  As the advanced driver assistance system (ADAS) functions become more
sophisticated, the strategies that properly coordinate interaction and
communication among the ADAS functions are required for autonomous driving.
This paper proposes a derivative-free optimization based imitation learning
method for the decision maker that coordinates the proper ADAS functions. The
proposed method is able to make decisions in multi-lane highways timely with
the LIDAR data. The simulation-based evaluation verifies that the proposed
method presents desired performance.
