# US 11,308,741 B1 · Systems and methods for modeling and simulation in vehicle forensics

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- Number: US 11,308,741 B1
- Document ID: US11308741B1
- Status: Granted
- Kind: B1
- Application number: 16/579,045
- Filed: 2019-09-23
- Granted: 2022-04-19
- Earliest claimed: 2019-05-30
- Assignees: State Farm Mutual Automobile Insurance Company
- Applicants: State Farm Mutual Automobile Insurance Company
- Inventors: Alexander Cardona; Jerome Scott Trayer; An Ho
- Web page: https://patentgrep.com/patent/US11308741B1

## CPC

- G07C 5/0841: {Registering performance data (recording measured values G01D; information storage G11B)}
- G06F 30/20: Design optimisation, verification or simulation (optimisation, verification or simulation of circuit designs G06F30/30)
- G06F 40/205: Parsing
- G06Q 40/08: Insurance
- G07C 5/008: {communicating information to a remotely located station (transmission systems for measured values G08C)}
- G08G 1/0112: {from the vehicle, e.g. floating car data [FCD]}
- G08G 1/0133: {for classifying traffic situation}
- G08G 1/0137: {for specific applications}
- G08G 1/205: {Indicating the location of the monitored vehicles as destination, e.g. accidents, stolen, rental}
- G10L 15/26: Speech to text systems (G10L15/08 takes precedence)
- G07C: TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G08G: TRAFFIC CONTROL SYSTEMS (guiding railway traffic, ensuring the safety of railway traffic B61L; arrangement of road signs or traffic signals E01F9/00; radar or analogous systems, sonar systems, lidar systems specially adapted for traffic control G01S13/91, G01S15/88, G01S17/88; {radar or analogous systems, sonar systems, lidar systems specially adapted for anti-collision purposes G01S13/93, G01S15/93, G01S17/93})
- G10L: SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING

## Abstract

A vehicle forensics analytics (“VFA”) computing device is configured to: (1) determine a time and a location of a traffic collision; (2) retrieve map data and contextual data associated with the time and the location of the traffic collision; (3) receive speech data, the speech data corresponding to a statement given by a witness of the traffic collision; (4) parse the speech data for phrases describing the traffic collision; (5) determine, based upon the parsed speech data, for each of a plurality of moments in time during the traffic collision, a position and an orientation of a vehicle involved in the traffic collision; (6) generate a simulation including a representation of the vehicle involved in the traffic collision based upon the map data, the contextual data, and the determined position and orientation for each of the plurality of moments in time; and (7) display the simulation to reconstruct the collision.

## Claims

### Claim 1

A vehicle forensics analytics (“VFA”) computing device comprising a processor in communication with a memory device, said processor configured to:
determine a time and a location of a traffic collision;
retrieve map data and contextual data associated with the time and the location of the traffic collision;
receive speech data, the speech data corresponding to a statement given by a witness of the traffic collision;
parse the speech data for phrases describing the traffic collision;
determine, based upon the parsed speech data, for each of a plurality of moments in time during the traffic collision, a position and an orientation of a vehicle involved in the traffic collision;
generate a simulation including a representation of the vehicle involved in the traffic collision based upon the map data, the contextual data, and the determined position and orientation for each of the plurality of moments in time; and
display the simulation.

### Claim 2 (depends on 1)

The VFA computing device of claim 1, wherein to determine the time of the traffic collision, the processor is further configured to:
retrieve vehicle telematics data; and
identify the time based upon the vehicle telematics data.

### Claim 3 (depends on 2)

The VFA computing device of claim 2, wherein the processor is configured to retrieve the vehicle telematics data from one or more of an automated vehicle, a mobile phone device, or a telematics device.

### Claim 4 (depends on 2)

The VFA computing device of claim 2, wherein to determine the location of the traffic collision, the processor is configured to retrieve geographic coordinates from one or more of an automated vehicle, a mobile phone device, or a telematics device.

### Claim 5 (depends on 1)

The VFA computing device of claim 1, wherein to determine the time and the location, the processor is configured to retrieve a timestamp and geographic coordinates from a mobile phone device.

