Vehicular Crash Reconstruction for Automated Emergency Dispatch
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Solution Overview
Problem
Human perception in traumatic situations like vehicular crashes is unreliable, leading to inaccurate accident reports due to memory and perception errors, which can delay medical evaluation and misrepresent the severity of injuries.
Innovation Solution
A network-based system that uses sensor data from mobile devices and vehicle computers to reconstruct vehicular crashes, generating scenario models that predict injuries and damage, and automatically notifies emergency services, reducing reliance on human reports and improving response times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human perception and memory are used to report accidents, then the reporting process is simple and quick, but the accuracy and reliability of the accident description deteriorate due to perception errors and memory issues
Solution Approach 1:
The system performs preliminary data collection by continuously monitoring sensor data (accelerometers, gyroscopes, GPS) before the accident occurs. This preliminary action ensures that accurate objective data is already captured and stored, eliminating the need for unreliable post-accident human recollection while maintaining system simplicity.
Solution Approach 2:
The patent replaces the mechanical human cognitive system (perception and memory) with an electronic sensor-based data collection system. Sensors continuously monitor and record objective physical data, substituting unreliable human reporting with automated electronic measurement and recording, thereby improving accuracy without significantly increasing complexity.
2Loss of information
If detailed accident descriptions are created after the accident, then more information can be captured, but the time delay increases and medical evaluation is postponed
Solution Approach 1:
The system continuously collects and stores sensor data, location information, and environmental data before the accident occurs. This preliminary data capture ensures that complete accident information is immediately available post-accident without requiring time-consuming interviews or recollection, thus eliminating time delay while maintaining information completeness.
Solution Approach 2:
The system automatically generates the accident report using pre-collected sensor data and objective measurements, eliminating the need for manual post-accident information gathering. This self-service approach provides complete accident information immediately, preventing time delays in medical evaluation while maintaining data completeness.
3Reliability
If multiple data sources and sensors are integrated to improve reconstruction accuracy, then the reliability of crash scenario modeling increases, but the device complexity and data processing requirements worsen
Solution Approach 1:
The system uses a multi-functional integrated platform that combines sensor data acquisition, GPS tracking, wireless communication, and data processing capabilities within a single unified system. This universal approach allows multiple data sources (accelerometers, gyroscopes, GPS, sensors from multiple devices) to be integrated seamlessly, improving crash reconstruction reliability while managing complexity through consolidation rather than proliferation of separate systems.
Data Source
AI summary
A system for notifying emergency services of a vehicular crash may (i) receive sensor data of a vehicular crash from at least one mobile device associated with a user; (ii) generate a scenario model of the vehicular crash based upon the received sensor data; (iii) store the scenario model; and/or (iv) transmit a message to one or more emergency services based upon the scenario model. As a result, the speed and accuracy of deploying emergency services to the vehicular crash location is increased. The system may also utilize vehicle occupant positional data, and internal and external sensor data to detect potential imminent vehicle collisions, take corrective actions, automatically engage autonomous or semi-autonomous vehicle features, and/or generate virtual reconstructions of the vehicle collision.