2024/12/20 by Lin, Yuanfei, Xing, Zekun, Han, Xuyuan +1 · 1 citation
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Robotics (cs.RO)
paper · doi:10.48550/arxiv.2412.15837
Complying with traffic rules is challenging for automated vehicles, as numerous rules need to be considered simultaneously. If a planned trajectory violates traffic rules, it is common to replan a new trajectory from scratch. We instead propose a trajectory repair technique to save computation time. By coupling satisfiability modulo theories with set-based reachability analysis, we determine if and in what manner the initial trajectory can be repaired. Experiments in high-fidelity simulators and in the real world demonstrate the benefits of our proposed approach in various scenarios. Even in complex environments with intricate rules, we efficiently and reliably repair rule-violating trajectories, enabling automated vehicles to swiftly resume legally safe operation in real time.