Mobility is an important factor in everyday life. Human-Machine-Interaction can improve the reliability, safety and comfort in beeing mobile in this case by using bikes. Cyclists like children, young teenagers and elderly as well are vulnerable road users because of the limited protection on a bike. Furthermore, children and young teenagers are sometimes too inexperienced to realize traffic situations appropriately.
The goal of the "Safety4Bikes" project is to develop a modularizied assistence system for bikes. These modules should detect risky and may predict hazardous situations. Once the situation is detected an audible, optical or haptic feedback will be given to the cyclist. This can be done by using actuators on the bike or helmet. The research objective is to develop the right form of feedback and additionally the communication between bikes and other road users. Finally, this should lead to a improved safety.
Using the developed technologies, the bike in conjunction with a helmet and smartphone of the cyclist will predict hazardous situations and teach kids and young teenagers in traffic behaviour.
The research and development tasks of AMT is to develop sensors and actuators for the bike and cyclist. Additionally, the modularization of the sensors and actuators will be focused. Based on a set of exemplary hazardous situations the needed parameters for detection and prediction will be discussed and evolved with the other project partners.
Further work is to determine which sensors are usable in a biking scenarion based on power requirements, precission and ruggedness. The selected sensors and actuators will be modularized for example with a independent power supply, so that the modules are easily attachable and dettachable to the bike. Each module has it's own processing chain to obtain required information based on sensor data. The complete system will be trained using the set of preliminary classified hazardous situations to enable early detection of such situations. A similar procedure is planned for the detection of the cyclist's behaviour. This is achieved by using sensors like accelerometers, gyroscopes and compasses. Using EEG data and fNIRS is also beeing considered.
The project "Safety4Bikes" (previously "Bikes4Kids") is funded by the "Bundesministerium für Bildung und Forschung" - BMBF - from 01/2017 to 12/2019.
- GeoMobile GmbH, Dortmund
- Gesellschaft für empirische soziologische Forschung e. V., Nürnberg
- OFFIS e. V., Oldenburg
- UVEX SPORTS GROUP GmbH & Co. KG, Fürth
- Universität Paderborn
- Valtech GmbH, Düsseldorf
- PFAU Tec GmbH, Quakenbrück