Before revision:  Extensive Monte-Carlo simulations show the performance of a trained SR2L against the baseline approach. The SR2L framework achieves at least one order fewer episodes to learn the policy than the conventional RL framework .
After revision:  Extensive Monte-Carlo simulations show the performance of a trained SR2L consistently outperforms conventional IAC and the motion planner itself as the baselines .