US 12,205,420 B2
Systems and methods for detecting software interactions for autonomous vehicles within changing environmental conditions
Aaron Scott Chan, San Jose, CA (US); and Kenneth Jason Sanchez, San Francisco, CA (US)
Assigned to State Farm Mutual Automobile Insurance Company, Bloomington, IL (US)
Filed by State Farm Mutual Automobile Insurance Company, Bloomington, IL (US)
Filed on Apr. 12, 2022, as Appl. No. 17/719,072.
Application 17/719,072 is a continuation of application No. 16/376,843, filed on Apr. 5, 2019, granted, now 11,321,972.
Prior Publication US 2022/0237961 A1, Jul. 28, 2022
Int. Cl. G05D 1/02 (2020.01); G06N 20/00 (2019.01); G07C 5/00 (2006.01); G07C 5/08 (2006.01); H04L 67/12 (2022.01)
CPC G07C 5/0808 (2013.01) [G06N 20/00 (2019.01); G07C 5/008 (2013.01); G07C 5/085 (2013.01); H04L 67/12 (2013.01)] 20 Claims
OG exemplary drawing
 
1. An interaction detection and analysis (“IDA”) computing device comprising at least one processor in communication with at least one memory device, wherein the at least one processor is configured to:
store software ecosystem data, environmental condition data, and performance data in a plurality of data records in a database, wherein each data record i) is associated with one autonomous vehicle (AV) of a plurality of AVs and ii) includes the software ecosystem data, the environmental condition data, and the performance data of the corresponding AV;
identify, by applying at least one machine learning algorithm to a set of the plurality of data records, a software-environment interaction between at least one software application operating onboard the at least one AV and at least one environmental condition resulting in a particular outcome of operation of the at least one AV in the at least one environmental condition;
generate a confidence indicator indicating a strength of a correlation between the software-environment interaction and the particular outcome, the confidence indicator representing a likelihood that the software-environment interaction contributes to the particular outcome;
in response to the confidence indicator exceeding a predetermined threshold, transmit, to at least one AV associated with the set of data records, at least one alert message advising of the particular outcome; and
cause at least one of (i) a user device associated with an operator of the at least one AV or (ii) the at least one AV to notify the operator of the particular outcome.