traffic times before and after this policy intervention and in doing so, test behavioral theories of mode substitution," Asensio said.

Asensio and his team received early access to the then-new Uber Movement Dataset, which gave them detailed information about commute times across the city that previously had to be collected by surveys.

Mary Feeney, a program director for NSF's Science of Science Program, said, "Asensio and his team are using newly available Big Data sources to tackle practical questions with real policy implications. Bringing the appropriate data and analytical approaches to these problems helps empower decision-makers to enact evidence-based policy."

Beyond Atlanta, the research has implications for American cities considering regulation and facilitation of e-scooters, e-bikes and other micromobility options.