Learning to Drive Autonomously

The research team aims to develop innovative adaptive learning algorithms to tackle the combined longitudinal and lateral control of autonomous vehicles and its extension to optimal cooperative adaptive cruise control (CACC) of connected and autonomous vehicles. Learning-based suboptimal vehicle controllers will be designed, along with robustness analysis in the presence of human reaction time and exogenous disturbances.

Project

Subject/Index Terms

Filing Info

  • Accession Number: 01737125
  • Record Type: Research project
  • Source Agency: Connected Cities for Smart Mobility towards Accessible and Resilient Transportation Center (C2SMART)
  • Contract Numbers: USDOT 69A3551747124
  • Files: UTC, RiP
  • Created Date: Apr 22 2020 3:51PM