Steering Wheel Driver Monitoring to Detect Hand-Spoofing
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Solution Overview
Problem
Existing vehicle systems are vulnerable to driver spoofing, where drivers use external objects or devices to deceive steering wheel sensors, compromising safety and operational integrity.
Innovation Solution
A vehicle system utilizing a combination of steering wheel sensors and interior depth sensing cameras, such as TOF cameras, radar, or lidar, to estimate driver hand positions and correlate with steering wheel torque, detecting spoofing by analyzing the correlation between estimated and actual data using AI/ML algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If driver behavior detection features are implemented in vehicles, then driver safety and attentiveness monitoring are improved, but drivers can spoof the system using external objects or devices
Solution Approach 1:
The patent introduces depth sensing cameras as an intermediary verification layer between the driver and the steering wheel sensors. These cameras capture depth images to verify that the detected object is indeed a human hand and not a spoofing device, thereby eliminating the spoofing vulnerability while maintaining reliable driver behavior detection
Solution Approach 2:
The patent adds a spatial dimension (depth) to the traditional 2D steering wheel sensor detection. By incorporating depth information from time-of-flight cameras, the system can distinguish between actual hands and spoofing objects based on their spatial characteristics and distance from the steering wheel, resolving the reliability-spoofing contradiction
2Measurement precision
If additional sensors are added to detect spoofing, then detection accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The patent makes the depth sensing cameras serve multiple functions: they verify hand presence on the steering wheel, detect driver facial expressions for attentiveness monitoring, and provide spatial context for driver positioning. This multi-functionality improves measurement precision without proportionally increasing device complexity
Solution Approach 2:
The patent combines the spoofing detection function with existing driver monitoring systems by integrating depth camera data with steering wheel sensor data and facial recognition algorithms. This merging approach allows the system to achieve high detection accuracy while avoiding the complexity of entirely separate detection systems
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Effectively detects driver spoofing without requiring additional hardware, ensuring driver engagement with the steering wheel and enhancing vehicle safety by preventing deceptive maneuvers.
Implementation Method 1
interior depth sensing cameras, such as TOF cameras, radar, or lidar, to estimate driver hand positions
Data Source
AI summary
A vehicle including a steering wheel, a first detection unit, a second detection unit and a processor is disclosed. The first detection unit may be configured to detect a first parameter associated with the steering wheel, and the second detection unit may be configured to capture an input associated with a vehicle occupant. The processor may be configured to obtain the input and the first parameter, and estimate a second parameter associated with a vehicle occupant interaction with the steering wheel based on the input. The processor may be further configured to correlate the first parameter and the second parameter, and determine that a predefined condition may be met based on the correlation. The processor may further transmit a notification responsive to a determination that the predefined condition may be met.