This study introduces Trust-Aware Reward Shaping (TARS), an interactive reinforcement learning method that uses real-time trust as an additional reward signal for automated lane changes. The approach combines preferred driving styles with trust dynamics to generate vehicle behavior that responds to changes in user trust.