Develop efficient algorithms for autonomous systems to characterize and actively identify the inconsistencies (e.g., in perception and decision-making) among the interacting agents and to influence the behaviors of the other agents to improve the safety of the overall system.
Develop specification formalisms, control synthesis algorithms, and quantitative verification frameworks for autonomous systems that include learning-based components, operate in uncertain environments, and are subject to conflicting requirements with partially established priorities.
Develop planning and decision-making algorithms with multiple, potentially conflicting objectives.
A path planning system for multi-vehicle domains.