Vehicle Forensics Collision Simulation Using Telematics and Map Data
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Solution Overview
Problem
Current vehicle forensics processes are manual, prone to human error, and inefficient in determining the events leading to a collision, often relying on inaccurate driver statements and outdated map data, which complicates insurance claims processing.
Innovation Solution
A vehicle forensics analytics computing device that utilizes geolocation, speech data, and vehicle telematics data to model and simulate collisions, automatically determining the time and location, parsing eyewitness accounts, and generating simulations to accurately depict vehicle positions and orientations during the collision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual forensics processes are used with toy cars to reconstruct accidents, then human operators can interpret driver statements, but the process becomes highly manual, costly, and prone to human error
Solution Approach 1:
The patent replaces the manual mechanical system of using toy cars and human operators with an automated computer-based simulation system. The system uses software to automatically reconstruct collision events by processing telematics data, map data, and speech data, eliminating the need for manual manipulation of physical models and reducing human error while maintaining reconstruction accuracy.
Solution Approach 2:
The system enables self-service by automatically processing collision reconstruction without requiring human operators to manually interpret statements or manipulate models. The computer system autonomously gathers data from multiple sources, processes speech data to extract collision details, and generates simulations independently, making the process more efficient and reliable.
2Loss of information
If claims employees use Internet maps to find collision locations, then they can obtain location information, but they are unable to validate the date or accuracy of such maps
Solution Approach 1:
The system implements feedback by automatically validating map data against multiple sources including telematics data from the vehicle, speech data from witnesses, and other contextual information. This cross-validation process provides feedback on the accuracy and currency of location data, eliminating the need for manual verification and ensuring reliable location information is used in the reconstruction.
Solution Approach 2:
The system performs multiple functions simultaneously: it retrieves map data, validates its accuracy against telematics and speech data, determines collision location, and integrates this validated information into the collision simulation. This multi-functional approach eliminates the separate time-consuming validation step while ensuring data accuracy.
3Loss of information
If claims employees paraphrase driver statements for claims files, then they can document the accident account, but additional error may be added to the driver's account
Solution Approach 1:
The patent replaces the manual paraphrasing process with automated speech data processing technology. The system uses computer algorithms to directly extract and analyze collision information from speech data, preserving the original accuracy of driver statements without introducing human interpretation errors, while simultaneously improving processing efficiency through automation.
Solution Approach 2:
The system creates an accurate digital copy of the collision account directly from speech data through automated processing. Instead of human paraphrasing that may introduce errors, the system captures and processes the original speech information faithfully, maintaining the integrity of the driver's account while enabling efficient claims processing.
Data Source
AI summary
An autonomous vehicle (AV) including a vehicle body, and a vehicle computing device is provided. The vehicle computing device includes a processor in communication with a memory device. The processor is configured to identify a time and a geographic location of a traffic collision involving the AV, retrieve map data and contextual data associated with the time and the geographic location of the traffic collision, retrieve vehicle telematics data collected by sensors coupled to the vehicle body, determine for each of a plurality of moments in time during the traffic collision a position and an orientation of the AV during the traffic collision, generate a simulation of the traffic collision including a representation of the AV based upon the map data, the contextual data, and the vehicle telematics data, and provide content to enable display of the simulation on a display device.