SimRa: Using Crowdsourcing to Identify Near Miss Hotspots in Bicycle Traffic
This addresses safety concerns for cyclists and city planners by providing data to improve bicycle infrastructure, though it is incremental as it builds on existing crowdsourcing methods.
The paper tackles the problem of insufficient data on bicycle safety by developing SimRa, a crowdsourcing platform that collects bicycle routes and near miss incidents via smartphones, and proposes a scoring model to identify dangerous hotspots.
An increased modal share of bicycle traffic is a key mechanism to reduce emissions and solve traffic-related problems. However, a lack of (perceived) safety keeps people from using their bikes more frequently. To improve safety in bicycle traffic, city planners need an overview of accidents, near miss incidents, and bike routes. Such information, however, is currently not available. In this paper, we describe SimRa, a platform for collecting data on bicycle routes and near miss incidents using smartphone-based crowdsourcing. We also describe how we identify dangerous near miss hotspots based on the collected data and propose a scoring model.