Driver Distraction Detection Using In-Cabin Skeletal Posture Data
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Solution Overview
Problem
The increasing complexity of vehicle operating environments and the presence of advanced entertainment systems in vehicles lead to increased driver distractions, necessitating methods to generate data representative of in-cabin insurance risk evaluations based on driver skeletal diagrams indicative of distractions.
Innovation Solution
A system that includes vehicle interior and location data receiving modules to detect and generate data on driver distractions, which can be transmitted to a remote computing device for analysis, allowing for the identification of distracted drivers and potential hazards, and can alter navigation routes to avoid distraction clusters while providing warnings to vulnerable road users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If advanced entertainment systems and complex vehicle operating environments are added to vehicles, then vehicle functionality and user experience are improved, but driver distractions increase
Solution Approach 1:
The system continuously monitors driver state through sensors (camera, microphone, accelerometer) and provides real-time feedback by analyzing skeletal diagrams to detect distraction levels. This closed-loop feedback mechanism allows the system to respond to driver state changes and alert drivers when distraction is detected, resolving the contradiction by making the harmful effect visible and actionable.
Solution Approach 2:
The patent introduces an intermediary system (the distraction detection system with skeletal analysis) that mediates between the complex vehicle environment and the driver. This intermediary processes sensor data, generates skeletal diagrams, and translates complex environmental factors into interpretable distraction assessments, allowing the driver to maintain awareness despite the complex operating environment.
2Reliability
If driver distraction monitoring systems are implemented, then driver safety is improved, but device complexity increases
Solution Approach 1:
The system uses a multi-functional approach where existing vehicle sensors (camera, microphone, accelerometer) are repurposed for distraction detection in addition to their primary functions. The skeletal diagram generation technology serves multiple purposes including driver monitoring, posture analysis, and distraction detection, reducing the need for dedicated specialized components and thereby managing complexity while maintaining safety.
Solution Approach 2:
The system performs self-analysis by processing its own sensor data to generate skeletal diagrams and assess driver distraction levels autonomously. The processor independently analyzes the collected data without requiring external intervention, allowing the system to maintain high reliability while keeping the architecture relatively simple through self-contained processing capabilities.
Data Source
AI summary
Apparatuses, systems and methods are provided for determining vehicle driver distractions. More particularly, apparatuses, systems and methods are provided for determining distracted drivers associated with vehicle driving routes based on postures of vehicle occupants.