INNOVATION Research Lab: Human Autonomy Teaming


This research team aims to gain new insights into role-based human variability contributing to interpersonal (automated vehicle-pedestrian) interactions under the real-world conditions of a vehicle traveling in regular traffic. We are interested in learning and predicting variability that arises from naturalistic fluctuations in cognitive state, indexed by gait and daily estimates of risk preferences of a pedestrian.

This team will investigate the feasibility of a fully predictive methodology to detect the intention to start and stop a gait cycle by utilizing EEG signals obtained before the event occurrence and model an intelligent traffic system that can establish connection between vehicle to pedestrian without sacrificing privacy. The team aims to gain new insight about pedestrian and automated driver communication methodology for a safe traffic system. This team also aims in building innovative sensor prototypes for supporting the research application.

Experience Gained

  • Python programming
  • Neural Signal Processing
  • Machine Learning
  • Biomedical signal Processing
  • Sensor Design 
  • Statistical Analysis

Majors and Interests Needed

  • Electrical Engineering
  • Psychology
  • Computer Science
  • Information Technology
  • Data Science

Team Advisors

  • Name 
  • Sylvia Bhattacharya, Ph.D. 

    Assistant Professor of Electrical Engineering Technology