In-Vehicle Intent Display for Autonomous Occupant Awareness
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Solution Overview
Problem
Autonomous vehicles lack effective means to communicate their intentions and interactions with the surrounding environment to occupants, leading to a lack of transparency and potential safety concerns.
Innovation Solution
The system generates visual representations of detected objects and intentions using color-coded indicators on an in-vehicle display, filtering out irrelevant information to reduce clutter and enhance occupant understanding of the vehicle's actions and environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the autonomous vehicle displays all detected objects and calculations to the operator, then the operator gains complete information about vehicle reasoning, but the display becomes cluttered and difficult to interpret
Solution Approach 1:
The display system segments information by spatial relationship, showing only objects within a predefined distance threshold from the vehicle. This divides the complete environmental data into relevant and irrelevant portions, maintaining information transparency for critical objects while reducing overall display complexity by excluding distant objects.
Solution Approach 2:
The system applies different display qualities to different objects based on their relevance. Objects within the threshold distance receive enhanced visual treatment (higher priority display), while objects beyond the threshold are excluded or minimally represented. This local differentiation optimizes the display for operator understanding of critical vehicle interactions.
2Reliability
If the vehicle displays detailed sensor data and environmental information, then the operator understands the vehicle's perception capabilities, but the operator may become overwhelmed by excessive data
Solution Approach 1:
The system extracts and displays only the most relevant features of detected objects—specifically their spatial relationship to the vehicle and basic identification. This extraction approach provides sufficient information for operator confidence in vehicle perception while eliminating extraneous sensor data that would complicate information processing.
Solution Approach 2:
Rather than displaying complete sensor data sets, the system applies partial action by showing only a subset of detected objects (those within threshold distance). This partial display provides adequate information for operator confidence without the cognitive overload of comprehensive data presentation.
3Loss of information
If the autonomous vehicle communicates all its intentions and planning calculations, then the operator understands vehicle decision-making, but the communication becomes complex and hard to comprehend
Solution Approach 1:
The intent communication system segments information by filtering objects based on distance threshold. Only objects within the threshold are included in intent communications, dividing the complete set of potential interactions into manageable segments. This maintains transparency of vehicle intentions regarding critical objects while reducing communication complexity.
Solution Approach 2:
Instead of presenting complex calculation data and reasoning processes directly, the system inverts the approach by presenting simplified visual representations of intended actions on relevant objects. This inversion transforms complex computational information into intuitive visual cues about vehicle intent.
Data Source
AI summary
Aspects of the present disclosure relate to a vehicle for maneuvering an occupant of the vehicle to a destination autonomously as well as providing information about the vehicle and the vehicle's environment for display to the occupant.