Target Vehicle Movement Classification for Active Safety
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Solution Overview
Problem
Existing vehicle safety systems lack the ability to effectively classify the movement of target vehicles relative to a host vehicle, leading to inadequate tailored active safety responses.
Innovation Solution
A method and system that measure and assess the movement patterns of target vehicles, classify them based on deviations from typical behavior, and take appropriate actions using a processor and detection unit within an active safety control system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If active safety systems provide automated warnings or actions for detected target vehicles, then safety functionality is improved, but the system cannot tailor actions to particular types of target vehicles because it lacks classification capability
Solution Approach 1:
The patent segments target vehicle detection into multiple classification categories based on movement patterns. The processor divides the continuous space of target vehicle behaviors into discrete classes (e.g., typical movement, erratic movement, aggressive movement) by assessing patterns of movement relative to the host vehicle and third vehicles. This segmentation enables tailored active safety actions for each category.
Solution Approach 2:
The system dynamically classifies target vehicles by continuously assessing movement patterns in real-time. The processor evaluates changing positions and movements of target vehicles relative to the host vehicle and third vehicles, adjusting classifications as movement patterns evolve. This dynamic assessment enables adaptive tailoring of safety responses to current target vehicle behavior.
2Adaptability or versatility
If the system classifies target vehicle movement patterns to enable tailored safety responses, then adaptability is improved, but device complexity increases due to additional detection and processing requirements
Solution Approach 1:
The detection unit and processor are designed to perform multiple functions: detecting target vehicles, measuring their movements, assessing movement patterns, and generating classifications. This multi-functionality reduces the need for separate specialized components for each task, thereby managing device complexity while achieving comprehensive classification capability.
Solution Approach 2:
The processor autonomously assesses movement patterns and generates classifications without requiring external intervention or additional complex subsystems. The system uses its own detection capabilities and processing power to self-service the classification function, avoiding the need for separate classification hardware or external processing systems.
Data Source
AI summary
Methods, program products, and vehicles are provided for classifying movement of target vehicles in proximity to a host vehicle and taking appropriate action based on the classification. An active safety system is coupled to a drive system, and is configured to provide an action during a drive cycle of the vehicle. The active safety system comprises a detection unit and a processor. The detection unit is configured to measure movement of a target vehicle in proximity to a host vehicle. The processor is coupled to the detection unit, and is configured to assess a pattern of the movement of the target vehicle relative to the host vehicle or a third vehicle, classify the movement of the target vehicle based on the pattern to generate a classification, the classification pertaining to a deviation from a typical vehicle movement, and take action based on the classification.