Autonomous Vehicle Control Using Driver State Feedback
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Solution Overview
Problem
Current autonomous vehicle systems lack the ability to effectively monitor driver behavior and adjust operations to prevent accidents by seamlessly transitioning between human control and autonomous driving modes based on real-time monitoring of driver and environmental conditions.
Innovation Solution
A system comprising sensors and a processor that monitor driver behavior and environmental conditions, comparing the data to baseline expectations to determine when to engage or disengage autonomous driving mode, thereby preventing risky driving situations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If autonomous vehicle systems operate without continuous human monitoring, then automation level increases, but safety decreases when drivers are distracted or unable to control the vehicle
Solution Approach 1:
The system continuously monitors driver behavior through sensors (camera, microphone, touch sensors) and provides feedback by comparing real-time data against baseline expectations. When anomalies are detected (e.g., driver distraction, drowsiness, impairment), the system alerts the driver and can request control transfer, creating a closed-loop feedback mechanism that maintains safety while enabling autonomous operation.
Solution Approach 2:
The system dynamically adjusts the level of autonomous operation based on real-time driver state assessment. The processor continuously evaluates sensor data and modifies the autonomous driving mode engagement accordingly - allowing full autonomy when the driver is competent, reducing autonomy when distractions are detected, and maintaining safety through adaptive control transitions.
2Reliability
If the system continuously monitors driver behavior with multiple sensors, then safety increases, but device complexity increases
Solution Approach 1:
The system employs multi-functional sensors that serve multiple purposes. For example, the camera captures images for both driver monitoring and environmental perception, the microphone array detects both driver speech for behavior analysis and external sounds for safety alerts. This multi-functionality reduces the need for separate dedicated sensors, thereby reducing overall system complexity while maintaining comprehensive monitoring capabilities.
Solution Approach 2:
The system combines multiple monitoring functions into a unified processor that handles driver behavior analysis, environmental condition assessment, and autonomous control decisions. By merging these functions into a single integrated processing unit rather than separate systems, the patent reduces device complexity while achieving comprehensive safety monitoring.
3Adaptability or versatility
If the system transitions between human control and autonomous driving modes, then adaptability increases, but loss of time occurs during control transitions
Solution Approach 1:
The system performs preliminary assessments of driver state continuously in the background, so when a transition is needed, the decision can be made immediately based on pre-analyzed data. The processor maintains a ready state with baseline driver behavior data and can quickly determine whether control transfer is necessary, reducing the time lost during transitions between human control and autonomous driving modes.
Data Source
AI summary
A system may include one or more sensors configured to acquire data associated with a driver of a vehicle and a processor. The processor may receive the data and determine whether the data is within a baseline data associated with expected behavior of the driver. The processor may then control one or more operations of the vehicle in response to the data being outside the baseline data.