US 12,147,227 B2
Robotic process automation for achieving an optimized margin of vehicle operational safety
Charles Howard Cella, Pembroke, MA (US)
Assigned to Strong Force TP Portfolio 2022, LLC, Fort Lauderdale, FL (US)
Filed by STRONG FORCE TP PORTFOLIO 2022, LLC, Fort Lauderdale, FL (US)
Filed on Dec. 22, 2023, as Appl. No. 18/395,136.
Application 18/395,136 is a continuation of application No. 17/977,550, filed on Oct. 31, 2022.
Application 17/977,550 is a continuation of application No. 16/887,557, filed on May 29, 2020.
Application 16/887,557 is a continuation of application No. 16/803,220, filed on Feb. 27, 2020.
Application 16/803,220 is a continuation of application No. PCT/US2019/053857, filed on Sep. 30, 2019.
Claims priority of provisional application 62/739,335, filed on Sep. 30, 2018.
Prior Publication US 2024/0126284 A1, Apr. 18, 2024
Int. Cl. G06N 20/00 (2019.01); B60W 40/08 (2012.01); G01C 21/34 (2006.01); G01C 21/36 (2006.01); G05B 13/02 (2006.01); G05D 1/00 (2006.01); G05D 1/224 (2024.01); G05D 1/225 (2024.01); G05D 1/226 (2024.01); G05D 1/227 (2024.01); G05D 1/228 (2024.01); G05D 1/229 (2024.01); G05D 1/24 (2024.01); G05D 1/646 (2024.01); G05D 1/69 (2024.01); G05D 1/692 (2024.01); G05D 1/81 (2024.01); G06F 40/40 (2020.01); G06N 3/04 (2023.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01); G06N 3/086 (2023.01); G06Q 30/0208 (2023.01); G06Q 50/18 (2012.01); G06Q 50/40 (2024.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 20/56 (2022.01); G06V 20/59 (2022.01); G06V 20/64 (2022.01); G07C 5/00 (2006.01); G07C 5/02 (2006.01); G07C 5/08 (2006.01); G10L 15/16 (2006.01); G10L 25/63 (2013.01); G06N 3/02 (2006.01); G06Q 30/02 (2023.01); G06Q 50/00 (2012.01)
CPC G05D 1/0022 (2013.01) [B60W 40/08 (2013.01); G01C 21/3438 (2013.01); G01C 21/3461 (2013.01); G01C 21/3469 (2013.01); G01C 21/3617 (2013.01); G05B 13/027 (2013.01); G05D 1/0088 (2013.01); G05D 1/0212 (2013.01); G05D 1/0287 (2013.01); G05D 1/224 (2024.01); G05D 1/225 (2024.01); G05D 1/226 (2024.01); G05D 1/227 (2024.01); G05D 1/228 (2024.01); G05D 1/229 (2024.01); G05D 1/24 (2024.01); G05D 1/646 (2024.01); G05D 1/69 (2024.01); G05D 1/692 (2024.01); G05D 1/81 (2024.01); G06F 40/40 (2020.01); G06N 3/0418 (2013.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06N 3/086 (2013.01); G06N 20/00 (2019.01); G06Q 30/0208 (2013.01); G06Q 50/188 (2013.01); G06Q 50/40 (2024.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 20/56 (2022.01); G06V 20/59 (2022.01); G06V 20/597 (2022.01); G06V 20/64 (2022.01); G07C 5/006 (2013.01); G07C 5/008 (2013.01); G07C 5/02 (2013.01); G07C 5/08 (2013.01); G07C 5/0808 (2013.01); G07C 5/0816 (2013.01); G07C 5/0866 (2013.01); G07C 5/0891 (2013.01); G10L 15/16 (2013.01); G10L 25/63 (2013.01); B60W 2040/0881 (2013.01); G06N 3/02 (2013.01); G06Q 30/0281 (2013.01); G06Q 50/01 (2013.01)] 17 Claims
OG exemplary drawing
 
1. A method for mimicking human operation of a vehicle by robotic process automation, the method comprising:
collecting human operator interactions with a vehicle control system interface operatively connected to the vehicle;
collecting vehicle response and operating conditions associated at least contemporaneously with the human operator interactions;
collecting environmental information associated at least contemporaneously with the human operator interactions and storing the environmental information in an environment data collection module;
training an artificial intelligence system to control the vehicle with an optimized margin of safety while mimicking the human operator, the training including instructing the artificial intelligence system to take an input from the environment data collection module about instances of the environmental information associated at least contemporaneously with the collected vehicle response and operating conditions, wherein the optimized margin of safety is achieved by training the artificial intelligence system to control the vehicle based on a set of human operator interaction data collected from interactions of an expert human vehicle operator and a set of outcome data from a set of vehicle safety events;
configuring a set of expert systems to provide outputs based on which a transportation system manages transportation-related parameters, wherein the transportation-related parameters facilitate operation of at least one of: a set of vehicles, a fleet of vehicles, or a transportation system user experience;
configuring a plurality of visual elements representing a set of attributes and parameters of the set of expert systems; and
manipulating at least one of the plurality of visual elements, thereby causing configuration of the set of expert systems.