Vehicle Collision Damage Prediction via Energy Transfer Analysis
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Solution Overview
Problem
Current vehicle collision detection systems fail to accurately predict damage to components and associated hazards, such as slip, fire, electrocution, and respiratory hazards, due to limitations in assessing energy transfer and material deformation during collisions.
Innovation Solution
A computer system in the vehicle predicts damage to components by analyzing energy transfer based on the speed and mass of a target vehicle, contact area, deformation strength of materials, and shape of the vehicle body, identifying potential hazards and generating a list of components to repair, using sensors and image data to determine the target vehicle's characteristics and cargo.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional collision detection systems use basic sensor data to detect collisions, then the system complexity is low, but the measurement precision of damage prediction is insufficient
Solution Approach 1:
The system segments the collision detection and analysis process into multiple components: initial collision detection using basic sensors, energy transfer calculation module, deformation characteristic analysis module, and penetration depth prediction module. Each segment processes specific aspects of collision analysis independently, improving overall measurement precision without requiring complete system redesign.
Solution Approach 2:
The system performs preliminary actions by calculating energy transfer and deformation characteristics immediately upon collision detection, before final damage assessment. This preliminary analysis prepares data structures and intermediate results that accelerate the final damage prediction process, enhancing measurement precision while managing computational complexity.
2Measurement precision
If the system analyzes multiple factors including energy transfer, contact area, and material deformation, then the damage prediction accuracy improves, but the loss of time for computation increases
Solution Approach 1:
The system implements periodic action by updating damage predictions in stages: initial collision detection triggers energy transfer calculation, which then triggers deformation analysis, followed by penetration depth prediction. This staged periodic processing allows complex multi-factor analysis to be performed systematically, improving accuracy while managing computation time through structured sequential execution.
3Productivity
If the system predicts penetration depth and component damage, then the productivity of repair prioritization improves, but the device complexity increases
Solution Approach 1:
The system performs preliminary action by predicting penetration depth and identifying damaged components before repair operations begin. This advance prediction provides repair teams with prioritized component lists and hazard information, significantly improving repair productivity. The complexity is managed by automating the prediction process through integrated calculations of energy transfer, deformation, and material properties.
Data Source
AI summary
A computer includes a processor and a memory, the memory storing instructions executable by the processor to predict damage to one or more components of a host vehicle and predict a hazard for a user of the host vehicle based on the predicted damage of at least one of the components disposed at the collision location. The computer predicts the damage based on an energy transfer between a target vehicle and the host vehicle. The energy transfer is based on a speed of a target vehicle, a mass of the target vehicle, a predicted contact area of a collision location of the host vehicle where the target vehicle is predicted to collide, and a deformation strength of material at the collision location.