In-Vehicle Driver Profiling Using Driving Behavior Matrices
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Solution Overview
Problem
Existing driver identification systems in vehicles often require direct user input, which can be time-consuming, prone to errors, and vulnerable to incorrect identification, especially in scenarios where multiple drivers use the same vehicle.
Innovation Solution
A driver identification system that utilizes driving behavior data to infer the identity of the driver by generating two-dimensional matrices based on vehicle operating parameters such as speed, acceleration, and pedal position, comparing these matrices to stored profiles to determine the likelihood of the current driver matching a known driver.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct user input is used for driver identification, then identification accuracy can be ensured, but it interferes with driving experience and consumes valuable computing resources
Solution Approach 1:
The system performs self-identification by automatically analyzing driving behavior patterns without requiring direct user input. The driver's actions (steering, acceleration, braking patterns) serve as the identification mechanism, eliminating the need for separate login or biometric scanning steps while maintaining identification accuracy.
Solution Approach 2:
The patent replaces mechanical input methods (buttons, biometric scanners, keyboard entry) with behavioral analysis of vehicle control systems. Instead of requiring the driver to physically interact with identification devices, the system substitutes these mechanical interaction points with electronic analysis of existing driving data from sensors already present in the vehicle.
2Reliability
If direct user input is used for driver identification, then identification can be performed, but it is vulnerable to incorrect identification when multiple users share a vehicle
Solution Approach 1:
The system continuously monitors and compares real-time driving behavior against stored driver profiles, providing ongoing verification throughout the driving session. This feedback mechanism ensures that if the wrong driver is initially identified, the system can detect discrepancies in driving patterns and correct the identification, thereby eliminating vulnerability to incorrect identification.
Solution Approach 2:
The system performs preliminary analysis of driving behavior patterns before finalizing driver identification. By analyzing multiple parameters (steering patterns, acceleration profiles, braking behavior) in advance and comparing them against stored profiles, the system establishes a reliable identification baseline that prevents incorrect attribution of driving sessions to the wrong user.
3Measurement precision
If multiple sensors are used for driver identification, then identification accuracy improves, but computing resources and system complexity increase
Solution Approach 1:
The system makes existing vehicle sensors serve multiple functions: they simultaneously monitor vehicle operation for safety and control purposes while also collecting behavioral data for driver identification. The steering angle sensor, accelerator pedal position sensor, and brake sensor data used for normal vehicle operation are repurposed to create driver profiles, eliminating the need for dedicated identification sensors.
Solution Approach 2:
The patent merges the driver identification function with the existing vehicle monitoring and control systems. Instead of adding separate sensors and processing systems for identification, the system combines identification analytics with the existing data streams from vehicle operation sensors, thereby improving accuracy without increasing overall system complexity.
Data Source
AI summary
Embodiments are disclosed for an automatic identification of a driver. In one example, an in-vehicle computing system of a vehicle includes a sensor interface communicatively coupled to one or more data collection devices, a processor, and a storage device storing instructions executable by the processor to generate a two-dimensional current driver profile matrix for a current driver of the vehicle, the current driver profile matrix indicating a vehicle operating status in terms of a pair of driving parameters at sampled times during a current vehicle trip, and determine a probability that the current driver is one of a plurality of known drivers by comparing the current driver profile matrix to one or more stored driver profile matrices associated with the plurality of known drivers.