AV Software Interaction Evaluation for Trip-Specific Risk Mitigation
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Solution Overview
Problem
Existing systems fail to effectively evaluate and mitigate risks associated with interactions between autonomous vehicle software ecosystems and environmental conditions, leading to potential adverse performance outcomes.
Innovation Solution
A system and method that aggregates data from multiple autonomous vehicles to identify correlations between software applications and environmental conditions, enabling the detection of adverse outcomes and executing remedial actions to avoid them.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data from multiple autonomous vehicles is aggregated to identify software-environment correlations, then the ability to detect adverse outcomes improves, but the system complexity increases
Solution Approach 1:
The system segments the complex evaluation task into distinct functional modules: data collection module that gathers software version information and environmental condition data from multiple vehicles, correlation analysis module that identifies relationships between software configurations and environmental factors, and risk evaluation module that assesses adverse outcome probabilities. This segmentation manages system complexity while maintaining comprehensive multi-vehicle data analysis capabilities
Solution Approach 2:
The patent introduces an intermediary evaluation system that acts as a mediator between individual autonomous vehicles and the central analysis platform. This intermediary layer standardizes data collection from multiple vehicles, processes information uniformly, and presents consolidated results to the analysis system, thereby managing complexity while enabling comprehensive multi-vehicle correlation detection
2Measurement precision
If software ecosystem data and environmental conditions are compared to identify interactions, then the precision of risk assessment improves, but the computational resources required increase
Solution Approach 1:
The system performs preliminary actions by pre-collecting and organizing software ecosystem data and environmental condition data from multiple vehicles before conducting correlation analysis. Data is structured and indexed in advance with defined schemas for software versions, configurations, and environmental parameters, enabling efficient querying and comparison without requiring intensive real-time computational resources during actual risk assessment
Solution Approach 2:
The patent transforms complex software-environment interaction data into standardized parameters and metrics that can be efficiently processed. Software configurations are converted into discrete version parameters, environmental conditions are quantified into measurable parameters (temperature, humidity, terrain type), and interaction effects are expressed as standardized risk scores, reducing computational complexity while maintaining assessment precision
3Reliability
If correlations between software applications and environmental conditions are identified, then the safety of autonomous vehicles improves, but the time required for evaluation increases
Solution Approach 1:
The system implements preliminary anti-action by proactively identifying software-environment correlations and potential adverse outcomes before they manifest as actual safety incidents. The correlation analysis module continuously monitors patterns in aggregated data from multiple vehicles, detecting risky software configurations in specific environmental conditions ahead of time, enabling preventive software updates and risk mitigation before accidents occur
Solution Approach 2:
The patent establishes a feedback mechanism where correlation analysis results from multiple vehicles are continuously fed back into the evaluation system. Identified software-environment correlations update the risk assessment models, which then guide targeted data collection and analysis priorities, creating an iterative process that improves evaluation efficiency over time while maintaining enhanced safety through accumulated knowledge
Data Source
AI summary
An autonomous vehicle (AV) computing device including at least one processor may be provided. The at least processor may be programmed to (i) receive a proposed trip including a destination location and a departure time, (ii) determine environmental conditions data based on the destination location and the departure time, (iii) retrieve current software ecosystem data for the AV, (iv) retrieve aggregated data for a plurality of AVs, the aggregated data including a plurality of correlations, each correlation including a) an interaction between at least one software application and at least one environmental condition and b) an adverse performance outcome associated with the interaction, (v) compare the environmental conditions data for the proposed trip and the current software ecosystem data for the AV to the plurality of correlations to identify an adverse performance outcome, and (vi) execute a remedial action to avoid the adverse performance outcome.