Baisravan HomChaudhuri, Illinois Institute of Technology, MMAE.
November 16, 2021. 12:45 – 1:45 pm.
John T. Rettaliata Engineering Center, Room 106.
Decision making for automated systems in the presence of uncertainty is a challenging yet ubiquitous problem (e.g., automated vehicle control) that has significant potential for societal impact. For example, autonomous vehicles can improve emission and energy-efficiency of the transportation system, which contributes 29% of greenhouse gas emissions and 142 billion gallons of gasoline was consumed in 2019 in US. The automated systems technology industry has potential for tremendous growth. The global autonomous vehicle market is projected to reach $556 billion by 2026, while small unmanned aerial systems are projected to be a $30 billion industry by 2029. Recent market research highlights safety as one of the major factors that can impact this growth. Hence, ensuring safety of these automated systems, while improving their performance (e.g., energy efficiency), is of utmost importance. This research will specifically focus on safe and energy-efficient vehicle control methods, which is a challenging problem due to uncertainties in the system, nonlinear system dynamics, and non-convexity in the decision making problem. The problem is aggravated when these automated vehicles work in close proximity to human-operated vehicles. This research aims at addressing these challenges by developing new stochastic optimal control methods and developing a suggestion-based control framework that exploits inter-vehicular communication.