SimRa: Using Crowdsourcing to Identify Near Miss Hotspots in Bicycle Traffic

Abstract

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.

Publication
Pervasive and Mobile Computing
Jonathan Hasenburg
Jonathan Hasenburg
Research Associate & PhD Student

My research focuses primarily on the optimization of publish/subscribe systems for mobile IoT applications by using geo-context information.