CW-ERM: Improving Autonomous Driving Planning with Closed-loop Weighted Empirical Risk Minimization. (arXiv:2210.02174v2 [cs.LG] UPDATED)

The imitation learning of self-driving vehicle policies through behavioral
cloning is often carried out in an open-loop fashion, ignoring the effect of
actions to future states. Training such policies purely with Empirical Risk
Minimization (ERM) can be detrimental to real-world performance, as it biases
policy networks towards matching only open-loop behavior, showing poor results
when evaluated in closed-loop. In this work, we develop an efficient and
simple-to-implement principle called Closed-loop Weighted Empirical Risk
Minimization (CW-ERM), in which a closed-loop evaluation …

arxiv autonomous autonomous driving driving erm loop planning risk