### Claim 6 (depends on 1)

The VFA computing device of claim 1, wherein to determine the time and the location, the processor is configured to:
retrieve a document including the time and geographic coordinates indicating the location; and
parse the document to determine the time and the location.

### Claim 7 (depends on 1)

The VFA computing device of claim 1, wherein the received speech data includes an audio signal and the processor is further configured to convert the audio signal into text.

### Claim 8 (depends on 7)

The VFA computing device of claim 7, wherein the processor is further configured to display the text.

### Claim 9 (depends on 1)

The VFA computing device of claim 1, wherein the processor is further configured to analyze the parsed speech data to identify inconsistent phrases.

### Claim 10 (depends on 9)

The VFA computing device of claim 9, wherein to determine the position and the orientation of the vehicle at each of the plurality of moments in time, the processor is configured to determine whether to use a phrase based upon whether the phrase is identified as an inconsistent phrase.

### Claim 11 (depends on 1)

The VFA computing device of claim 1, wherein to determine the position and the orientation of the vehicle at each of the plurality of moments in time, the processor is configured to determine the position and orientation based upon one or more of vehicle telematics data, vehicle specification data, photographic data, or physics data.

### Claim 12

A computer-implemented method for vehicle forensics, said computer-implemented method implemented by a vehicle forensics analytics (“VFA”) computing device including a processor in communication with a memory device, said computer-implemented method comprising:
determining, by the VFA computing device, a time and a location of a traffic collision;
retrieving, by the VFA computing device, map data and contextual data associated with the time and the location of the traffic collision;
receiving, by the VFA computing device, speech data, the speech data corresponding to a statement given by a witness of the traffic collision;
parsing, by the VFA computing device, the speech data for phrases describing the traffic collision;
determining, by the VFA computing device, based upon the parsed speech data, for each of a plurality of moments in time during the traffic collision, a position and an orientation of a vehicle involved in the traffic collision;
generating, by the VFA computing device, a simulation including a representation of the vehicle involved in the traffic collision based upon the map data, the contextual data, and the determined position and orientation for each of the plurality of moments in time; and
displaying, by the VFA computing device, the simulation.

### Claim 13 (depends on 12)

The computer-implemented method of claim 12, wherein determining the time of the traffic collision comprises:
retrieving, by the VFA computing device, vehicle telematics data; and
identifying, by the VFA computing device, the time based upon the vehicle telematics data.

### Claim 14 (depends on 13)

The computer-implemented method of claim 13, wherein retrieving the vehicle telematics data comprises retrieving, by the VFA computing device, the vehicle telematics data from one or more of an automated vehicle, a mobile phone device, or a telematics device.

### Claim 15 (depends on 12)

The computer-implemented method of claim 12, wherein determining the location of the traffic collision comprises retrieving, by the VFA computing device, geographic coordinates from one or more of an automated vehicle, a mobile phone device, or a telematics device.

### Claim 16 (depends on 12)

The computer-implemented method of claim 12, wherein determining the time and the location comprises retrieving, by the VFA computing device, a timestamp and geographic coordinates from a mobile phone device.

### Claim 17 (depends on 12)

The computer-implemented method of claim 12, wherein determining the time and the location comprises:
retrieving, by the VFA computing device, a document including the time and geographic coordinates indicating the location; and
parsing, by the VFA computing device, the document to determine the time and the location.

### Claim 18 (depends on 12)

The computer-implemented method of claim 12, wherein the speech data includes an audio signal and said computer-implemented method further comprises converting, by the VFA computing device, the audio signal into text.

### Claim 19 (depends on 18)

The computer-implemented method of claim 18, further comprising displaying, by the VFA computing device, the text.

### Claim 20

An autonomous vehicle (AV) comprising a vehicle forensics analytics (“VFA”) computing device, said VFA computing device comprising a processor in communication with a memory device, said processor configured to:
determine a time and a location of a traffic collision involving the AV;
retrieve map data and contextual data associated with the time and the location of the traffic collision;
receive speech data, the speech data corresponding to a statement given by a witness of the traffic collision;
parse the speech data for phrases describing the traffic collision;
determine, based upon the parsed speech data, 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 including a representation of the AV based upon the map data, the contextual data, and the parsed speech data; and the determined position and orientation of the AV for each of the plurality of moments in time; and
display the simulation.