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
Dr. Jonathan Hasenburg
Dr. Jonathan Hasenburg
Software Architect

I did my PhD on optimizing data distribution for IoT applications with a heavy focus on pub/sub systems that are, among others, based on MQTT. Now I am working for RIO (Bosch Group) as a Software Architect on topics concerning any part of our Home Connect Plus offering with a focus on the Cloud backend and Matter.