Vehicle Crash Severity Estimation Using Multi-Modal Occupant Sensing
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Solution Overview
Problem
Current accident response systems lack an effective approach for determining appropriate remedial actions based on the severity of a vehicle collision, often leading to inappropriate or unnecessary actions.
Innovation Solution
An accident severity estimation system that utilizes microphones, vision systems, motion-based input systems, thermal incident systems, and propulsion systems to gather multi-modal data, employing 2-value logic, weighted sum models, and fuzzy logic to determine the severity of an accident and select appropriate remedial actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current accident response systems are used, then remedial actions can be performed after a collision, but the appropriateness of remedial actions cannot be effectively determined
Solution Approach 1:
The system segments the accident assessment into multiple independent sensor systems (audio, vision, motion, thermal) each evaluating specific aspects of the collision. Each sensor type processes its own data through dedicated logic circuits, allowing precise measurement of different collision parameters separately before integrating them for overall severity assessment.
Solution Approach 2:
The controller serves multiple functions: it processes data from all sensor systems, evaluates collision severity using multiple logic methods (2-value logic, weighted sum, fuzzy logic), and determines appropriate remedial actions. This multi-functional approach enables comprehensive severity estimation that improves both measurement precision and reliability of action appropriateness.
2Measurement precision
If multiple sensor systems are integrated, then accurate severity estimation is achieved, but system complexity increases
Solution Approach 1:
The controller is segmented into distinct processing modules for each sensor system (audio processing circuit, vision processing circuit, motion processing circuit, thermal processing circuit). Each module independently processes its sensor data through dedicated logic, reducing the complexity of data integration while maintaining comprehensive measurement capabilities.
Solution Approach 2:
The system uses multiple mathematical models (2-value logic, weighted sum model, fuzzy logic) that transform raw sensor parameters into standardized severity indicators. These parameter transformations normalize data from different sensor types, enabling accurate integration without proportionally increasing system complexity.
3Productivity
If remedial actions are performed without accurate severity estimation, then response time is reduced, but the effectiveness of remedial actions decreases
Solution Approach 1:
The system performs preliminary processing of sensor data and severity estimation in parallel with the actual remedial action execution. The controller continuously monitors sensor inputs and pre-evaluates collision severity using multiple logic methods, so that when a collision occurs, the severity assessment is already underway or complete, enabling rapid yet accurate determination of appropriate actions.
Solution Approach 2:
The system implements feedback loops where sensor data continuously updates the severity estimation, which in turn adjusts the selection of remedial actions. This feedback mechanism ensures that actions are both rapid and adaptive to the actual collision severity, maintaining both response speed and effectiveness.
Data Source
AI summary
An accident severity estimation system for estimating the severity of an accident for a vehicle includes one or more microphones that capture a plurality of audio-based inputs indicative of verbal and non-verbal sounds emitted by one or more occupants of the vehicle. The accident severity estimation system also includes a vision system that captures a plurality of vision-based inputs representing image data indicative of the occupants, a motion-based input system that collects a plurality of motion-based inputs indicative of the motion of the vehicle during the accident, a thermal incident system that collects a plurality of thermal inputs indicative of thermal events within the vehicle, a propulsion system that provides a status-based input of the propulsion system of the vehicle, and one or more controllers.