Vehicle Collision Indication Using Yaw Rate and Lateral Velocity
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Solution Overview
Problem
Conventional techniques for determining imminent collisions in vehicles are often inaccurate, leading to false positives and delayed reactions in advanced driver assistance systems, which can decrease safety and user experience.
Innovation Solution
The method involves determining a predicted path and an in-path band for a host vehicle, assessing the yaw rate and lateral velocity of both the host and target vehicles to estimate their future positions within the in-path band, and generating a collision indication only when both are likely to be within the band, thereby improving the accuracy of collision detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional collision detection techniques are used, then the system responds to potential collisions, but the accuracy of collision detection is low leading to false positives
Solution Approach 1:
The patent changes the parameters used for collision detection from conventional methods to include yaw rate and lateral velocity thresholds. By monitoring whether the host vehicle's yaw rate exceeds a threshold and whether the target's lateral velocity exceeds a threshold, the system achieves more accurate collision detection. This parameter transformation resolves the contradiction by providing both high detection accuracy and reduced false positives through physically meaningful thresholds.
Solution Approach 2:
The patent introduces an intermediary assessment layer that evaluates yaw rate and lateral velocity as intermediate parameters before determining collision imminence. This intermediary step filters out false positives by checking whether the host vehicle is actually changing direction (yaw rate threshold) and whether the target is moving laterally (lateral velocity threshold), thereby improving reliability while maintaining detection accuracy.
2Loss of time
If conventional collision detection techniques are used, then the system can detect collisions, but the reaction time is delayed
Solution Approach 1:
The patent performs preliminary assessment of yaw rate and lateral velocity thresholds before a collision is actually imminent. By continuously monitoring whether the host vehicle's yaw rate exceeds the threshold and whether the target's lateral velocity exceeds the threshold in advance, the system prepares for potential collision scenarios earlier, reducing reaction time while maintaining accurate detection through the threshold-based filtering mechanism.
3Reliability
If downstream operations like AEB and ESA are activated frequently, then safety is improved, but false positives decrease user experience
Solution Approach 1:
The patent changes the activation parameters for downstream operations by requiring both yaw rate threshold exceedance and lateral velocity threshold exceedance before triggering collision avoidance actions. This dual-threshold parameter change ensures that AEB and ESA are activated only when there is genuine lateral movement indicating a real collision threat, thereby maintaining high safety while eliminating false positives that would degrade user experience.
Solution Approach 2:
The patent implements feedback by continuously monitoring yaw rate and lateral velocity thresholds to determine when downstream operations should be activated. This feedback mechanism ensures that safety-critical systems like AEB and ESA are triggered only when the physical thresholds indicate a real threat, preventing unnecessary activations that would harm user experience while maintaining reliable safety protection.
Data Source
AI summary
The techniques and systems herein enable collision indication based on yaw rate and lateral velocity thresholds. Specifically, an in-path band is determined for a predicted path of a host vehicle. Responsive to determining that a target is within the in-path band, a lateral movement for the host vehicle at a time is determined based on whether a yaw rate of the host vehicle meets a yaw rate threshold. A lateral movement for the target at the time is also determined based on whether a lateral velocity of the target meets a lateral velocity threshold. A collision indication is generated responsive to determining, based on the lateral movements, that the host vehicle and the target are likely to be within the in-path band at the time. In this way, the collision indication more accurately reflects an imminent collision, thereby increasing safety while also mitigating false-positive events.