Autonomous Feature Risk Evaluation Using Virtual Driving Scenarios
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Solution Overview
Problem
Current methods for determining vehicle insurance premiums do not account for the use of autonomous vehicle operation features, which poses a risk assessment challenge.
Innovation Solution
A system and method for testing and evaluating the effectiveness of autonomous vehicle operation features by simulating scenarios in a virtual environment, determining risk levels based on the features' responses, and using these risk levels to adjust insurance premiums.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional premium determination methods are used, then simplicity and ease of operation are maintained, but accuracy and reliability of risk assessment deteriorate because they do not account for autonomous vehicle features
Solution Approach 1:
The system segments the risk assessment process into multiple independent components: autonomous feature identification module, virtual scenario simulation module, feature response evaluation module, and premium calculation module. Each module handles a specific aspect of the assessment, allowing complex analysis to be broken down into manageable segments that can be processed independently and combined for final risk determination.
Solution Approach 2:
The patent introduces a virtual environment simulation system as an intermediary between the autonomous vehicle features and the risk assessment process. This intermediary creates controlled virtual scenarios that safely evaluate feature responses without requiring real-world testing, thereby improving assessment accuracy while containing system complexity within a simulated framework rather than requiring complex physical testing infrastructure.
2Reliability
If virtual environment testing is implemented, then reliability of feature evaluation is improved, but loss of time in testing and evaluation increases
Solution Approach 1:
The system performs preliminary evaluation of autonomous features by testing them in virtual environments before actual deployment or insurance underwriting. Virtual scenarios are pre-configured to represent various driving conditions and edge cases, allowing the system to assess feature reliability in advance without requiring extensive real-world road testing, thus reducing overall evaluation time while maintaining reliability.
Solution Approach 2:
The patent creates virtual copies of driving scenarios and vehicle environments to replicate real-world conditions without the time constraints and safety risks of physical testing. These digital twins and simulated environments allow rapid iteration and evaluation of autonomous features across numerous scenarios simultaneously, significantly accelerating the reliability assessment process compared to traditional road testing methods.
3Measurement precision
If comprehensive feature monitoring is performed, then measurement precision of risk levels is improved, but device complexity and data processing requirements worsen
Solution Approach 1:
The system extracts and isolates specific autonomous features for individual evaluation, separating them from the complex whole vehicle system. Each feature (e.g., automatic braking, lane keeping, adaptive cruise control) is tested independently in the virtual environment, allowing precise measurement of each feature's contribution to risk without the confounding complexity of analyzing the entire autonomous vehicle system as a unified whole.
Solution Approach 2:
The patent employs parameter changes by varying scenario conditions, feature configurations, and environmental factors in the virtual testing framework. By systematically adjusting parameters such as weather conditions, traffic density, feature activation states, and scenario types, the system achieves comprehensive risk assessment with high measurement precision while managing complexity through controlled parameter variation rather than uncontrolled system complexity.
Data Source
AI summary
Methods and systems for monitoring use and determining risks associated with operation of a vehicle having one or more autonomous operation features are provided. According to certain aspects, operating data may be recorded during operation of the vehicle. This may include information regarding the vehicle, the vehicle environment, use of the autonomous operation features, and/or control decisions made by the features. The control decisions may include actions the feature would have taken to control the vehicle, but which were not taken because a vehicle operator was controlling the relevant aspect of vehicle operation at the time. The operating data may be recorded in a log, which may then be used to determine risk levels associated with vehicle operation based upon risk levels associated with the autonomous operation features. The risk levels may further be used to adjust an insurance policy associated with the vehicle.