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While elements such as rain or inclines may deter individuals from cycling, a significant obstacle is the danger of being struck by a vehicle. Identifying the safest paths for cycling is challenging, particularly for novice riders, and a crucial method to highlight perilous streets relies on time and harm: waiting until vehicles have struck multiple cyclists at a specific site.

A team from the University of Washington has created a system known as ProxiCycle, which records instances when a passing vehicle approaches too closely to a cyclist (within four feet). An affordable, compact sensor attaches to bicycle handlebars and monitors these close encounters, transmitting data to the rider’s mobile device. The team evaluated the system over two months with 15 cyclists in Seattle and discovered a noteworthy correlation between the sites of close passes and additional indicators of inadequate safety, like accidents. When implemented on a larger scale, the system could assist in mapping or guiding cyclists towards safer biking passages in urban areas.

“Seasoned cyclists tend to possess this mental blueprint of which routes are secure and which are perilous, and I aimed to devise a straightforward method to convey that information to beginner cyclists,” stated lead author Joseph Breda, a doctoral candidate at UW in the Paul G. Allen School of Computer Science & Engineering. “Cycling significantly benefits both health and the planet. Increasing the number of people cycling regularly is pivotal for us to gain those advantages and enhance safety through higher cyclist numbers on the streets.”

The team shared their findings on April 29 at the ACM CHI Conference on Human Factors in Computing Systems in Yokohama, Japan.

Initially, researchers conducted a survey with 389 individuals in Seattle. Participants of various cycling experience levels identified the threat posed by vehicles as the primary factor discouraging them from biking, and they expressed a strong likelihood of utilizing a map that assists in safe navigation. However, a significant hurdle to this is the scarcity of data on road safety.

The team subsequently developed a compact sensor system that attaches to a bicycle’s left handlebar. This system, costing under $25 to produce, consists of a 3D-printed plastic shell containing two sensors and a Bluetooth antenna. The antenna relays data to the cyclist’s mobile device, where the team’s algorithm distinguishes a passing vehicle from a pedestrian, another cyclist, or a stationary object.

The group validated the system through tests in a parking lot, allowing a vehicle to pass at varying distances, as well as having seven cyclists ride through Seattle equipped with GoPro cameras on their handlebars. Researchers analyzed the footage from these journeys and compared it to the sensor’s findings.

Later, the team enlisted 15 cyclists via the newsletter of Seattle Neighborhood Greenways, a local advocacy organization. Each participant received a ProxiCycle sensor, a tailored Android application, and guidelines. Over two months, the cyclists undertook 240 bike rides and documented 2,050 close encounters. Researchers then juxtaposed the instances of close passes with the cyclists’ perceived safety at various locations throughout the city—measured by presenting cyclists with images of specific areas and asking them to gauge how secure they felt there (termed “perceived safety”)—along with the locations of known vehicle-to-bicycle accidents from the past five years.

The team discovered a significant relationship between close encounters and other indicators of cycling risk. They also noted that this metric of close passes provided a more accurate gauge of actual safety than the surveyed perceived safety, which is currently the standard used by policymakers when examining safety in instances where collisions are insufficient.

Looking ahead, researchers aspire to expand the study and potentially include other risk factors, such as cyclists being impacted by suddenly opening car doors, and implement ProxiCycle in additional cities. With an ample amount of data, existing bike mapping applications, including Google Maps or Strava, could potentially feature safer route options for cyclists.

Some of these routes require only minimal changes.

“One participant, residing near Seattle Center, constantly cycled down Mercer,” said Breda. “It’s a busy, multi-lane thoroughfare. However, shortly before the study commenced, they discovered an excellent bike lane on a more tranquil street, just one block to the north.”

Keyu Chen, an applied science lead at Gridware, along with Thomas Ploetz, a professor at the Georgia Institute of Technology, are co-authors of this paper. Shwetak Patel, a professor at UW in the Allen School, is the principal author.

For further details, reach out to Breda at [email protected].

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