Patents by Inventor Vishal Suresh Vaingankar
Vishal Suresh Vaingankar has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11899458Abstract: Described herein are technologies relating to computing a likelihood of an operation-influencing event with respect to an autonomous vehicle at a geographic location. The likelihood of the operation-influencing event is computed based upon a prediction of a value that indicates whether, through a causal process, the operation-influencing event is expected to occur. The causal process is identified by means of a model, which relates spatiotemporal factors and the operation-influencing events.Type: GrantFiled: January 16, 2023Date of Patent: February 13, 2024Assignee: GM CRUISE HOLDINGS LLCInventors: Antony Joseph, Geoffrey Louis Chi-Johnston, Nimish Patil, Vishal Suresh Vaingankar, Laura Athena Freeman
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Patent number: 11899452Abstract: Various technologies described herein pertain to routing an autonomous vehicle based upon risk of takeover of the autonomous vehicle by a human operator. A computing system receives an origin location and a destination location of the autonomous vehicle. The computing system identifies a route for the autonomous vehicle to follow from the origin location to the destination location based upon output of a computer-implemented model. The computer-implemented model is generated based upon labeled data indicative of instances in which autonomous vehicles are observed to transition from operating autonomously to operating based upon conduction by human operators while the autonomous vehicles are executing predefined maneuvers. The computer-implemented model takes, as input, an indication of a maneuver in the predefined maneuvers that is performed by the autonomous vehicle when the autonomous vehicle follows a candidate route.Type: GrantFiled: August 31, 2021Date of Patent: February 13, 2024Assignee: GM CRUISE HOLDINGS LLCInventors: Geoffrey Louis Chi-Johnston, Vishal Suresh Vaingankar, Antony Joseph, Sean Gregory Skwerer, Lucio Otavio Marchioro Rech, Nitin Kumar Passa, Laura Athena Freeman, George Herbert Hines
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Publication number: 20230168674Abstract: Described herein are technologies relating to computing a likelihood of an operation-influencing event with respect to an autonomous vehicle at a geographic location. The likelihood of the operation-influencing event is computed based upon a prediction of a value that indicates whether, through a causal process, the operation-influencing event is expected to occur. The causal process is identified by means of a model, which relates spatiotemporal factors and the operation-influencing events.Type: ApplicationFiled: January 16, 2023Publication date: June 1, 2023Inventors: Antony Joseph, Geoffrey Louis Chi-Johnston, Nimish Patil, Vishal Suresh Vaingankar, Laura Athena Freeman
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Publication number: 20230152813Abstract: Various technologies described herein pertain to routing autonomous vehicles based upon spatiotemporal factors. A computing system receives an origin location and a destination location of an autonomous vehicle. The computing system identifies a route for the autonomous vehicle to follow from the origin location to the destination location based upon output of a spatiotemporal statistical model. The spatiotemporal statistical model is generated based upon historical data from autonomous vehicles when the autonomous vehicles undergo operation-influencing events. The spatiotemporal statistical model takes, as input, a location, a time, and a direction of travel of the autonomous vehicle. The spatiotemporal statistical model outputs a score that is indicative of a likelihood that the autonomous vehicle will undergo an operation-influencing event due to the autonomous vehicle encountering a spatiotemporal factor along a candidate route.Type: ApplicationFiled: January 17, 2023Publication date: May 18, 2023Inventors: Antony Joseph, Geoffrey Louis Chi-Johnston, Vishal Suresh Vaingankar, Laura Athena Freeman
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Patent number: 11579609Abstract: Described herein are technologies relating to computing a likelihood of an operation-influencing event with respect to an autonomous vehicle at a geographic location. The likelihood of the operation-influencing event is computed based upon a prediction of a value that indicates whether, through a causal process, the operation-influencing event is expected to occur. The causal process is identified by means of a model, which relates spatiotemporal factors and the operation-influencing events.Type: GrantFiled: June 30, 2021Date of Patent: February 14, 2023Assignee: GM CRUISE HOLDINGS LLCInventors: Antony Joseph, Geoffrey Louis Chi-Johnston, Nimish Patil, Vishal Suresh Vaingankar, Laura Athena Freeman
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Patent number: 11561547Abstract: Various technologies described herein pertain to routing autonomous vehicles based upon spatiotemporal factors. A computing system receives an origin location and a destination location of an autonomous vehicle. The computing system identifies a route for the autonomous vehicle to follow from the origin location to the destination location based upon output of a spatiotemporal statistical model. The spatiotemporal statistical model is generated based upon historical data from autonomous vehicles when the autonomous vehicles undergo operation-influencing events. The spatiotemporal statistical model takes, as input, a location, a time, and a direction of travel of the autonomous vehicle. The spatiotemporal statistical model outputs a score that is indicative of a likelihood that the autonomous vehicle will undergo an operation-influencing event due to the autonomous vehicle encountering a spatiotemporal factor along a candidate route.Type: GrantFiled: February 20, 2019Date of Patent: January 24, 2023Assignee: GM CRUISE HOLDINGS LLCInventors: Antony Joseph, Geoffrey Louis Chi-Johnston, Vishal Suresh Vaingankar, Laura Athena Freeman
