Vehicle Handoff Control via Driver and Environment Profile Comparison
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Solution Overview
Problem
Existing techniques for managing driving modes in autonomous vehicles are inefficient as they rely on predetermined threshold data and pre-fed conditions, failing to adapt effectively to dynamic surrounding environments and driver profiles.
Innovation Solution
A method and system that detect driver attributes and surrounding environment conditions using multiple data capturing modules, compare autonomous and driver profiles, and determine real-time handoff between autonomous and manual driving modes based on environmental data, including GPS and neighboring vehicle data, to optimize vehicle control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If handoff switching is based on predetermined threshold data and pre-fed conditions, then the system can operate with simple decision logic, but the system fails to adapt effectively to dynamic surrounding environments and driver profiles
Solution Approach 1:
The patent implements dynamic handoff decision-making by continuously monitoring multiple parameters including driver profile attributes, surrounding environment conditions, and vehicle operational data. The system adapts its decision logic in real-time based on changing conditions rather than relying on static predetermined thresholds, enabling effective adaptation to dynamic environments while maintaining manageable system complexity through structured data processing.
Solution Approach 2:
The system incorporates feedback mechanisms by continuously comparing actual driving conditions against stored driver profiles and autonomous vehicle profiles. This feedback loop enables the system to learn from past driving patterns and environmental conditions, improving its adaptability over time while using structured comparison algorithms to maintain decision logic complexity at acceptable levels.
2Measurement precision
If multiple data capturing modules are used to detect driver attributes and surrounding environment conditions, then the measurement precision of driving profiles is improved, but the device complexity increases
Solution Approach 1:
The patent employs multiple data capturing modules that serve multiple functions: detecting driver attributes (facial pose, gaze, behavior patterns), monitoring surrounding environment conditions (traffic, terrain, weather), and tracking vehicle operational data. This multi-functionality approach improves measurement precision of driving profiles while managing device complexity by consolidating data processing through a centralized system that handles diverse input sources uniformly.
Solution Approach 2:
The system merges data from multiple capturing modules into unified driver profiles and environment models. By combining facial recognition data, gaze tracking data, behavior pattern data, and environmental sensor data into integrated profiles stored in memory, the system achieves high measurement precision while reducing the apparent complexity through consolidated data structures and processing workflows.
Data Source
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AI summary
The present invention relates to handoff control switching based on a comparison between the driver's driving profile and the autonomous profile indicative of the vehicle control under autonomous driving mode. Driver presence is determined after which the driver is identified using identification attributes extracted. Further, based on a request for handoff initiated, data related to external environment to a vehicle (102) is fetched. Based on the fetched external environment data the autonomous profile and the driver's profile is collected. for the current surrounding environment collected, the optimum driving mode out of the two is determined. After determination, the control is handed off to that driving mode.