DC5. AI to mitigate driver distraction and drowsiness at different levels of automation

Ajay Iyer

Education
MIT MicroMasters Program in Statistics and Data Science
Masters in international Business,Grenoble graduate school of Business
Bachelors in Instrumentation Engineering from Mumbai University
About
A PHD researcher in the domain of AI and road safety, with a multicultural background and thrives in a diverse environment. A passionate and driven Data Scientist with more than 5 years of experience in the transportation sector, with an academic background in statistics, data science and international business. My enthusiasm for values based research fuels my projects in applying AI/ML and data science to real world challenges.

Hosts: TUD & PSA-LAB

Objectives:

  • To understand factors contributing to driver distraction and drowsiness in different levels of automation (e.g., ADAS, maintaining
  • driver’s readiness in SAE level 2 vs levels 0 & 1)
  • To develop AI-based models to detect, monitor and predict the precursors of distraction and drowsiness among drivers
  • To understand the relationship between distraction/drowsiness and other risky driving behaviours such as speeding, short headways,
  • delayed reaction time etc.

Expected results:

  • A list of factors as precursors (or predictors) of drowsiness and distraction
  • Cutting-edge analytical models for predicting distraction and drowsiness and their impact on road safety
  • Recommendations about distraction and drowsiness in the presence of technology, AI, and automation

Planned secondment(s):

  • TUD-NL, Purpose: to enrol in DE programme and review state-of-the art and methodology development