Systems and methods for modeling and simulation in vehicle forensics

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.

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.