Explore a Stanford seminar on multi-agent systems and traffic negotiation presented by Mrdjan Jankovic of Ford Research. Delve into the complexities of coding negotiation algorithms for autonomous driving and mobile robotics. Learn about Control Barrier Function (CBF) based methods for collision avoidance and their advantages in solving non-convex obstacle avoidance problems. Compare six different CBF-based control policies for a 5-agent, holonomic-robot system, examining their effectiveness in collision avoidance and preventing gridlocks. Analyze the correlation between gridlock prevention and system stability, illustrated through extensive simulations and a vehicle experiment. Gain insights into decentralized multi-agent controllers, centralized CBF controllers, and the PCCA algorithm. Investigate the causes of gridlocks from a stability perspective and explore potential solutions, including the impact of lower barrier bandwidth on traffic flow improvement.