Those E-Scooters Might Not Be as Dangerous as You Think

A civil engineer looks at traffic data to improve road safety

Photo: Brian Bumby/Getty Images

E-scooters continue to intrigue us. They’re new and unfamiliar, and they’re also everywhere. Perhaps this explains the sensationalized media coverage on e-scooters, much of which is driven by anecdotes of accidents. But an army of researchers has been itching to unveil empirical evidence to augment the e-scooter dialogue.

I am a soldier in this army.

At the center of the e-scooter controversy is safety. Let’s look at some recent headlines:

Now, those headlines have to instill some fear. But road safety is not a simple matter that can be summarized in a headline. This is especially true for e-scooters because we don’t know much about them yet.

I started my PhD journey with a mission of answering the question “Are e-scooters safe?” Fast forward a year, and I am now convinced that the more appropriate question may be “Are our streets safe?” Let me tell you why.

The little we know about e-scooters

Katie Harmon and Laura Sandt at the University of North Carolina Highway Safety Research Center have been tracking fatal crashes involving e-scooters in the U.S. since late 2018. Of the 18 fatal crashes in 2019, 16 of them involved e-scooter riders killed from being struck by motor vehicles. One e-scooter fatality was a result of an e-scooter rider colliding with another rider. The remaining fatality resulted from a single-vehicle event where the e-scooter rider crashed into a tree. From these statistics, it’s difficult to decipher how much to attribute these terrible events to e-scooters and their riders versus how much to attribute to the general lack of safety for vulnerable road users.

The universal metric for road safety has been the number of crashes, which requires a three- to five-year observation period. Statistically speaking, crashes are rare and random, and with shorter observation periods, all data is zero-inflated. Even “dangerous” intersections may only accumulate several crashes over five years. This makes it difficult to get any significant results in crash modeling for engineers, and, unfortunately, modern e-scooters haven’t been in wide use for that long. Through the lens of traditional road safety engineering, we are only seeing a few data points in a comprehensive e-scooter safety story that has yet to be written, let alone be told.

We don’t have to wait for more e-scooter crashes

Road safety is a topic that is near and dear to my heart. I started my career in technical assistance and monitoring and evaluation of road safety in emerging economies, which put me knee-deep in the problem of crash data scarcity. This is when I grew fond of surrogate measures of safety, which are objective indicators that either resemble crashes or have strong relationships with crashes. A common one is “traffic conflicts,” which a layperson might refer to as “close calls.”

In our everyday lives, we don’t think much about almost getting into an accident. But for safety researchers, this data can be a gold mine. Christer Hyden, known as the godfather of traffic conflicts, introduced the safety pyramid below to illustrate the continuum of traffic event types. The idea is to study severe traffic conflicts as they greatly resemble actual crashes and occur more frequently. This way, we overcome the paradox of road safety engineers having to wait for crashes to occur in order to understand how to prevent them.

Safety pyramid adapted from Hyden (1987)

The beginnings of surrogate safety research involved humans physically observing and recording indicators at sites for days or weeks. You can imagine why this was not scalable. With recent advances in computer vision and machine learning, however, we are able to automate this process. We can feed traffic video data into a machine-learning algorithm and automatically detect and classify road users and calculate indicators of interest like spatial and/or temporal proximity indicators such as speed, traffic conflicts, and evasive maneuvers. Video data may be available through traffic cameras, or researchers could collect their own data. Several years ago, I wandered the streets of Accra and Bogota to install and babysit my GoPros.