AI-SEE aims to develop a robust and fault-tolerant novel sensing technology and associated AI enabling automated driving in all relevant weather & lighting conditions (snow, heavy rain, fog).

Consortium Overview

The strong industrially driven consortium is coordinated by Mercedes Benz AG. Major OEMs and world class suppliers including software specialists lend credibility to an industrialized, marketable sensor system. The development work is supported by research institutes and engineering companies with large experience in AI, signal processing and simulation specific topics.


System providers (hardware and software)

Technology providers (AI algorithms and frameworks)

Development tools and simulation

Modules and Components

Inclement weather testing facilities

AI-SEE at a glance


Dr. Werner Ritter

Mercedes Benz AG

20 Partners

OEMs, Automotive Suppliers, Research Institutes, Engineering Companies

43 Months runtime

01.06.2021- 31.12.2024

6 Countries

Austria, Canada, Finland, Germany, Israel, Sweden


Total Costs


Funding Budget

The impact

The importance of the automotive industry for the EU’s economy is crucial. The European automotive sector is one of the largest global exporter and driver of Europe’s growth and prosperity with 2.7 million people employed in the production of motor vehicles which accounts for 8.5% of EU manufacturing jobs. The automotive industry needs to stay in the forefront and can only do so by being technology leaders that provide significant value added benefits to the consumers. 

The industry is adjusting to a sharing society that sees transportation less as a product to buy but more as a mobility service – with the global market for shared vehicles and mobility offerings predicted to grow exponentially in the years from 2020 onwards. 
With its novel sensing technology, AI-SEE has the potential to set a new industry benchmark for automated vehicles first entering the market and operating flawless in all visibility and weather conditions.

Concretely, AI-SEE will

  • create a paradigm shift in signal enhancement technique by performing sensor-near transformation of good weather datasets into adverse datasets
  • reduce the costs for the creation of adverse weather annotated data for AI
  • sustain jobs & foster economic growth
  • reduce high costs for AI & Lidar data
  • strenghten Europe's lead in Automotive
  • shorten the time to market
  • improve road safety