Autonomous Vehicle User Profiles for Cross-Fleet Driving Mode Adaptation
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Solution Overview
Problem
As self-driving vehicle technology advances, managing user profiles across multiple fleets to provide personalized and efficient trip experiences becomes challenging due to varying vehicle capabilities and road conditions, leading to inconsistent user experiences.
Innovation Solution
A full self-driving assistive system that retrieves user profiles and road conditions to configure vehicles appropriately, allowing for seamless transitions between different vehicles and adjusting driving modes based on real-time analytics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If user profiles are managed across multiple fleets with varying vehicle capabilities, then user personalization is improved, but system complexity increases
Solution Approach 1:
The user profile system is designed to be universal across multiple fleets and vehicle types. The profile contains adaptable parameters that can be applied to different vehicle capabilities, allowing one profile to work across diverse autonomous vehicles without requiring fleet-specific profiles, thus achieving personalization without proportional increases in system complexity
Solution Approach 2:
The system manages complexity by parameterizing user preferences and vehicle capabilities. Instead of hard-coded fleet-specific configurations, the patent uses adjustable parameters within the user profile that can be dynamically matched to different vehicle types and capabilities, enabling flexible personalization through parameter adjustment rather than structural complexity
2Reliability
If vehicles are configured based on user profiles and road conditions, then user experience consistency is improved, but processing time increases
Solution Approach 1:
User profiles are pre-configured with preferred settings, comfort parameters, and driving style preferences before the user even requests a vehicle. This preliminary configuration allows the system to quickly match users with appropriate vehicles and apply pre-determined settings, reducing real-time processing time while maintaining experience consistency
Solution Approach 2:
The system continuously polls external sensors for road conditions and uses this feedback to dynamically adjust vehicle configuration and driving mode. This real-time feedback loop enables the system to maintain consistent user experiences by adapting to changing conditions without requiring extensive re-processing of user preferences, as the core profile remains stable and only specific parameters need adjustment
3Reliability
If driving modes are dynamically adjusted based on road conditions, then safety is improved, but control complexity increases
Solution Approach 1:
The autonomous vehicle system automatically monitors road conditions through external sensors and self-adjusts driving modes without requiring manual user input or complex control interfaces. The system serves itself by autonomously determining when to switch between driving modes based on sensor data, thereby improving safety through continuous adaptation while keeping control complexity manageable through automation
Solution Approach 2:
The driving mode system is designed to be dynamic rather than static. The patent implements a flexible control architecture that can smoothly transition between different driving modes based on real-time road conditions. This dynamic approach allows the system to adapt control complexity as needed - using simpler controls in good conditions and more sophisticated controls only when necessary - while maintaining continuous safety monitoring
Data Source
AI summary
A computer hardware system includes a full self-driving (FSD) assistive system for assisting a user with a trip using a FSD autonomous vehicle and hardware processing configured to initiate the following executable operations. Based upon a first user input to a computing device associated with the user, a proposed route of the trip is received. A previously-stored user profile of the user and a context of the trip is retrieved. The vehicle is searched for based upon the user profile, the proposed route, and the context. The vehicle is configured using the user profile. External sensors are polled for road conditions along the route, and the road conditions are forwarded to the vehicle. An onboard analytics device of the vehicle uses the road conditions to change a driving mode of the vehicle.