Vehicle Alarm Notification via Driver Recognition Feedback
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Solution Overview
Problem
Existing vehicle alarm notification systems fail to differentiate alarm states based on the degree of risk, emergency, and driver recognition, making it difficult for drivers to accurately and promptly respond to alarms.
Innovation Solution
A method and system that utilize a driver state monitor and head-up display to determine driver recognition of alarms, adjusting the display and alarm sound accordingly, and outputting warnings based on eye position and recognition frequency to ensure timely and appropriate handling of alarm states.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional alarm notification systems are used, then the system structure is simple, but the driver cannot accurately recognize alarm states and respond promptly
Solution Approach 1:
The alarm notification system is segmented into multiple independent modules: alarm state detection module, driver state monitoring module (tracking eye position and recognition status), alarm content determination module, and display control module. Each module performs a specific function, allowing the system to achieve high recognition accuracy through coordinated operation of simpler components rather than a monolithic complex system.
Solution Approach 2:
The system implements feedback loops where the driver state monitor continuously tracks whether the driver has recognized the alarm by monitoring eye position and recognition frequency. This recognition status feedback is fed back to the display control module, which adjusts the alarm display accordingly - moving alarms to HUD when unrecognized, or summarizing them when recognized, thereby improving recognition accuracy through adaptive feedback control.
2Ease of operation
If alarm display is moved to HUD based on driver eye position, then driver recognition is improved, but device complexity increases
Solution Approach 1:
The system uses the driver's own eye position and attention state to automatically determine the optimal display location. The driver state monitor self-evaluates whether the driver is looking at the alarm, and the system self-adjusts by moving the alarm display to the HUD when the driver is not recognizing it, or summarizing it when the driver is paying attention. This self-service mechanism improves response efficiency without requiring complex external control interventions.
Solution Approach 2:
The alarm display position and format are made dynamic rather than static. The system continuously monitors driver eye position and recognition status, dynamically adjusting the alarm display location (between cluster and HUD) and format (detailed vs. summarized) in real-time based on driver attention state. This dynamic adaptation improves ease of operation by automatically optimizing the interface to match driver behavior.
3Loss of information
If differentiated display controls are implemented based on risk degree, then alarm recognition accuracy is improved, but the system becomes more complex
Solution Approach 1:
The system applies different display qualities and formats to different alarm types based on their risk degree. High-risk alarms receive detailed display with prominent positioning, while lower-risk alarms are summarized or placed in less prominent locations. The driver state monitor also applies local quality by focusing monitoring resources on detecting whether the driver has recognized the current alarm, rather than uniformly monitoring all possible alarms. This localized differentiation improves information effectiveness without requiring the entire system to be uniformly complex.
Solution Approach 2:
The system changes display parameters (position, format, prominence) based on the risk degree parameter of the alarm. The alarm content determination module assigns risk degrees to different alarm types, and the display control module translates these risk parameters into appropriate display characteristics - such as moving high-risk alarms to HUD with detailed information, or summarizing low-risk alarms in the cluster. This parameter-based control approach improves information effectiveness while maintaining manageable system complexity through systematic parameter mapping.
Data Source
AI summary
A method and system for notifying an alarm state of a vehicle include displaying an alarm corresponding to an alarm state of an alarm state occurring in a vehicle, and determining whether a driver recognizes the displayed alarm. The alarm is displayed in a different manner based on a recognition frequency and duration of time the driver recognized the alarm when it is determined that the driver recognizes the displayed alarm. An alarm sound is output for a period of time when it is determined that the driver does not recognize the displayed alarm.