Crowdsourced bicycling crashes and near misses: trends in Canadian cities

Abstract

Safety concerns are a barrier to increasing bicycling. BikeMaps.org, a tool for crowdsourcing bicycling collisions, near misses, and falls, offers rich data on local bicycling safety concerns. Our goal is to characterize dominant bicycling safety issues reported in nine Canadian cities. We analyzed 2,513 BikeMaps.org reports (522 collisions, 151 falls, 1840 near misses), and summarized the types of incidents reported, ratios of near misses to collisions by incident type and by city, and injuries resulting from various types of crashes. Incidents categorized as a 'dangerous pass, overtake at midblock', were most commonly reported and had the highest ratio of near misses to collision reports (9:1). Cities with a high commute mode share for bicycling had lower near miss to collision reporting ratios. Overall, 40.3% of reported collisions or falls required medical treatment. Incident types with the most severe outcomes were 'left cross at an intersection' (58.4% reported needing medical treatment); 'vehicles failing to stop at intersection or yield to bike' (54.0%); and 'multi-use paths, vehicle conflicts at intersection' (48.5%). Mitigating conditions leading to real or perceived concerns over dangerous passes by vehicles should improve bicycling comfort. Bicycling injuries will be reduced by safety improvements at intersections including those with multi-use paths.

Results From a Campus Population Survey of Near Misses, Crashes, and Falls While E-Scooting, Walking, and Bicycling

“…Additionally, these findings suggest a need for a near miss monitoring or mapping system, such as BikeMaps.org, where users can log complaints to prompt action before a crash occurs. In crowdsource reports of incidents, near misses are reported at approximately 3:1, compared with crashes and near miss data ( 33 ). An even better system could be one that systematically captures near misses, as some sensor and video networks are working toward.…”

WalkRollMap.org: Crowdsourcing barriers to mobility

“…In addition to collecting data on the hazard or concern, missing amenity, or incident, we ask demographic questions to determine gender, age, race, and any mobility issues on all reports ( Figure 5 ). Finally, we included a mandatory open-ended description field for the participant to provide additional details on their report as our work on BikeMaps.org has shown that these narratives provide valuable context for informing research or action ( 28 , 29 ).…”

“…Crowdsourcing data provides an opportunity to fill in data gaps related to the urban built environment ( 27 ). For example, BikeMaps.org has provided rich self-reported data that have enabled a better understanding of the contextual issues at hot spot locations ( 28 ) and trends in crash scenarios across cities ( 29 ). Another crowdsourcing app, accessnow.com, rates the accessibility of public spaces such as restaurants, trails, and shops.…”

Epidemiologi Kecelakaan Lalu Lintas: Tantangan Dan Solusi

“…Apabila insiden kecelakaan lalu lintas tidak dilaporkan, maka hal ini dapat mengurangi kewaspadaan pengguna jalan dan pengambil kebijakan tidak dapat memutuskan upaya pencegahan kecelakaan lalu lintas di wilayah tersebut (Chang et al, 2020;Sa'diyah & Enggarsasi, 2018). Masalah underreporting, dimana insiden kecelakaan lalu lintas memang terjadi tetapi belum dilaporkan, terbentuk karena adanya persepsi pelaporan kecelakaan hanya untuk jenis kecelakaan besar dan fatal dan kurangnya pengetahuan masyarakat tentang kemana harus melapor sesaat setelah terjadi kecelakaan (Laberee et al, 2021;Shinar et al, 2018;Zamzuri, 2021). Statistik kecelakaan lalu lintas saat ini hanya jumlah yang tercatat, jumlah tersebut sebenarnya dapat melebihi jumlah saat ini.…”

“…Persepsi ini perlu diubah. Penelitian sebelumnya menyimpulkan pentingnya pelaporan insiden nyaris celaka (nearmiss) dan kecelakaan non-fatal untuk menghindari jenis kecelakaan yang lebih besar terjadi di lokasi yang sama pada masa mendatang (Laberee et al, 2021;Shinar et al, 2018).…”