When multiple agents share space, interactions can lead to deadlocks, where no agent can advance toward their goal. This paper addresses this challenge with a deadlock recovery strategy. In particular, the proposed algorithm integrates hybrid- A⋆, STL, and MPPI controller – where hybrid-A⋆ generates a reference path, STL defines a goal (deadlock avoidance) and constraints (w.r.t. traffic rules), and MPPI refines the path and speed accordingly. This STL-MPPI framework ensures the sys- tem compliance and safety of the resulting maneuvers, indicating a strong potential for complex traffic scenarios (and rules) in practice. The validation studies are conducted in simulations and with real scaled cars, respectively, to showcase the effectiveness of the proposed algorithm.