BikeMaps.org: A Global Tool for Collision and Near Miss Mapping

Abstract

There are many public health benefits to cycling, such as chronic disease reduction and improved air quality. Real and perceived concerns about safety are primary barriers to new ridership. Due to limited forums for official reporting of cycling incidents, lack of comprehensive data is limiting our ability to study cycling safety and conduct surveillance. Our goal is to introduce BikeMaps.org, a new website developed by the authors for crowd-source mapping of cycling collisions and near misses. BikeMaps.org is a global mapping system that allows citizens to map locations of cycling incidents and report on the nature of the event. Attributes collected are designed for spatial modeling research on predictors of safety and risk, and to aid surveillance and planning. Released in October 2014, within 2 months the website had more than 14,000 visitors and mapping in 14 countries. Collisions represent 38% of reports (134/356) and near misses 62% (222/356). In our pilot city, Victoria, Canada, citizens mapped data equivalent to about 1 year of official cycling collision reports within 2 months via BikeMaps.org. Using report completeness as an indicator, early reports indicate that data are of high quality with 50% being fully attributed and another 10% having only one missing attribute. We are advancing this technology, with the development of a mobile App, improved data visualization, real-time altering of hazard reports, and automated open-source tools for data sharing. Researchers and citizens interested in utilizing the BikeMaps.org technology can get involved by encouraging citizen mapping in their region.

Keywords: active transportation; bicycling safety; citizen science; cycling safety surveillance; near miss.

Figure 1

BikeMaps.org is a global tool for citizen mapping of cycling collisions, near misses, hazards, and thefts. The upper panel shows the website and global map. The lower panel – left is a close up of the map and the view typically used by the citizen mapper when adding data. The lower – right is an example of the table used to collect attribute data on each cycling incident.

Figure 2

Number of citizen reports since website launch. (A) Date of initial press release and local radio interview. (B) Date of local newspaper article. (C) Date of regional TV news report. (D) Date of local newspaper article paper. (E) Date of radio interview.

Figure 3

Day of week trends for citizen reports of collisions and near misses.