Driver Attention Warning Control for Occluded Road Threats
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Solution Overview
Problem
Existing systems for assisting road-vehicle drivers in manual or supervised automation modes often generate unnecessary warnings due to low driver attention levels, leading to potential late or missed warnings, especially when occluded threats are involved, such as pedestrians emerging from obscured areas.
Innovation Solution
A method and system that determine the required driver attention level based on hypothetical threats using exterior sensors and driver monitoring data, estimating the time needed to handle these threats, and providing visual, acoustic, or haptic alerts, or triggering automated braking and steering to ensure timely attention and safety, accounting for driver and system capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If driver monitoring systems warn drivers for low attention levels, then driver attention is improved, but unnecessary warnings are generated when traffic situation is safe
Solution Approach 1:
The system performs preliminary assessment of traffic situation safety before generating warnings. It evaluates external sensor data, threat levels, and occlusion conditions in advance to determine whether a warning should be issued, preventing unnecessary warnings while maintaining driver attention when truly needed.
Solution Approach 2:
The system applies different warning strategies based on local traffic conditions. It segments the monitoring space into zones with different risk levels (e.g., occluded areas vs. clear areas) and generates warnings selectively based on the specific local situation rather than applying a uniform warning approach.
2Measurement precision
If exterior sensing systems monitor traffic threats, then threat detection is improved, but occluded threats cannot be detected sufficiently
Solution Approach 1:
The system performs preliminary identification of occlusion zones using external sensors and map data before threats emerge. It proactively monitors areas where threats are likely to appear from obscured locations and prepares warning conditions in advance, enabling detection and response to occluded threats before they become fully visible.
Solution Approach 2:
The system uses driver monitoring data as an intermediary to compensate for sensor limitations. When external sensors cannot sufficiently detect occluded threats, the system uses driver attention levels, gaze direction, and reaction patterns as additional information sources to infer potential threats and trigger appropriate warnings.
3Reliability
If warnings are issued when driver is distracted, then driver attention is promoted, but warnings may be late or missed when threats appear suddenly
Solution Approach 1:
The system issues preliminary warnings when driver distraction is detected in conjunction with identified occlusion zones or potential threat conditions, rather than waiting for threats to fully manifest. This advance warning approach promotes driver attention before critical situations develop, reducing response time while avoiding late warnings.
Solution Approach 2:
The system dynamically adjusts warning timing and intensity based on real-time assessment of driver state, threat level, and time-to-collision. It modulates the urgency and frequency of warnings to match the evolving situation, ensuring timely intervention without causing alarm fatigue or delayed response.
Data Source
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AI summary
Described herein is a method and system for assisting a driver of a vehicle (1) to drive with precaution. Vehicle environment monitoring sensors (3a, 3b) determines other road users and particular features associated with a traffic situation of the vehicle (1) and hypotheses are applied related to hypothetical threats that may arise based thereupon. A driver level of attention, required to handle the hypothetical threats, and a time until that level will be required is estimated. A current driver level of attention is derived, from driver-monitoring sensors (4). If determined that the estimated required driver level of attention exceeds the current and the time until the estimated driver level of attention will be required is less than a threshold-time (tthres), there is produced at least one of visual (5), acoustic (6) and haptic (7) information to a vehicle driver environment, and/or triggered at least one of automated braking (8) and steering (9) of the vehicle (1).