authorities have sought to address these concerns through measures such as speed
restrictions, requiring users to wear helmets, designated parking areas, and limiting
the number of scooters or operators allowed in the city - or even outright bans.
are not necessarily more dangerous than bicycles, but they are often perceived
as such, possibly because of their unfamiliarity and the behavior of their
riders,” explains Marco Dozza, Professor in Active Safety and Road-User
Behaviour at Chalmers University of Technology, and lead author of the new
benefits from established social norms, regulations, and infrastructure, the
same is not true for newer micromobility vehicles, such as e-scooters, Segways,
monowheels, electric skateboards and so on. The spread and usage of these
vehicles is only likely to increase in the near future; so, finding ways to safely
integrate them in the transport system is a vital and urgent challenge.”
understand what makes riding new micromobility vehicles unsafe and how that
compares to riding a more traditional bicycle, extensive data is needed.
Scooter companies already have access to huge amounts of data, because they track
every ride using GPS, but the quality of the data tends to only be useful for logistics
and mapping services, while providing insufficient information about safety.
Hospital admissions data and police reports may help appreciate the size of the
safety problem - but cannot explain why crashes happen.
missing is a framework for collecting and analysing data to understand what makes
rider behavior unsafe and causes the crashes. Now, Marco Dozza and colleagues
present a framework for exactly this.
different strategies: braking or steering away
researchers have outlined a process for data-collection in the field and
analysis, that is intended to be repeatable and adaptable for different
vehicles from identifying useful test-maneuvers, to measuring and analysing the
results of subsequent experiments. In their pilot study, the researchers
compared bikes and e-scooters directly, equipping them with measuring
instruments and testing the riders on various maneuvers, involving combinations
of braking - both planned, and in reaction to a random signal - and steering at
Watch a video of the research tests here
One of the most relevant findings of the new research was the fact that the
braking performance of a bicycle proved consistently superior to the one of an e-scooter - offering
faster deceleration and up to two times shorter stopping distance. In contrast,
the e-scooter performed better during the steering maneuvers, involving a
slalom through traffic cones - likely due to its shorter wheelbase and no need to
pedal. The participants were also questioned about their experience and
confirmed that braking felt more comfortable on the bicycle and steering more
so on the e-scooter.
vehicles showed distinct advantages and disadvantages through the different scenarios,”
explains Marco Dozza. “We can say that the best strategy for a cyclist and an e-scooterist
to avoid the same crash may be different - either braking or steering away.”
from these experiments may inform how the infrastructure might be designed to benefit
all riders - for example, a winding path might be easier for e-scooterists than
for cyclists, whereas a cyclist might find a narrower path, with low light less
challenging than an e-scooterist.
this experiment was small, and the data far from conclusive. However, this
pilot experiment demonstrates the potential for field data to describe rider
behavior and help understand the causes of crashes. With more data from a
larger sample of riders, we may reach a comprehensive picture of the rider behaviors
that makes riding an e-scooter safe. This information may help the authorities to
devise innovative safety measures and motivate their decisions to the public
with objective data” explains Marco Dozza.
application in smart future cities
researchers will now, in collaboration with Scandinavian scooter company Voi,
collect more field data to account for differences between riders and scenarios.
Eventually, findings such as the one presented here could teach future
automated vehicles and intelligent-transport-systems how to best interact with
scooterists and cyclists by anticipating their behavior. Other safety measures
that could be based on results from field-data analyses include dynamic geofencing - limiting
the scooters’ speed depending on how crowded an area is, or the time of the day
not involved in the research project outlined here in any form.
The article "A data-driven framework for the safe integration of
micro-mobility into the transport system: Comparing bicycles and e-scooters in
field trial" was published in the Journal of Safety Research and was written
by Marco Dozza, Alessio Violin, and Alexander Rasch.
The research was supported by several students from the Master Programme in Automotive Engineering, for instance via the Automotive Engineering Project which will be part of the new Master programme in Mobility Engineering at Chalmers. The Area of Advance Transport and Trafikverket sponsored this work.
For more information on scooters and micromobility vehicles in cities, contact:
Professor at Mechanics and Maritime Sciences, Division of Vehicle Safety
+46 31 772 3621
Text: Lovisa Håkansson and Joshua Worth