• Micromobility
  • Fleet Decarbonization
  • Digital Innovations
  • Automated Vehicles

Data Driving Automated Vehicles

Quantity, Quality, and Relevance

Sep 11, 2018 - 2:00 PM EDT
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Sponsored By https://mighty.ai/
The nature of software architecture and development has shifted dramatically in the past decade, enabled in part by the evolution of highly parallelized microprocessors. Since machine learning and neural networks have become practical to use, engineers can apply these techniques to solving esoteric problems. Among these are object recognition and classification, which are crucial to enabling everything from manufacturing to security systems to automated driving. 

Before millions of automated vehicles are deployed in the coming decade, the deep neural networks powering them will require large quantities of carefully annotated and labeled data for training and validation. With the vast and often unpredictable nature of driving, billions of virtual driving miles in simulation using both real world and synthetic datasets will be essential to ensuring that these systems are safe for use. Join this webinar and read the white paper to learn more about how the data is captured, curated, prepared and used to enable these sensor laden automated vehicles. 

  • Data collection and processing for automated driving
  • Data and product validation
  • Simulation using synthetic data
  • Why is data needed to develop new mobility products?
  • How is the data used in these new products?
  • Where does the data come from?
  • How can stakeholders ensure all the data generated by automated vehicles is useful?
  • How does synthetic data get produced and used?
  • Auto manufacturers
  • Automated driving developers
  • Technology vendors
  • Computing providers
  • Software developers
  • Mobility service providers