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Adaptive Collision Avoidance in Mixed-Traffic Autonomous Driving via Hamilton-Jacobi Reachability and Learning-Based Techniques
Introduction When it comes to the safety of autonomous vehicles (AV), developing algorithms that balance conservatism and performance is the key to achieve methods that allow Avs to be integrated with human driven ones.One of the most promising techniques is the Hamilton-Jacobi (HJ) backward reachability analysis (based on dynamic programming and differential games), which allows Read more
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Agents for Competitive Multi-Agent Autonomous Vehicle Racing: Learning-based vs Model-base
High-speed, multi-agent autonomous vehicle racing demands agents that can make split-second decisions while strategically interacting with unpredictable opponents. This thesis will develop a learning-based racing agent and a model-based one both capable of long-term reasoning, balancing raw speed with tactical maneuvers, and benchmark their performance under head-to-head competition. Requirements and tools Contacts: Michael Khayyat, Stefano Read more