Cooperative collision risk detection for C-ITS-equipped bicycles and connected automated vehicles.
Hannah Wies, Markus Steinmaßl, Andreas Wagner, Edwin Frühwirth, Florian Bissinger, Alexander Paier, Karl Rehrl, Robert Kölbl, Fabio F. Oberweger und Cornelia Zankl (2025): Cooperative collision risk detection for C-ITS-equipped bicycles and connected automated vehicles. In: Journal of Location Based Services
The numbers of cycling fatalities and serious injuries remain too high to meet the targets set by the European Commission with the Road Safety Framework 2021. Cooperative intelligent transport systems are one possible solution, enabling the exchange of safety critical information between vehicles, vulnerable road users, and infrastructure to prevent accidents and increase safety. The aim of this work is to actively integrate bicyclists in vehicle-to-everything communication, to profit from collective perception and to test it with a proof-of-concept prototype. This approach incorporates the location information of road users with the perception information captured by a connected automated vehicle and a video detection system at the roadside. The communication is based on standardized messages that are exchanged via vehicular communication standard (ITS-G5) and cellular networks. A central cloud-based processing service calculates collision risks of the road users, using an infrastructure-based approach with high-definition-maps and sending out warning messages. The proof-of-concept prototype was evaluated in real-world experiments in urban and rural environments, successfully demonstrating a technical roundtrip of the flow of information from sending self-localization information up to receiving a warning. Results show that precise self-localization as well as a low latency and stable map matching are crucial prerequisites for safety applications.
