Occupant Reaction Monitoring for Vehicle Situational Awareness Validation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Automated and autonomous vehicle systems face challenges in maintaining accurate situational awareness, particularly when sensors encounter lighting limitations or edge cases beyond their trained data, leading to incomplete or inaccurate perceptions of the surrounding environment.
Innovation Solution
A system that monitors vehicle occupant reactions, such as physiological and behavioral responses, to correlate with perceived environmental attributes, allowing for the identification of mismatches between the vehicle's situational awareness and actual environmental conditions, and executes responsive actions to address these inconsistencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If sensors and processing routines are used to generate situational awareness, then the vehicle can operate autonomously/semi-autonomously, but the situational awareness may become incomplete or inaccurate under certain conditions
Solution Approach 1:
The system introduces feedback by monitoring occupant reactions (physiological and behavioral) and using this information to validate or correct the vehicle's situational awareness. The monitoring module continuously observes occupant responses and feeds this data back to the introspection system, which compares expected reactions based on sensor data with actual reactions, creating a closed-loop verification mechanism that improves reliability of situational awareness
Solution Approach 2:
The occupant serves as an intermediary validation point between the vehicle's sensor system and the actual environmental conditions. The monitoring module uses the occupant as a mediator to indirectly verify situational awareness by detecting whether the occupant's reactions align with what the vehicle's sensors perceive, providing an additional layer of verification without requiring direct modification of the sensor system
2Adaptability or versatility
If sensors operate beyond their designed range (e.g., extreme lighting conditions), then the vehicle can function in diverse environments, but sensor accuracy deteriorates
Solution Approach 1:
The system uses feedback from occupant reactions to detect when sensor accuracy may be compromised. When environmental conditions exceed sensor design ranges (such as extreme lighting), the monitoring module detects corresponding occupant reactions that differ from expected patterns, providing feedback that indicates sensor information may be inaccurate even if the sensor is technically functioning
Solution Approach 2:
The system performs self-validation by using the occupant's natural reactions as an automatic verification mechanism. The introspection system continuously self-checks the reliability of its situational awareness by comparing sensor-derived expectations with actual occupant responses, enabling the system to self-identify potential sensor accuracy issues without external intervention
3Speed
If processing routines use training data and programmed correlations, then the vehicle can make rapid decisions, but the reasoning may be inaccurate for edge cases beyond defined understandings
Solution Approach 1:
The system introduces feedback validation for edge cases by monitoring whether occupant reactions align with the processing routine's interpretations. When the vehicle encounters situations beyond its trained understanding, the monitoring module detects occupant reactions that diverge from expected patterns, providing feedback that signals the processing routine may have produced inaccurate reasoning, allowing for subsequent re-evaluation or human intervention
4Device complexity
If the vehicle system does not monitor occupant reactions, then the system complexity is reduced, but the ability to identify incomplete situational awareness is diminished
Solution Approach 1:
The system introduces an intermediary monitoring layer that uses the occupant as a mediator to validate situational awareness. The monitoring module and introspection system act as intermediaries between the vehicle's autonomous systems and the environment, using the occupant's natural reactions as an indirect but effective validation mechanism without requiring direct modification of the core autonomous driving systems
Data Source
AI summary
System, methods, and other embodiments described herein relate to identifying when a situational awareness of a vehicle is inconsistent with a surrounding environment. In one embodiment, a method includes analyzing occupant sensor data about at least one occupant of the vehicle to generate a reaction level of the occupant. The reaction level characterizes at least a current response of the occupant to the surrounding environment and control of the vehicle within the surrounding environment. The method includes comparing an expected reaction for the occupant with the reaction level to determine whether the reaction level of the occupant correlates with the situational awareness of the vehicle about the surrounding environment. The method includes, in response to identifying that the reaction level does not correlate with the expected reaction, executing, by the vehicle, a responsive action to account for inconsistencies in the situational awareness of the vehicle.