Integrating Deep Reinforcement Learning with Model-based Path Planners for Automated Driving

Automated driving in urban settings is challenging. Human participant behavior is difficult to model, and conventional, rule-based Automated Driving Systems (ADSs) tend to fail when they face unmodeled dynamics... (read more)

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