A car is turning right while an e-scooter continues straight ahead. If the driver fails to spot the scooter, a collision can happen in an instant. Dr Pascal Brunner of Technische Hochschule Ingolstadt (THI) has been studying situations like these at urban junctions for several years. His idea is to tackle the problem directly through the vehicle rather than installing additional sensors on the roads.
Known high-risk areas are marked digitally, for example by creating a virtual GPS boundary around a junction. As soon as an e-scooter enters the zone, its maximum speed is automatically limited to 10 km/h. The commands are transmitted via an Internet of Things (IoT) device already fitted to rental e-scooters. This means no changes to road infrastructure or additional cameras are required. Once the area has been defined, researchers say the speed restriction can be programmed in a matter of minutes.
“We already know exactly where dangerous encounters are likely to occur in many locations. We can put that knowledge to good use,” says Brunner. “Rather than investing in extensive upgrades at every junction, we can reduce speeds precisely where they pose a risk. That allows us to intervene before a dangerous situation even develops.”
Accident figures underline the importance of such approaches. In 2025, German police recorded 16,496 e-scooter accidents involving personal injury. A total of 1,895 people were seriously injured and 38 lost their lives.
The potential impact of speed restrictions can be assessed even before they are introduced on public roads. Brunner uses digital twins of real-world traffic situations to do this. In his doctoral research, he adapted a principle from controlled medical studies to traffic research, comparing almost identical scenarios with and without intervention. He simulated millions of journeys through junctions using this method. Under the conditions examined, the calculated risk of an accident was reduced eightfold. Shorter braking distances are only part of the explanation: lower speeds also give both parties more time to react.
The approach has since moved from simulation to real-world testing. Hamburg trialled the system in live traffic for one week, while researchers also collected data from a separate week without speed restrictions for comparison. According to the project partners, this was the world's first real-world trial of a slow zone designed specifically to reduce e-scooter speeds at a junction to prevent accidents. E-scooter rental provider Ryde was involved in the technical implementation. The data are currently being analysed. To establish statistically robust evidence of the system's effectiveness, Brunner recommends monitoring five or six busy junctions for at least a year.
The Hamburg pilot forms part of the European research project MITHOS, which brings together data from different modes of transport and uses artificial intelligence to develop new solutions for safer, more efficient infrastructure. Professor Werner Huber leads THI's work on the project, while Brunner plays a key role in the research into e-scooter safety.
High-resolution movement data will also help researchers understand how cars, bicycles and e-scooters interact. This will allow them to identify potential conflicts and test preventive measures virtually before implementing them. The aim is to reduce dangerous situations involving bicycles and e-scooters by 30 per cent in the pilot area. The approach is also set to be introduced in Bilbao, Spain.
Brunner sees the technology as a contribution to Vision Zero, the goal of eliminating road deaths and serious injuries. “E-scooters have become an integral part of urban transport. The key question is how to integrate them safely. If we can reduce known risks through a relatively simple technical solution, we should make the most of that potential.”
