Vehicle Driving State Detection System with Adaptive Thresholds
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Solution Overview
Problem
Current driving state detection systems face reliability issues due to insufficient lighting affecting facial image detection and variability in driving behaviors, which hinder continuous and accurate monitoring of vehicle states, especially under high-speed conditions.
Innovation Solution
A system comprising a driver monitoring unit for real-time image capture, a vehicle monitoring unit for continuous operation data collection, and a control unit that determines driver and vehicle danger conditions using facial features and vehicle parameters, providing adaptive notification signals and dynamically updating deviation ranges based on driving behavior and traffic conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If facial image detection is used to monitor driver concentration, then driver state can be detected, but detection reliability deteriorates under insufficient lighting conditions (tunnels, night)
Solution Approach 1:
The patent combines facial image detection with vehicle state detection into a unified driving state detection system. The control unit integrates data from both facial recognition (driver concentration) and vehicle state parameters (steering wheel angle, brake pedal position) to comprehensively monitor driving state, ensuring reliable detection regardless of lighting conditions.
Solution Approach 2:
The control unit acts as an intermediary that processes and correlates data from multiple sources. It uses vehicle state parameters as complementary indicators to infer driver concentration level, especially when facial detection is compromised by poor lighting. This intermediary processing enables reliable detection by cross-validating multiple data streams.
2Duration of action of stationary object
If vehicle state detection is used to monitor driving state, then continuous monitoring is achieved without lighting dependence, but analysis complexity increases under high-speed driving conditions
Solution Approach 1:
The patent segments the detection system into distinct functional modules: facial image detection unit, vehicle state detection unit, and control unit. Each module independently processes specific data types (facial features, steering wheel angle, brake pedal position), reducing the complexity of analyzing all parameters simultaneously while enabling continuous comprehensive monitoring.
Solution Approach 2:
The control unit dynamically adjusts detection sensitivity and parameter thresholds based on driving conditions. Under high-speed conditions, the system adapts its analysis criteria to maintain appropriate detection accuracy without excessive computational complexity, balancing continuous monitoring with processing requirements.
3Measurement precision
If detection thresholds are set strictly to ensure high accuracy, then detection precision improves, but false alarms increase due to individual driving behavior variations
Solution Approach 1:
The patent employs multiple detection parameters (facial features, steering wheel angle, brake pedal position, seat belt status) that can be individually adjusted and weighted. The control unit changes parameter thresholds and detection criteria based on the specific combination of parameters being evaluated, allowing optimization of precision while reducing false alarms through multi-parameter correlation analysis.
Solution Approach 2:
The system incorporates feedback mechanisms where the control unit continuously monitors driving state and adjusts detection criteria based on observed patterns. By analyzing the temporal and contextual relationships between different parameters, the system learns to distinguish between normal driving variations and actual dangerous states, reducing false alarms while maintaining precision.
Data Source
AI summary
A system is adapted for detecting a driving state of a vehicle, and is operable to obtain real-time image frames corresponding to a driver of the vehicle for determining if the driver is in a dangerous driving state, to obtain operation information of the vehicle for determining if the vehicle is being operated in a dangerous condition when the driver is unable to be identified by the system, and to provide a notification when the driving state of the vehicle is determined to be dangerous.