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Quality measures for sensor fusion

During the Vehicle Intelligence 2017 BASELABS was pleased to hold the round table session "quality measures for sensor fusion". Among many other possible topics that were preselected by the organizers of the conference, we chose this one in particular. BASELABS has a strong stand in data fusion development as well as data fusion development tooling. We believe that evaluating and validating the output of the data fusion, i.e. the environment model, is an essential and critical part of the overall development process. In a first step, the participants established a unified understanding on the interfaces and connected functionality of sensor fusion in the context of Advanced Driver Assistance Systems (ADAS) and Highly Automated Driving (HAD). This decomposition revealed, that situation assessment is sometimes regarded as part of the data fusion, sometimes as part of the driving function or even as an independent component. In a second and third steps possible output quantities and according quality measures where discussed. A strong argument was given, that for establishing useful quality measures for sensor fusion, one needs to consider the reason the quality is measured for. This could be development support, benchmarking of different data fusion options and designs, or pre-series validation. Furthermore, a technical debate was initiated on how specific quality measures could be determined in practice and reliable ground truth information could be established. In the light of so many interesting aspects we eventually ran out of time during the round table at the Vehicle Intelligence 2017, but we are looking forward to continuing this discussion with our customers and partners, to fulfill our mission on bringing cutting edge data fusion on the street.

For more details about the round table session on the Vehicle Intelligence 2017 click here.

Let's step ahead!

BASELABS addresses several of the points raised in the discussion. Contact us to discuss your specific requirements towards the utilization of quality measures in the data fusion development process.

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