Autonomous Vehicle Driver Fitness Detection and Mode Intervention
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Solution Overview
Problem
Existing systems fail to accurately determine when an individual is unfit to operate a vehicle and effectively dissuade them from doing so, despite advancements in vehicle sensors and data generation.
Innovation Solution
A computer-implemented method and system that uses image sensors and sensor data to identify individuals within a vehicle, analyze their state, and generate control signals to alter the autonomous operation mode, providing real-time notifications to dissuade unfit operators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vehicle sensors and data generation capabilities are increased, then the ability to detect driver state improves, but the system complexity and cost increase
Solution Approach 1:
The patent applies multi-functionality by using a single image sensor to perform multiple tasks: identifying the driver, detecting driver state (drowsiness, intoxication), and generating operational data. This eliminates the need for separate sensors for each function, thereby improving measurement precision while avoiding increased system complexity
Solution Approach 2:
The existing vehicle sensors and image processing capabilities are leveraged to serve the additional function of driver state monitoring. The system uses already-present computational resources and sensor infrastructure to perform driver identification and state assessment, avoiding the need for entirely new hardware systems
2Reliability
If real-time driver state monitoring is implemented, then safety improvements are achieved, but processing time and computational load increase
Solution Approach 1:
The system performs preliminary actions by continuously capturing and pre-processing image data in real-time, maintaining a ready state for rapid driver state assessment. Image sensors continuously capture data and basic processing occurs in advance, enabling quick determination of driver fitness without delaying vehicle operation
Solution Approach 2:
The system implements partial monitoring by focusing computational resources on key indicators of driver fitness such as eye closure detection, facial color analysis, and head position monitoring. Rather than analyzing every aspect of driver behavior, the system targets specific partial indicators that most strongly correlate with driver unfitness, reducing overall processing time while maintaining safety
3Object-affected harmful factors
If autonomous operation mode is altered based on driver state, then hazardous situations are reduced, but the loss of driver control and autonomy increases
Solution Approach 1:
The system applies preliminary anti-action by implementing gradual escalations of autonomous intervention. Rather than immediately removing driver control, the system first provides warnings and alerts to the driver, then progressively increases autonomous operation levels only if the driver fails to respond or remains unfit, thereby reducing hazardous situations while preserving driver control as long as possible
Solution Approach 2:
The system employs feedback mechanisms by continuously monitoring driver responses to warnings and alerts, and by providing real-time information about driver state assessments. This feedback loop allows the system to adjust the level of autonomous intervention based on driver condition and response, maintaining driver control when appropriate while ensuring safety when necessary
Data Source
AI summary
Systems and methods for improving vehicular safety are provided. According to certain aspects, an electronic device may receive and analyze image data depicting an individual located within a vehicle. The electronic device may also access certain data related to a condition of the individual, and may accordingly determine whether the individual is fit to operate the vehicle. If the individual is unfit to operate the vehicle, the electronic device may alter autonomous operation of the vehicle.