Vehicle CAN-Based Impaired Driving Detection With Dynamic Thresholds
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Solution Overview
Problem
Existing methods for detecting impaired driving, such as using in-cabin image detectors and breath alcohol detectors, are unreliable due to potential data alteration or instability, necessitating a more robust and accurate method.
Innovation Solution
Utilizing controller area network (CAN) data from a vehicle, combined with location data, to determine impaired driving by comparing it to reference data and adjusting deviation thresholds based on the vehicle's location, and implementing a vehicle intervention system to control operations when impairment is detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensor data (in-cabin image detectors, touch alcohol detectors, breath alcohol detectors) is used for detecting impaired driving, then detection capability is provided, but reliability is reduced due to data alteration or instability
Solution Approach 1:
The patent introduces CAN data as an intermediary indicator that indirectly reflects driver impairment status through driving behavior patterns rather than directly measuring alcohol or drug presence. This mediator approach bypasses the reliability issues of direct sensors while maintaining detection capability through behavioral analysis of steering, acceleration, and braking patterns
Solution Approach 2:
The patent replaces the mechanical/sensor-based detection system (image detectors, breath analyzers) with an electronic data analysis system that processes CAN bus signals. This substitution uses existing vehicle electronic infrastructure to achieve more reliable detection without adding complex sensor hardware
2Measurement precision
If a fixed threshold value is used for determining impaired driving, then determination process is simple, but accuracy is reduced due to location-specific variations
Solution Approach 1:
The patent implements dynamic threshold adjustment based on location data, where the threshold value changes according to the vehicle's geographic position. This allows the system to adapt to location-specific driving patterns and alcohol access environments, improving detection accuracy without requiring complex manual calibration
Solution Approach 2:
The system incorporates feedback loops where location data continuously informs threshold adjustments. The determination unit receives location information and dynamically modifies the threshold value accordingly, creating a closed-loop system that automatically adapts to environmental conditions affecting driving behavior
Data Source
AI summary
Methods and systems for determining impaired driving is provided. The methods include acquiring controller area network (CAN) data and location data of a vehicle, comparing the CAN data to a reference data associated with driving behavior of a driver of the vehicle, determining the driver is impaired driving in response to determining that a level of deviation of the CAN data from the reference data is greater than a threshold value, changing the threshold value in response to determining that the location data indicates the vehicle is located in an area associated with a place offering access to alcohol, and controlling operations of the vehicle in response to determining that the driver is impaired driving.