Introduction and Objectives
Bike traffic often plays a minor part in the context of automated and connected driving. Because of this, this research project aims at developing a warning and support system across all transport modes and implementing it as a prototype.
Through the integration and connection of different transport modes such as bicycles, passenger cars and public transport, the comprehensive study of safety aspects is possible. The warnings issued in critical situations are generated on the basis of the fundamental analysis, classification and modeling of hazard situations created with the help of statistical data (accident data, historical data) as well as dynamic data (latest bicycle sensor data, signals of other traffic participants and traffic lights). New information types, such as maneuver decisions of automated vehicles, are also suitable for the system.
Data is acquired by environmental sensors including GPS (in conjunction with a specific correction signal for higher locating precision). The information thus extracted is passed on in a user-adaptive and context-based way and provides the basis for action support in complex traffic situations. For the first time, human-machine interface (HMI) concepts for bicycles allowing a context-based and user-adaptive complex interaction are investigated.
The warning and support system does not only give warnings to bike and car drivers in situations of immediate danger, but it also gives predictive warnings. The system’s modularity, user-based and context-based adaptivity of alerts and comprehensive coverage of safety aspects promise a broad application of the solution in terms of different user groups and customer segments (high-end niche market vs. mass market).