Driver Alerting HMI with Adaptive Gaze-Based Notification Timing
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Solution Overview
Problem
Existing systems struggle to effectively and acceptably notify drivers of a distracted state, particularly at intersections, due to individual variations in human response to stimuli, making it difficult to determine the optimal form of notification.
Innovation Solution
An alerting system that measures gaze dwell time using eye tracking and adjusts notification parameters, such as timing and conspicuousness level, to optimize driver response through machine learning, recording and analyzing reaction ratios to refine notification settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If notification stimulus is made more conspicuous to ensure driver recognition, then notification effectiveness is improved, but driver acceptability and comfort deteriorate
Solution Approach 1:
The notification system dynamically adjusts stimulus characteristics (conspicuousness level, timing, type) based on real-time driver state detection. The system transitions from static notification parameters to dynamic adaptation, selecting different notification strategies depending on whether the driver is in a distracted state, thereby resolving the contradiction between effectiveness and comfort.
Solution Approach 2:
The system changes notification parameters (timing, conspicuousness level, stimulus type) based on detected driver state. By varying these parameters adaptively, the system achieves effective notification when needed while maintaining driver comfort during normal operation, thus resolving the technical contradiction.
2Loss of time
If notification is executed early to alert distracted drivers, then safety response time is improved, but false notification rate increases
Solution Approach 1:
The system performs preliminary detection of driver distraction state using gaze tracking and other sensors before executing notification. This preliminary assessment allows the system to notify drivers early when truly distracted, while avoiding premature notifications when the driver is merely temporarily looking away, thus resolving the contradiction between early warning and false alarms.
Solution Approach 2:
The system uses feedback from multiple sensors (gaze tracking, steering input, vehicle state) to continuously assess driver attention state. This multi-source feedback mechanism improves detection accuracy, allowing early notification when distraction is confirmed while reducing false notifications, thereby resolving the technical contradiction.
3Object-affected harmful factors
If individual driver characteristics are considered to improve notification acceptability, then driver comfort is improved, but system complexity increases
Solution Approach 1:
The system performs self-adjustment by automatically detecting driver state and adapting notification parameters without requiring manual calibration or complex individual profiling. The driver's own behavior patterns serve as the basis for customization, reducing system complexity while improving acceptability.
Solution Approach 2:
The system uses a unified multi-functional approach, where a single notification system handles multiple driver states and scenarios by adapting its parameters. Rather than creating separate systems for different drivers, the universal system adjusts to individual needs through real-time detection, resolving the contradiction between personalization and complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively notifies drivers of a distracted state in a form that is easily acceptable, enhancing traffic safety by improving driver response to notifications.
Implementation Method 1
a gaze measurement unit that measures a gaze dwell time of a driver of a vehicle
Data Source
AI summary
An alerting system includes: a notification unit, when a gaze dwell time of a driver exceeds a predetermined threshold, executing a notification at a predetermined conspicuousness level to the driver via an HMI device; a decision unit deciding on a notification parameter set including parameters defining a notification output timing and the conspicuousness level; a behavior recording unit recording presence/absence of a reactive behavior to the notification executed using the notification parameter set; and a reaction information recording unit recording reaction information where a reaction ratio, which is a ratio of the number of the notifications to which the reactive behavior occurs to the number of the notifications executed, is associated with each different notification parameter set, wherein the decision unit calculates and decides on, based on the reaction information, an optimal parameter set with which the reaction ratio is estimated to become the highest.