Driver Carelessness Detection Using Gaze and Pupil Response
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Solution Overview
Problem
Conventional carelessness warning systems for drivers rely on uniform determination parameters, leading to improper or false warnings due to arbitrary definitions, failing to accurately assess the driver's carelessness level and timing based on individual variations.
Innovation Solution
A carelessness determination method and smart cruise control association system that analyzes a driver's biological state, including line of sight, pupil size changes, and external environment information, to dynamically assess carelessness without uniform parameters, and automatically switches to smart cruise control when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If uniform determination parameters are used for all drivers, then the system is simple to operate, but the accuracy of carelessness detection deteriorates due to individual variations
Solution Approach 1:
The patent applies local quality by transitioning from uniform determination parameters to driver-specific parameters. The system captures individual driver characteristics (eye movement patterns, pupil size variations, line of sight behavior) and uses these personalized parameters for carelessness detection, thereby improving accuracy while maintaining system simplicity through automated adaptation.
Solution Approach 2:
The system dynamically changes determination parameters based on individual driver characteristics. Instead of using fixed uniform parameters, the system adjusts parameters such as eye closing time thresholds, gaze deviation angles, and pupil size criteria according to each driver's biological state and driving behavior patterns, resolving the contradiction between simplicity and accuracy.
2Ease of manufacture
If arbitrary determination parameters are defined by manufacturers, then the system is easy to manufacture, but false warnings occur due to erroneous determination
Solution Approach 1:
The system implements feedback mechanisms where driver responses to warnings and actual driving outcomes are continuously monitored. This feedback loop allows the system to learn from false warnings and adjust determination parameters accordingly, reducing erroneous determinations while maintaining ease of manufacture through automated parameter optimization rather than manual tuning.
Solution Approach 2:
The system performs self-service by automatically optimizing determination parameters based on collected driving data and individual driver characteristics. Rather than requiring manufacturers to arbitrarily define parameters, the system autonomously adapts parameters to minimize false warnings and improve reliability, while the manufacturing process remains simple.
3Device complexity
If conventional camera-based methods are used, then the device complexity is low, but the measurement precision of driver state assessment deteriorates
Solution Approach 1:
The patent merges multiple detection approaches by combining conventional camera-based line of sight tracking with physiological measurements such as pupil size monitoring. This integration enhances measurement precision by cross-validating multiple indicators of driver attention and state, while the system remains relatively simple by using existing camera technology and adding complementary sensors.
Data Source
AI summary
The present disclosure relates to a carelessness determination method based on the analysis of a driver's biological state and an SCC association system and method using the same, which can determine a driver's carelessness state by using a line of sight of the driver, a change in the size of the pupil of the driver according to a vehicle speed, and external environment information and can forcedly change the subject of driving into a vehicle based on SCC when the driver's carelessness state is determined as a driver carelessness situation.