Driver Attention Detection Using Gaze and Road Heat Maps
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Solution Overview
Problem
Existing driver distraction monitoring systems fail to effectively assess driver attentiveness by only analyzing head pose and gaze angles on a frame-by-frame basis, without considering critical factors like road conditions and driver intention.
Innovation Solution
A computer-implemented method that collects vehicle data and scene information to generate a reference heat map, and tracks the driver's gaze direction and duration to create a driver gaze heat map, which are then analyzed to determine the level of driver distraction and provide recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If head pose and gaze angles are analyzed on a frame-by-frame basis, then the system can detect driver distraction, but it fails to consider other critical information such as road conditions and driver intention
Solution Approach 1:
The patent merges multiple data sources including head pose, gaze angles, road conditions, and driver intention into a unified driver attention assessment model. This combination allows the system to simultaneously process visual attention data and contextual driving information, resolving the contradiction between precise gaze tracking and comprehensive information consideration
Solution Approach 2:
The driver attention assessment system is designed to perform multiple functions: tracking head pose, monitoring gaze angles, evaluating road conditions, and inferring driver intention. This multi-functional approach enables a single system to address various aspects of driver distraction detection without requiring separate specialized systems for each parameter
2Reliability
If the system collects and processes multiple types of data (vehicle data, scene information, gaze data), then the assessment of driver attentiveness becomes more comprehensive, but the system complexity increases
Solution Approach 1:
The patent segments the driver attention assessment system into distinct functional modules: a data collection module for gathering head pose and gaze data, a separate module for obtaining road condition and driver intention information, and an integration module that combines these data streams. This segmentation reduces system complexity by organizing multiple data processing functions into manageable, independent components
Solution Approach 2:
The patent introduces an intermediary driver attention assessment model that acts as a mediator between raw multi-source data and the final distraction determination. This intermediary layer processes and integrates vehicle data, scene information, and gaze data before producing the final assessment, thereby managing system complexity while maintaining comprehensive data analysis
Data Source
AI summary
The disclosure relates to technology for monitoring driver attentiveness in a vehicle. A driver distraction system collects vehicle data and scene information from the vehicle while traveling on a route. The vehicle data and scene information are then processed to generate a reference heat map. At the same time, the driver distraction system may capture a gaze of a driver to track a gaze direction and duration of the driver while driving the vehicle on the route. The gaze direction and duration are processed to generate a driver gaze heat map. The driver gaze heat map and reference heat map are analyzed to determine a level of driver distraction of the driver in the vehicle, and a recommendation or warning is output to the driver of the vehicle according to the level of driver distraction.