Relative Movement Prediction for Low-Frame-Rate Collision Detection
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Solution Overview
Problem
Existing methods for predicting collisions between moving objects are inadequate, especially when objects change direction or move in complex areas, as they assume continuous movement patterns without considering potential changes in relative position, leading to inaccurate collision predictions and high camera frame rate requirements.
Innovation Solution
A method that classifies the expired change in relative position of one object and defines the future area of relative movement based on object properties and probabilities, using a database to reduce the number of required camera frames and handle movements with lower frame rates, allowing for efficient collision prediction without assuming continuous movement patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the time intervals for repetition are selected to be sufficiently small to prevent excessive deviations from actual movements, then the accuracy of collision prediction is improved, but the camera frame rate requirements increase
Solution Approach 1:
The system performs preliminary classification of expired changes in relative position and defines future areas of relative movement in advance, allowing collision prediction without requiring continuous high-frame-rate capture of actual movements. This preliminary action enables accurate collision prediction while reducing camera frame rate requirements.
2Device complexity
If the method assumes continuation of expired changes in relative position, then the calculation complexity is reduced, but the reliability of collision prediction deteriorates when objects change direction
Solution Approach 1:
The system dynamically adapts the prediction model by classifying expired changes in relative position and defining future areas of relative movement based on object properties and probabilities. This dynamic approach maintains calculation simplicity while improving reliability when objects change direction, as the system can adjust to different movement patterns without complex recalculations.
Solution Approach 2:
The system changes parameters by classifying different types of relative position changes and assigning different future area definitions based on object properties. This allows the system to handle various movement scenarios (straight line, curve, direction change) with appropriate parameters while maintaining computational efficiency.
3Measurement precision
If image analysis with AI is applied to detect collisions, then the ability to detect complex movement patterns is improved, but the processing time and computational resources increase
Solution Approach 1:
The system extracts only the essential features needed for collision prediction by classifying expired changes in relative position and defining future areas of relative movement. This extraction approach achieves accurate collision detection without requiring full image analysis, thereby reducing processing time and computational resource requirements.
4Measurement precision
If the method observes individual trajectories, then the precision of movement tracking is improved, but the ability to predict collisions in intersection areas deteriorates
Solution Approach 1:
The system transitions from tracking individual trajectories to defining future areas of relative movement, adding a spatial dimension to the prediction. This area-based approach enables collision prediction in intersection regions by considering all possible future positions within the defined area, not just a single predicted trajectory.
Data Source
AI summary
A method for displaying and/or calculating relative movement of a second moved object to a first moved object, wherein a future first change in position of the first object is calculated from an expired first change in position, and wherein a future second change in relative position of the second object is calculated from an expired second change in relative position, which future first change in position is compared with the future second change in relative position.