  The popularity and proliferation of electric scooters (e-scooters) as a
micromobility solution in our cities and urban communities has been rapidly
rising. Rent-by-the-minute pricing and a healthy competition between
micromobility service providers is also benefiting riders with low trip costs.
However, an unprepared urban infrastructure, combined with uncertain operation
policies and poor regulation enforcement, has resulted in e-scooter riders
encroaching public spaces meant for pedestrians, thus causing significant
safety concerns both for themselves and the pedestrians. As a consequence, it
has become critical to understand the current state of pedestrian safety in our
urban communities vis-\`{a}-vis e-scooter services, identify factors that
impact pedestrian safety due to such services, and determine how to support
pedestrian safety going forward. Unfortunately, to date there have been no
realistic, data-driven efforts within the research community that address these
issues. In this work, we conduct a field study to empirically investigate
crowd-sensed encounter data between e-scooters and pedestrian participants on
two urban university campuses over a three-month period. We also analyze
encounter statistics and mobility trends that could identify potentially unsafe
spatio-temporal zones for pedestrians. This first-of-its-kind work provides a
preliminary blueprint on how crowd-sensed micromobility data can enable
safety-related studies in urban communities.
