4 papers
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…
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…
Specification-Guided Data Aggregation for Semantically Aware Imitation Learning
Ameesh Shah, Jonathan DeCastro, John Gideon +3
Advancements in simulation and formal methods-guided environment sampling have enabled the rigorous evaluation of machine learning models in a number of safety-critical scenarios,…
Learning Latent Traits for Simulated Cooperative Driving Tasks
Jonathan A. DeCastro, Deepak Gopinath, Guy Rosman +3
To construct effective teaming strategies between humans and AI systems in complex, risky situations requires an understanding of individual preferences and behaviors of humans. Pr…