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Publication number: 20210397184Abstract: Various technologies described herein pertain to routing an autonomous vehicle based upon risk of takeover of the autonomous vehicle by a human operator. A computing system receives an origin location and a destination location of the autonomous vehicle. The computing system identifies a route for the autonomous vehicle to follow from the origin location to the destination location based upon output of a computer-implemented model. The computer-implemented model is generated based upon labeled data indicative of instances in which autonomous vehicles are observed to transition from operating autonomously to operating based upon conduction by human operators while the autonomous vehicles are executing predefined maneuvers. The computer-implemented model takes, as input, an indication of a maneuver in the predefined maneuvers that is performed by the autonomous vehicle when the autonomous vehicle follows a candidate route.Type: ApplicationFiled: August 31, 2021Publication date: December 23, 2021Inventors: Geoffrey Louis Chi-Johnston, Vishal Suresh Vaingankar, Antony Joseph, Sean Gregory Skwerer, Lucio Otavio Marchioro Rech, Nitin Kumar Passa, Laura Athena Freeman, George Herbert Hines
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Publication number: 20210325883Abstract: Described herein are technologies relating to computing a likelihood of an operation-influencing event with respect to an autonomous vehicle at a geographic location. The likelihood of the operation-influencing event is computed based upon a prediction of a value that indicates whether, through a causal process, the operation-influencing event is expected to occur. The causal process is identified by means of a model, which relates spatiotemporal factors and the operation-influencing events.Type: ApplicationFiled: June 30, 2021Publication date: October 21, 2021Inventors: Antony Joseph, Geoffrey Louis Chi-Johnston, Nimish Patil, Vishal Suresh Vaingankar, Laura Athena Freeman
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Patent number: 11112794Abstract: Various technologies described herein pertain to routing an autonomous vehicle based upon risk of takeover of the autonomous vehicle by a human operator. A computing system receives an origin location and a destination location of the autonomous vehicle. The computing system identifies a route for the autonomous vehicle to follow from the origin location to the destination location based upon output of a computer-implemented model. The computer-implemented model is generated based upon labeled data indicative of instances in which autonomous vehicles are observed to transition from operating autonomously to operating based upon conduction by human operators while the autonomous vehicles are executing predefined maneuvers. The computer-implemented model takes, as input, an indication of a maneuver in the predefined maneuvers that is performed by the autonomous vehicle when the autonomous vehicle follows a candidate route.Type: GrantFiled: February 20, 2019Date of Patent: September 7, 2021Assignee: GM CRUISE HOLDINGS LLCInventors: Geoffrey Louis Chi-Johnston, Vishal Suresh Vaingankar, Antony Joseph, Sean Gregory Skwerer, Lucio Otavio Marchioro Rech, Nitin Kumar Passa, Laura Athena Freeman, George Herbert Hines
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Patent number: 11086322Abstract: Described herein are technologies relating to computing a likelihood of an operation-influencing event with respect to an autonomous vehicle at a geographic location. The likelihood of the operation-influencing event is computed based upon a prediction of a value that indicates whether, through a causal process, the operation-influencing event is expected to occur. The causal process is identified by means of a model, which relates spatiotemporal factors and the operation-influencing events.Type: GrantFiled: March 19, 2019Date of Patent: August 10, 2021Assignee: GM Cruise Holdings LLCInventors: Antony Joseph, Geoffrey Louis Chi-Johnston, Nimish Patil, Vishal Suresh Vaingankar, Laura Athena Freeman
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Publication number: 20200301419Abstract: Described herein are technologies relating to computing a likelihood of an operation-influencing event with respect to an autonomous vehicle at a geographic location. The likelihood of the operation-influencing event is computed based upon a prediction of a value that indicates whether, through a causal process, the operation-influencing event is expected to occur. The causal process is identified by means of a model, which relates spatiotemporal factors and the operation-influencing events.Type: ApplicationFiled: March 19, 2019Publication date: September 24, 2020Inventors: Antony Joseph, Geoffrey Louis Chi-Johnston, Nimish Patil, Vishal Suresh Vaingankar, Laura Athena Freeman
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Publication number: 20200264605Abstract: Various technologies described herein pertain to routing an autonomous vehicle based upon risk of takeover of the autonomous vehicle by a human operator. A computing system receives an origin location and a destination location of the autonomous vehicle. The computing system identifies a route for the autonomous vehicle to follow from the origin location to the destination location based upon output of a computer-implemented model. The computer-implemented model is generated based upon labeled data indicative of instances in which autonomous vehicles are observed to transition from operating autonomously to operating based upon conduction by human operators while the autonomous vehicles are executing predefined maneuvers. The computer-implemented model takes, as input, an indication of a maneuver in the predefined maneuvers that is performed by the autonomous vehicle when the autonomous vehicle follows a candidate route.Type: ApplicationFiled: February 20, 2019Publication date: August 20, 2020Inventors: Geoffrey Louis Chi-Johnston, Vishal Suresh Vaingankar, Antony Joseph, Sean Gregory Skwerer, Lucio Otavio Marchioro Rech, Nitin Kumar Passa, Laura Athena Freeman, George Herbert Hines
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Publication number: 20200264619Abstract: Various technologies described herein pertain to routing autonomous vehicles based upon spatiotemporal factors. A computing system receives an origin location and a destination location of an autonomous vehicle. The computing system identifies a route for the autonomous vehicle to follow from the origin location to the destination location based upon output of a spatiotemporal statistical model. The spatiotemporal statistical model is generated based upon historical data from autonomous vehicles when the autonomous vehicles undergo operation-influencing events. The spatiotemporal statistical model takes, as input, a location, a time, and a direction of travel of the autonomous vehicle. The spatiotemporal statistical model outputs a score that is indicative of a likelihood that the autonomous vehicle will undergo an operation-influencing event due to the autonomous vehicle encountering a spatiotemporal factor along a candidate route.Type: ApplicationFiled: February 20, 2019Publication date: August 20, 2020Inventors: Antony Joseph, Geoffrey Louis Chi-Johnston, Vishal Suresh Vaingankar, Laura Athena Freeman