5 papers · 1 filter
Dreaming to Assist: Learning to Align with Human Objectives for Shared Control in High-Speed Racing
Jonathan DeCastro, Andrew Silva, Deepak Gopinath +4
Tight coordination is required for effective human-robot teams in domains involving fast dynamics and tactical decisions, such as multi-car racing. In such settings, robot teammate…
Computational Teaching for Driving via Multi-Task Imitation Learning
Deepak Gopinath, Xiongyi Cui, Jonathan DeCastro +10
Learning motor skills for sports or performance driving is often done with professional instruction from expert human teachers, whose availability is limited. Our goal is to enable…
Think Deep and Fast: Learning Neural Nonlinear Opinion Dynamics from Inverse Dynamic Games for Split-Second Interactions
Haimin Hu, Jaime Fernández Fisac, Naomi Ehrich Leonard +3
Non-cooperative interactions commonly occur in multi-agent scenarios such as car racing, where an ego vehicle can choose to overtake the rival, or stay behind it until a safe overt…
Personalizing Driver Safety Interfaces via Driver Cognitive Factors Inference
Emily S Sumner, Jonathan DeCastro, Jean Costa +14
Recent advances in AI and intelligent vehicle technology hold promise to revolutionize mobility and transportation, in the form of advanced driving assistance (ADAS) interfaces. Al…
Blending Data-Driven Priors in Dynamic Games
Justin Lidard, Haimin Hu, Asher Hancock +9
As intelligent robots like autonomous vehicles become increasingly deployed in the presence of people, the extent to which these systems should leverage model-based game-theoretic…