Driver Distraction Detection Using Segmented Neural Networks
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Solution Overview
Problem
Current systems fail to effectively determine and mitigate driver distraction during vehicle operation, which can lead to accidents and is not adequately addressed by existing technologies.
Innovation Solution
A method and system that uses onboard sensors to sample images of the driver and the road environment, employing a neural network-based driver distraction module to classify driver poses and determine distraction states, with optional notification based on context and distraction scores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution images are processed to accurately determine driver distraction, then measurement precision is improved, but processing time increases
Solution Approach 1:
The patent divides the original high-resolution driver image into multiple sub-images of different resolutions. A face detection module identifies key facial regions, and these regions are extracted at different resolution levels. This segmentation allows the system to process only relevant portions of the image at high resolution while using lower resolution for other areas, thereby maintaining detection accuracy while reducing overall processing time and computational load.
2Measurement precision
If multiple sensor measurements are collected to improve distraction determination accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent employs a multi-functional onboard system that integrates various sensor types (cameras, microphones, other sensors) into a single unified platform. This system performs multiple functions including image capture, audio recording, distraction analysis, and context determination. By consolidating these functions into one multi-capable system rather than separate dedicated devices, the patent reduces overall system complexity while maintaining the ability to collect comprehensive multi-modal data for accurate distraction determination.
3Reliability
If real-time driver monitoring is implemented, then safety is improved, but energy consumption increases
Solution Approach 1:
The patent implements periodic sampling of sensor measurements rather than continuous monitoring. The system collects images, audio, and other sensor data at specific time intervals during driving sessions. This periodic approach allows real-time monitoring capability while significantly reducing energy consumption compared to continuous operation. The system can adjust sampling frequency based on driving conditions and detected distraction levels, maintaining safety while optimizing energy usage.
Data Source
AI summary
A method for determining distraction of a driver of a vehicle, including sampling sensor measurements at an onboard system of the vehicle; generating an output indicative of a distracted state; determining that the driver of the vehicle is characterized by the distracted state, based on the output; generating, at a second distraction detection module of a remote computing system, a second output indicative that the driver is characterized by the distracted state, based on the sensor measurements; computing a distraction score, at a scoring module of the remote computing system, in response to generating the second output and based on the sensor measurements and the distracted state.