4.6 Article

Impacts of micromobility on car displacement with evidence from a natural experiment and geofencing policy

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NATURE ENERGY
卷 7, 期 11, 页码 1100-1108

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NATURE PORTFOLIO
DOI: 10.1038/s41560-022-01135-1

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资金

  1. National Science Foundation [1945532, 2125399]
  2. IDEaS Data Science Fellowship

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The rapid growth of the global micromobility market will lead to increased electrification in urban transportation, however, the effects of micromobility adoption on traffic congestion and sustainability are still unclear. Using mobile geofencing and high-resolution data, a study examined the impact of banning electric scooters during evening hours and found that micromobility users might substitute scooters for cars. This research is important for understanding the implications of micromobility on urban transportation and the environment.
Micromobility, such as electric scooters and electric bikes-an estimated US$300 billion global market by 2030-will accelerate electrification efforts and fundamentally change urban mobility patterns. However, the impacts of micromobility adoption on traffic congestion and sustainability remain unclear. Here we leverage advances in mobile geofencing and high-resolution data to study the effects of a policy intervention, which unexpectedly banned the use of scooters during evening hours with remote shutdown, guaranteeing near perfect compliance. We test theories of habit discontinuity to provide statistical identification for whether micromobility users substitute scooters for cars. Evidence from a natural experiment in a major US city shows increases in travel time of 9-11% for daily commuting and 37% for large events. Given the growing popularity of restrictions on the use of micromobility devices globally, cities should expect to see trade-offs between micromobility restrictions designed to promote public safety and increased emissions associated with heightened congestion. Micromobility solutions such as e-bikes or e-scooters are rapidly changing urban travel patterns and behaviours. Asensio et al. use travel data from the city of Atlanta, which introduced a No Ride Zone, and uncover trade-offs between public safety policy and traffic congestion.

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