Publication

The VIASAFETY project demonstrates that connected vehicle data from electric micro‑mobility fleets is a worthwhile contrinuting data source to identify and mitigate urban road safety risks, especially given the increasing presence of electric twowheeled vehicles on European road networks. Using telematics sensors installed on a centrally managed fleet of electric mopeds operating in Gothenburg, the project collected large volumes of GPS and accelerometer data from real delivery operations, without relying on any personalised information. By analysing harsh braking, speeding, swerving and other near‑miss indicators with advanced data processing, machine learning and quality assurance methods, the project team identified a number of  “blackspots” and high‑risk zones across the city network. Beyond proving the technical feasibility of this approach, VIASAFETY clarifies how operational context, legal constraints and data representativeness must be handled to derive meaningful safety insights. The project delivers a GDPR‑compliant data pipeline, refined road safety algorithms and processed datasets ready for further research via SAFER and CLOSER’s national logistics data lab. The results create a foundation for cities and operators to move from retrospective, crash‑based safety management towards more proactive, near‑real‑time monitoring, enabling targeted interventions such as traffic calming, infrastructure adjustments and speed management for vulnerable road users and professional couriers.