Road Traffic Safety for Electric Microvehicles (VIASAFETY)

Important results from the project

The VIASAFETY project demonstrated that connected vehicle data from electric micro mobility fleets is a valuable contributing data source for identifying and mitigating safety risks in cities, especially given the increasing presence of electric two-wheeled vehicles on European road networks. By analysing the collected data using machine learning and quality assurance methods, the project team identified a number of high-risk zones across the urban network.

Expected long term effects

The ViaSafety project generated a picture of how delivery mopeds interact with the road network in Gothenburg, based on high-resolution GPS and accelerometer telematics. Using aggregated, anonymized event indicators, the analysis identifies where severe incidents occur more frequently and provides a structured basis for prioritizing locations for further research, investigation, and potential safety measures.

Approach and implementation

The project was implemented in three stages: 1- Data collection, processing and quality assurance, 2- Aggregation into comparable road areas 3- Ranking of the road network to identify locations with higher risk. The analysis calculated indicators (KPIs) such as heavy braking, hard cornering and high acceleration, where high-risk locations were identified by ranking road segments using a composite risk method and detecting clusters of segments with elevated event frequencies.