Collision Warning Suppression via Vehicle Safe-Zones
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Solution Overview
Problem
Collision avoidance systems often issue false warnings due to difficulty in distinguishing stationary objects from vehicles, leading to driver annoyance and potential safety issues, as they cannot easily identify non-vehicle stationary targets like berms, manhole covers, trees, and poles.
Innovation Solution
A method and system that utilize vehicle-to-vehicle communication data to create 'safe-zones' where stationary objects are unlikely to be present, based on the path history and position data of surrounding vehicles, allowing the suppression of collision warnings when a detected object is within these zones, thereby preventing false alarms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If collision avoidance systems issue warnings for all detected stationary objects, then detection precision is improved, but false warning rate increases
Solution Approach 1:
The system segments the detection area into multiple zones (safe-zone, caution-zone, danger-zone) based on vehicle path history and spatial relationships. By dividing the monitoring space into distinct regions with different warning thresholds, the system achieves precise detection while avoiding false warnings in areas where stationary objects are unlikely to pose threats.
Solution Approach 2:
The system performs preliminary actions by collecting vehicle path history data and pre-defining safe-zones before actual collision detection occurs. By establishing these zones in advance based on aggregated trajectory information from multiple vehicles, the system prepares the contextual framework needed to distinguish true threats from false warnings in real-time detection.
2Object-generated harmful factors
If the system suppresses warnings for stationary objects in safe-zones, then false warning rate decreases, but detection reliability may be affected
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring vehicle trajectories and updating safe-zone definitions based on aggregated path history data. This feedback loop allows the system to learn from actual vehicle behavior patterns, dynamically adjusting warning suppression decisions to maintain high detection reliability while minimizing false alarms through data-driven zone optimization.
Solution Approach 2:
The safe-zone concept acts as an intermediary layer between raw sensor detection and final warning issuance. This intermediary mechanism filters detection results through spatial contextual information, allowing the system to suppress warnings only when objects fall within pre-defined safe-zones while maintaining full sensitivity outside these zones, thereby preserving overall detection reliability.
3Ease of operation
If the system uses vehicle-to-vehicle communication data to define safe-zones, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The system achieves universality by using multi-functional vehicle-to-vehicle communication infrastructure for both navigation assistance and collision avoidance purposes. The same communication channels and data exchange protocols used for general vehicle connectivity are leveraged to transmit path history data for safe-zone definition, eliminating the need for dedicated specialized hardware and reducing overall system complexity.
Data Source
AI summary
A system and method for suppressing collision warning in a host vehicle is provided. The system receives position data from a remote vehicle. The host vehicle suppresses a collision warning when a detected stationary object is in a safe-zone based on the remote vehicle position data, thereby preventing false collision warnings.