Don't Get Stuck: A Deadlock Recovery Approach

Don't Get Stuck: A Deadlock Recovery Approach Abstract-- When multiple agents share space, interactions can lead to deadlocks, where no agent can advance towards its goal. This STL-MPPI framework ensures system compliance to specifications and dynamics while ensuring the safety of the resulting maneuvers, indicating a strong potential for application to complex traffic scenarios (and rules) in practice. Validation studies are conducted in simulations and on scaled cars, respectively, to demonstrate the effectiveness of the proposed algorithm. These unable to move forward. This presents concerns for traffic situations, which require intricate agent prediction, routing flow and safety, especially in urban settings where real-time and rerouting strategies, and navigation through expanded decision-making is crucial and where AVs must coexist with dynamic spaces, make resolving deadlocks a complex issue human-driven vehicles, each relying on distinct decisionmaking for AV technology.