Driver Impairment Assessment System Using Wearable and Vehicle Sensor Fusion
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Solution Overview
Problem
Current systems lack robust methods to effectively determine and mitigate driver impairment due to drowsiness, fatigue, and anxiety, which can reduce reaction time and increase the risk of accidents.
Innovation Solution
A system comprising a processing hardware unit and a non-transitory computer-readable storage device with modules to analyze driver health factors using wearable devices and vehicle sensors, determining fitness to drive by combining real-time data with pre-established driver profiles, and implementing actions such as recommending autonomous driving or alerting the driver.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If driver impairment assessment systems are implemented, then driving safety is improved, but system complexity increases
Solution Approach 1:
The patent combines multiple assessment methods (wearable device monitoring, non-contact sensing, and vehicle sensor data) into a unified driver impairment assessment system. This merging approach improves reliability by cross-validating data from multiple sources while managing complexity through integrated processing architecture.
Solution Approach 2:
The system employs multi-functional assessment capabilities that can operate in different modes (contact-based wearable monitoring, non-contact optical sensing, and vehicle-integrated sensor analysis). This universality allows the system to adapt to various driving conditions and driver preferences, improving safety without requiring a single complex specialized system.
2Measurement precision
If multiple data sources are integrated for accurate assessment, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the data collection and processing functions across three distinct data sources: wearable devices for physiological monitoring, non-contact devices for behavioral observation, and vehicle sensors for driving pattern analysis. This segmentation allows each component to specialize in specific measurements, improving overall precision while distributing complexity across modular units.
Solution Approach 2:
The system employs an intermediary processing layer that receives, standardizes, and integrates data from multiple heterogeneous sources. This intermediary architecture enables precise impairment assessment by harmonizing different data formats and protocols without requiring direct complex interactions between all data sources.
Data Source
AI summary
A system for analyzing driver fitness to drive with consideration given to any of various conditions such as driver drowsiness, fatigue, and anxiety. The system includes a processing hardware unit, and a non-transitory computer-readable storage device comprising various modules to determine if the driver is impaired. The modules include an input interface module that, when executed by the processing unit, receives sensor data indicating a present driver health factor. A database module includes pre-established driver-profile data particular to a driver. And the modules include an activity module that, when executed by the processing unit, obtains the driver-profile data and the sensor data, and determines, based on the present health factor and the pre-established driver-profile data, fitness of the driver to drive. The disclosure relates in various embodiments to a computer-readable storage device, separately, and processes performed by the system and device.