Computer Science Location: Zoom (email presenter for link)
Add to Calendar 2021-06-29T13:00:00 2021-06-29T13:00:00 America/New_York Ph.D. Qualifying Exam Presentation by Aron Harder Scenario2Vector -- Scenario Description Language Based Embeddings for Traffic Situations Abstract:  Zoom (email presenter for link)

Scenario2Vector -- Scenario Description Language Based Embeddings for Traffic Situations

Abstract: 

The industry standard metric for measuring progress in autonomous driving has been the “miles per intervention” metric. This is nowhere near a sufficient metric and it does not allow for a fair comparison between the capabilities of two autonomous vehicles (AVs). We propose Scenario2Vector - a Scenario Description Language (SDL) based embedding for traffic situations that would allow for automatically searching for similar traffic situations. The SDL embedding distills a traffic situation experienced by an AV into its canonical components - actors, actions, and the traffic scene. We can then use this embedding to evaluate similarity of different traffic situations in vector space.

Committee:

  • Aidong Zhang, Committee Chair, (CS/SEAS/UVA)
  • Madhur Behl, Advisor, (CS/SEAS/UVA)
  • Jack Stankovic (CS/SEAS/UVA)
  • Vicente Ordóñez Román (CS/SEAS/UVA)