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.

Mapping ridership using crowdsourced cycling data

“…Data on cycling volumes support decision making and research by enabling, for example, investigation of factors that influences ridership (Griswold et al, 2011;Niemeier, 1996) and quantification of exposure when assessing cycling safety (Nelson et al, 2015). Ridership data are difficult to obtain and often limited by traditional methods of data collection (Gosse and Clarens, 2014;Nordback et al, 2013).…”

Correcting Bias in Crowdsourced Data to Map Bicycle Ridership of All Bicyclists

“…Detailed maps of bicycling ridership are critical to professionals in making decisions regarding infrastructure investment and policy changes that support active transportation. The framework developed in this paper can be used as a generalized risk assessment and exposure modeling tool to benefit accident prevention among bicyclists, with sufficient availability of accident data from crowdsourced platforms, like Bikemaps.org [19], and provide an estimate of bias-corrected bicyclist volumes for infrastructure planning to enhance comfort among bicyclists and promote active modes of transportation for healthier lifestyles among wider demographics.…”

Assessing the Exposome with External Measures: Commentary on the State of the Science and Research Recommendations

“…There are also opportunities for crowdsourcing of self-reported data via Web-based interfaces. For example, data on cycling safety and collisions can be collected online by a global mapping system (66). Data on perceptual information can also be gathered through context-sensitive ecological momentary assessment (CS-EMA) through real-time self-reported smartphone assessments.…”