Our CTO Eric Richter spoke about the project goals and results of the BMWi project SADA (Smart Adaptive Data Aggregation)
In an interview with electriveNet at the Hannover Messe in Germany, Eric Richter describes the main ideas of the SADA project.
One aspect in the development of novel automated driving functions is the perception of the vehicle’s environment based on more and more sensors. As the number of sensors increases, so does the development time for vehicle manufacturers and suppliers. The objective of the SADA team was to drastically reduce the development time and the associated effort to enable faster availability of automated driving functions for the end-user of the vehicle.
Thereby the increasing number of sensors in the vehicle itself as well as in the infrastructure is decisive. In the future, for example, traffic lights, road signs or vehicle charging stations could be equipped with sensors. At this year’s “Hannover Messe” a demonstrator was presented which considers V2X sensors (vehicle-to-everything). This allows for integrating data from the infrastructure to extend the environment model and thus enable a more accurate data acquisition and evaluation. The data obtained from such networking of vehicles and infrastructure systems enables, for example, the displaying of free parking spaces, a stabilization of the traffic flow or the reduction of number of accidents.
The insights from this research project are used to further improve or redesign BASELABS’ software products to allow for their application for developing series-grade data fusion solutions. This will enable BASELABS customers to release series software and thereof the resulting driving functions more quickly for the market.
The Data Fusion Designer developed in the SADA project plays a decisive role here, since it enables a simple and fast integration of a wide range of sensors. Find out more about the Data Fusion Designer in our latest news article.
The SADA project is part of the technology program "IKT für Elektromobilität des BMWi".
The full video is available on the electriveNet YouTube channel.
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As active contributors to research and the data fusion community, we frequently publish papers with regards to sensor fusion. The paper can be downloaded free of charge.
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