Autonomous Vehicle Route Interface for Consequential Object Filtering
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Solution Overview
Problem
Current user interfaces in autonomous vehicles do not effectively communicate to passengers that the vehicle is monitoring potential hazards and considering path adjustments, leading to a lack of confidence due to cluttered displays showing inconsequential objects and low-confidence strategies.
Innovation Solution
A method that filters and presents only consequential objects and path adjustment options to the user interface, determining object type and position relative to the vehicle, ensuring that only relevant information is displayed to enhance passenger confidence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If detailed object detection results and path adjustment strategies are displayed on the user interface, then information completeness is improved, but device complexity and passenger confusion increase
Solution Approach 1:
The user interface is segmented into distinct functional zones: a navigation route display area showing the vehicle's path, and a separate object detection display area showing filtered hazard information. This segmentation allows comprehensive information to be presented without overwhelming the passenger, as each zone serves a specific purpose and is visually distinct.
Solution Approach 2:
The system extracts and filters only the most consequential detected objects and path adjustment strategies for display. Inconsequential objects (e.g., distant stationary objects, minor road features) are excluded from the display, while critical hazards (e.g., pedestrians, animals, vehicles in blind spots) are prominently shown. This extraction principle reduces display clutter while maintaining information completeness for safety-critical elements.
2Reliability
If all detected objects are displayed on the user interface, then monitoring coverage is improved, but passenger confidence decreases due to inconsequential objects
Solution Approach 1:
The system applies different display qualities to different detected objects based on their significance. Critical objects (pedestrians, animals, vehicles in blind spots, obstacles in navigation path) are displayed with high visibility and detailed information. Inconsequential objects (distant stationary objects, road markings, vegetation) are either omitted or displayed with minimal information. This local quality differentiation maintains monitoring coverage while enhancing passenger confidence by showing only relevant hazards.
3Reliability
If comprehensive path adjustment strategies are presented, then decision quality is improved, but device complexity increases due to multiple strategy options
Solution Approach 1:
The user interface dynamically adjusts the number and detail of path adjustment strategies displayed based on the situation. In high-confidence scenarios with clear hazards, the system displays multiple strategy options (e.g., brake, steer left, steer right) with their respective confidence levels. In low-uncertainty situations, the system displays only the primary intended action. This dynamic adaptation reduces complexity while maintaining comprehensive decision quality.
4Loss of information
If the user interface shows all navigation route details, then route awareness is improved, but information overload occurs reducing passenger confidence
Solution Approach 1:
The system extracts and displays only the most relevant portions of the navigation route information. Instead of showing the entire route, the interface focuses on the immediate upcoming path segments, critical turns, and areas with detected hazards. This extraction maintains route awareness by showing necessary navigation details while avoiding information overload by omitting redundant or distant route information.
Data Source
AI summary
Various technologies described herein pertain to causing presentation on a user interface of an immediate portion of a navigation route of an autonomous vehicle. A computing system of the autonomous vehicle determines whether an object detected by sensor(s) of the autonomous vehicle proximate to the immediate portion of the navigation route are of a type and relative position defined as one of consequential and inconsequential for a human passenger. In response to determining that an object has both a type and relative position defined as consequential, the computing system causes presentation on the user interface a representation of the object relative to the immediate portion of the navigation route to provide a confidence engendering indication that the autonomous vehicle has detected the object. Otherwise if inconsequential, presentation on the user interface of any representation of the object is not caused by the computing system to avoid creating a confusing presentation.