In the Reallabor Hamburg (RealLabHH) the mobility of tomorrow will be tested in the here and now of a metropolis in order to create a blueprint for the digital mobility of the future. The social debate on digital mobility services is at the core of the overall project and should provide important insights into which mobility solutions prove themselves in practice and in what form. A key feature of the project is the continuous and comprehensive involvement of citizens. The planned sub-projects range from establishing a mobility budget instead of using company cars to the creation of a provider-independent mobility platform. The contribution of Fraunhofer FOKUS: the development of a solution for particularly vulnerable participants in road traffic.

Warning of collisions and obstacles

In addition to moving on foot and by bicycle, electrified micromobility, i.e. e-scooters or electric bicycles, constitutes a valuable local contribution to emission-free mobility within the city. These road users, however, are exposed to an increased risk of injury compared to people in cars, buses or trucks - this group is designated as “vulnerable road users” (VRU). This is why the integrated solution from Fraunhofer FOKUS focuses on increasing traffic safety for the VRU. The service should warn the user of a collision with another road user or obstacle via their smartphone, as an example. The central technological building block for this is a highly accurate localization, which so far has had to be developed and tested individually for each app and each type of smartphone.

The Fraunhofer research team of the Smart Mobility business unit processes the smartphone sensor technology to determine position and orientation using Mobile Edge Computing, a cloud infrastructure that is closely connected to the mobile phone user. This “Location-as-a-Service (LaaS)” service can then be used for applications such as the hazard warning system or a traffic light phase assistant (Green Light Optimal Speed Advisory - GLOSA). A challenge here, compared to the localization of a car, is that the smartphone can be located in different places on a bicycle or scooter - e.g. on the handlebars or in the trouser pocket - and large steering movements can make localization more difficult. In a next step, sensor data from vehicles in the vicinity, e.g. from cameras and laser scanners, will be included in order to further improve precision.