# On Cycling Risk and Discomfort: Urban Safety Mapping and Bike Route Recommendations

## TL;DR

This paper analyzes cycling risk and discomfort in urban areas using geolocated accident data, providing risk maps and a route recommendation tool to enhance cyclist safety and urban planning.

## Contribution

It introduces a novel empirical risk mapping method and an open-source software for personalized bike route recommendations based on safety and comfort.

## Key findings

- Risk maps highlight accident hotspots in Zurich.
- Weather and time significantly influence cycling risk.
- The route recommendation tool improves safety awareness.

## Abstract

Bike usage in Smart Cities becomes paramount for sustainable urban development. Cycling provides tremendous opportunities for a more healthy lifestyle, lower energy consumption and carbon emissions as well as reduction of traffic jams. While the number of cyclists increase along with the expansion of bike sharing initiatives and infrastructures, the number of bike accidents rises drastically threatening to jeopardize the bike urban movement. This paper studies cycling risk and discomfort using a diverse spectrum of data sources about geolocated bike accidents and their severity. Empirical continuous spatial risk estimations are calculated via kernel density contours that map safety in a case study of Zurich city. The role of weather, time, accident type and severity are illustrated. Given the predominance of self-caused accidents, an open-source software artifact for personalized route recommendations is introduced. The software is also used to collect open baseline route data that are compared with alternative ones that minimize risk or discomfort. These contributions can provide invaluable insights for urban planners to improve infrastructure. They can also improve the risk awareness of existing cyclists' as well as support new cyclists, such as tourists, to safely explore a new urban environment by bike.