Autonomous Vehicle Handover Control Based on Driver Risk Profiles
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Solution Overview
Problem
Existing insurance premium determination methods do not account for the use of autonomous vehicle operation features, leading to inadequate risk assessment and pricing for vehicles with autonomous capabilities.
Innovation Solution
A system that evaluates the risk levels associated with autonomous vehicle operation features and human operator behavior, determining when to engage or disengage these features based on risk levels, and adjusts insurance premiums accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional insurance premium determination methods are used, then the pricing process is simple, but the risk assessment accuracy is insufficient for autonomous vehicles
Solution Approach 1:
The patent segments the risk assessment into multiple independent components: autonomous feature risk levels, operator behavior risk levels, and environmental risk factors. Each component is evaluated separately using specific sensors and algorithms, then combined to form a comprehensive risk profile. This segmentation enables precise measurement of each risk dimension without overwhelming system complexity.
Solution Approach 2:
The patent introduces an intermediary risk assessment system that acts as a mediator between traditional insurance pricing and autonomous vehicle operation data. This intermediary layer processes sensor data from autonomous features, operator behavior, and environmental conditions, translating them into standardized risk scores that can be integrated into existing insurance frameworks without requiring complete system redesign.
2Measurement precision
If autonomous vehicle operation features are monitored and evaluated, then insurance pricing accuracy improves, but the system complexity and data processing requirements increase
Solution Approach 1:
The patent implements a universal monitoring platform that serves multiple functions: it tracks autonomous feature performance, analyzes operator behavior patterns, assesses environmental risk factors, and generates insurance pricing data all through a single integrated system. This multi-functional approach consolidates what could be separate complex systems into one cohesive platform, reducing overall system complexity while maintaining comprehensive monitoring capabilities.
Solution Approach 2:
The patent transforms complex sensor data and operational parameters into standardized risk score parameters that are suitable for insurance pricing. By converting diverse data types (sensor readings, behavior patterns, environmental conditions) into unified risk parameters, the system simplifies data processing and integration while preserving the precision needed for accurate pricing.
3Measurement precision
If risk levels are continuously monitored and premiums are dynamically adjusted, then insurance pricing reflects actual risk more accurately, but the computational requirements and processing time increase
Solution Approach 1:
The patent performs preliminary risk assessment by continuously monitoring autonomous feature performance and operator behavior in real-time, establishing baseline risk profiles before insurance periods begin. This preliminary action allows the system to pre-calculate risk factors and prepare pricing adjustments in advance, reducing the computational burden and processing time required when actual premium adjustments need to be made.
Solution Approach 2:
The patent implements a feedback mechanism where risk assessment results from previous monitoring periods are fed back into the pricing model to inform future premium adjustments. This feedback loop allows the system to learn from historical data and refine risk predictions over time, reducing the need for complex real-time calculations while maintaining pricing accuracy through iterative improvement.
Data Source
AI summary
According to certain aspects, a computer-implemented method for operating an autonomous or semi-autonomous vehicle may be provided. With the customer's permission, an identity of a vehicle operator may be identified and a vehicle operator profile may be retrieved. Operating data regarding autonomous operation features operating the vehicle may be received from vehicle-mounted sensors. When a request to disable an autonomous feature is received, a risk level for the autonomous feature is determined and compared with a driver behavior setting for the autonomous feature stored in the vehicle operator profile. Based upon the risk level comparison, the autonomous vehicle retains control of vehicle or the autonomous feature is disengaged depending upon which is the safer driver—the autonomous vehicle or the vehicle human occupant. As a result, unsafe disengagement of self-driving functionality for autonomous vehicles may be alleviated. Insurance discounts may be provided for autonomous vehicles having this safety functionality.