Autonomous Vehicle Trajectory Display With Adaptive Trust Zones

The patent introduces trust zones as an intermediary visual element between the autonomous vehicle system and the passenger. These trust zones are displayed on the display device to show the spatial boundaries within which the autonomous system feels confident operating. This intermediary visualization mediates the relationship by making the abstract autonomous decision-making process concrete and understandable, thereby building passenger trust without reducing automation capability.

The system implements feedback by continuously monitoring passenger trust indicators (such as trust zone selections and intervention patterns) and adjusting the trust zone parameters accordingly. When passengers show signs of discomfort or unnecessary intervention, the system can modify trust zone sizes or positions to better align with passenger comfort levels, creating a closed-loop feedback mechanism that enhances trust while maintaining automation.

The patent segments the complex autonomous navigation information into distinct, manageable visual components: trust zones, trajectories, and detected objects. Each element is displayed separately and clearly on the display device, allowing passengers to understand one aspect at a time rather than overwhelming them with all information simultaneously. This segmentation reduces perceived complexity while maintaining comprehensive information delivery.

The system applies local quality by providing detailed trajectory and trust zone information only in regions or situations where it is most relevant to passenger understanding. For example, trust zones are prominently displayed when the vehicle is operating near boundaries or in uncertain environments, while simpler displays may suffice during routine autonomous operation. This selective information presentation reduces overall system complexity while maintaining trust-building effectiveness.

The system performs preliminary action by pre-defining multiple trust parameter sets corresponding to different passenger preference profiles (e.g., conservative, moderate, aggressive trust levels). Instead of implementing complex real-time dynamic adjustment algorithms, the system allows passengers to select from these pre-configured trust parameter sets before autonomous operation begins. This preliminary configuration approach achieves adaptability while significantly reducing control system complexity compared to fully dynamic adjustment.

The system implements dynamics by allowing trust parameters to be adjusted during operation based on detected passenger feedback, such as unnecessary interventions or expressed comfort levels. The trust zones and trajectories are dynamically modified in response to these feedback signals, enabling the system to adapt to passenger preferences in real-time. This dynamic adjustment is implemented through relatively simple rule-based modifications rather than complex algorithms, balancing adaptability with controlled system complexity.