For more than 20 years, we have developed algorithms for personal navigation using wearable sensors, particularly inertial sensors, barometer and magnetometer. We have concentrated on professional use-cases, such as firefighters or rescue teams. Since 2017, we opened our research area to the urban mobility. Firstly, we developed a navigation system for bicycles and we integrated the two active transport modes together, i.e. walking and riding a bicycle. Our next step was to add to our multi-sensor approach the satellite navigation. In 2019, we transformed our algorithms to work with the low-cost sensors embedded in commercial smartphones.
Currently, we focus our research in developing an enhanced smartphone-based passenger localization in stations, airports and on the bicycle. In addition, we develop data-driven movement models for bicycles that enable more realistic simulations of passengers’ flows, e.g. in SUMO. Furthermore, we work on increasing the awareness of other traffic participants towards the cyclists with the aim of avoiding possible collisions.
The sensors integrated in the smartphone measure the cyclist's position and speed. This data, as well as the vehicle position and speed, is transmitted to the app, which then anticipates a possible collision and triggers a warning.30.06.2020 - >>Contribution DLR Portal, DE