Bad road surfaces are are physical stress for drivers and car. They reduce the travelling comfort, increase the fuel consumption and create noise pollution. As a result, the measurement and repairing of roads is a regular task for road traffic departments everywhere. Detecting bad surfaces is mostly done with specialised measurement cars. This procedure is often both expensive and time consuming, and creates a financial problem. As a result, repairs are often delayed or not done at all.
Thanks to research in the area of cyberphysical systems, it is nowadays possible to integrate measurement devices in any car. Using a crowdsourcing approach, one could give away these measurement devices and then collect and evaluate all the measured data in a central instance. This data could then, for example, be used to create better road models which would allow faster repairs, or to improve navigation to avoid “bumpy roads”.
Goal of Roadstar
Goal of this project is it to develop and test a system, which allows simple measurement of road surface data while driving, and creating a system for storage and evaluation of this data afterwards. Common hardware, such as Rasperry PIs, gyro- and gps-sensors should therefore be combined into a portable measurement system.
Core concepts which should be implemented, are the synchronisation, transmission, storage and basic evaluation of the measured sensor data. With these sensors, data should continuously be measured at different points of the car. The collected data then should be synchronised and transmitted to a central server.
On the server, the data should be classified using existing algorithms, and transformed into a form which can be displayed on a simple web frontend.