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Session

Case Study

Thursday, June 26

06:00 PM - 06:30 PM

Live in San Francisco

Less Details

The automotive industry is undergoing rapid transformation with the introduction of new vehicle architectures and software-defined vehicles, alongside advanced processing platforms. This shift creates a wealth of innovative data-driven opportunities. In this presentation, Dr. Xiao explores Real-time HD Semantic Map solutions designed to enhance parking experiences and enable Level 4 autonomous parking systems, leveraging surround view cameras for precision and accuracy.

In this session, you will learn more about

  • Utilizing crowd-sourced parking maps derived from sensor data, sourced from mapping cars or end customer fleets.
  • Generating shareable global semantic parking maps on demand for Autonomous Valet Parking (AVP), leveraging the detection of landmarks like parking lines and guide signs.
  • Achieving centimeter-level accuracy in vehicle localization within the map through V-Localize technology.
  • Providing live status updates on parking spot availability, including handicap/EV/Reserved spots, ensuring efficient and accessible parking solutions.

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