Driver Profile Filters for Personalized Autonomous Vehicle Actions
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous vehicles often have pre-set driving personalities that do not align with individual drivers' preferences, and adapting to new environments requires personalized driving styles that existing systems fail to accommodate.
Innovation Solution
A system and method for generating and replicating driver profiles by analyzing driving actions, deriving filters from these actions, and applying them to adjust vehicle decisions to match the driver's style, incorporating safety filters to ensure compliance with safe driving thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If pre-set driving personalities are used in autonomous vehicles, then system complexity is reduced and ease of manufacture is improved, but adaptability to individual driver preferences and environmental contexts deteriorates
Solution Approach 1:
The system dynamically adjusts the autonomous vehicle's driving behavior by switching between multiple pre-defined driving personality profiles (e.g., aggressive, conservative, sporty) based on real-time context detection. The context detection module analyzes environmental factors, driver preferences, and traffic conditions to select and adapt the appropriate driving personality, making the system flexible and adaptable without requiring complex custom programming for each scenario.
Solution Approach 2:
The system changes key driving parameters such as acceleration rates, braking force, steering responsiveness, and following distance based on the selected driving personality profile. By modifying these parameters dynamically, the vehicle can adapt to different driving styles and environmental contexts while maintaining a manageable system architecture that relies on parameter adjustment rather than complete system reconfiguration.
2Adaptability or versatility
If driver profiles with multiple filters are implemented to approximate driving actions, then adaptability to driver preferences is improved, but device complexity increases
Solution Approach 1:
The driver profile system is segmented into multiple independent filter modules, each responsible for a specific aspect of driving behavior (e.g., acceleration filter, braking filter, steering filter). This segmentation allows the system to manage complexity by breaking down the overall driver personality approximation into smaller, modular components that can be independently configured, adjusted, and maintained without affecting the entire system.
Solution Approach 2:
The filter-based architecture provides universal applicability across different driving scenarios and vehicle types. The same filter framework can approximate various driving personalities by adjusting filter parameters, making the system multi-functional without requiring separate systems for each driving style. This universal approach reduces overall complexity by using a single adaptable framework rather than multiple specialized systems.
Data Source
AI summary
A method includes receiving a request to initialize a driver profile of a target driver for a vehicle, the driver profile including a plurality of filters each configured to approximate a driving style of the target driver. The method also includes initializing the driver profile of the target driver, obtaining sensor data indicating a context of the vehicle that triggers a vehicle decision to perform a vehicle action, and identifying a filter of the plurality of filters that corresponds to the vehicle action. The method further includes applying the filter to the vehicle action to generate an adjusted action that approximates a driving action of the target driver, applying a safety filter to the adjusted action to generate a safety adjusted action, and instructing the vehicle to perform the vehicle decision including the safety adjusted action.