Collision Avoidance System Using Angular Acceleration Threat Assessment
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Solution Overview
Problem
Current collision mitigation systems in vehicles face inefficiencies due to the need for extensive threat assessments on multiple targets in intersections, which consume significant computing resources and are costly, especially when many targets have a low risk of collision.
Innovation Solution
A system that determines threat numbers for each target based on angular acceleration, speed, and heading angles, allowing the vehicle to focus on targets most likely to collide, thereby reducing the number of targets requiring extensive analysis and conserving computing resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If threat assessment is performed on all detected targets in intersections, then collision safety is improved, but computing resource consumption increases significantly
Solution Approach 1:
The patent segments the set of all detected targets into two groups: high-risk targets requiring full threat assessment and low-risk targets using simplified evaluation. This segmentation is based on initial screening criteria such as target position, velocity, and trajectory relative to the host vehicle, allowing the system to apply different levels of analysis to different target subsets.
Solution Approach 2:
The patent applies partial action by performing complete threat assessment only on a subset of targets identified as high-risk, while using simplified evaluation methods for the remaining low-risk targets. This selective approach maintains collision safety for critical targets while reducing overall computing resource consumption.
2Reliability
If threat assessment is performed on multiple targets simultaneously, then comprehensive collision detection is improved, but processing time increases
Solution Approach 1:
The patent divides the threat assessment process into two stages: an initial rapid screening phase that evaluates all targets using simplified criteria, and a detailed assessment phase that focuses only on high-risk targets. This segmentation reduces processing time by avoiding exhaustive analysis of all targets while maintaining comprehensive detection of potential threats.
Solution Approach 2:
The patent applies partial action by performing detailed threat assessment only on a subset of targets identified as high-risk during the screening phase. This approach maintains comprehensive collision detection for critical targets while significantly reducing overall processing time.
3Productivity
If simplified target evaluation is used, then computing efficiency is improved, but collision detection accuracy deteriorates
Solution Approach 1:
The patent segments targets into high-risk and low-risk categories based on initial evaluation criteria, then applies different assessment methods to each segment. This segmentation allows simplified evaluation for low-risk targets (maintaining computing efficiency) while ensuring accurate detailed assessment for high-risk targets (maintaining detection accuracy).
Solution Approach 2:
The patent applies local quality by using different levels of assessment precision for different target subsets. High-risk targets receive comprehensive detailed analysis with high precision, while low-risk targets use simplified evaluation with lower computational requirements. This localized approach to quality ensures accuracy where needed while maintaining efficiency overall.
Data Source
AI summary
A system includes a computer including a processor and a memory, the memory storing instructions executable by the processor to determine respective threat numbers for each of a plurality of targets based on an angular acceleration of a host vehicle and actuate a component in the host vehicle based on the threat numbers.