Patents by Inventor Martin Levihn
Martin Levihn 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).
-
Publication number: 20230124864Abstract: A graph representation of a tactical map representing a plurality of static components of an environment of a vehicle is generated. Nodes of the graph represent static components, and edges represent relationships between multiple static components. Different edge types are used to indicate respective relationship semantics among the static components. Individual nodes are represented as having the same number and types of edges in the graph. Using the graph as input to a neural network based model, a set of results is obtained. A motion control directive based at least in part on the results is transmitted to a motion-control subsystem of the vehicle.Type: ApplicationFiled: December 21, 2022Publication date: April 20, 2023Applicant: Apple Inc.Inventors: Martin Levihn, Jürgen Wiest, Pekka Tapani Raiko, Anayo Kenechukwu Akametalu
-
Patent number: 11614739Abstract: Implementations described and claimed herein provide systems and methods for controlling an autonomous vehicle. In one implementation, the autonomous vehicle is navigated towards a flow of traffic with a first gap between first and second vehicles and a second gap following the second vehicle. A motion plan for directing the autonomous vehicle into the flow of traffic at an interaction zone is generated based on whether an ability of the autonomous vehicle to enter the interaction zone at the second gap exceeds a confidence threshold. The autonomous vehicle is autonomously navigated into the flow of traffic at the first gap when the confidence threshold is exceeded. The motion plan forgoes navigation of the autonomous vehicle into the flow of traffic at the first and second gaps when the ability of the autonomous vehicle to enter the interaction zone at the second gap does not exceed the confidence threshold.Type: GrantFiled: September 11, 2020Date of Patent: March 28, 2023Assignee: Apple Inc.Inventors: Ujjwal Das Gupta, Sandip Aine, Martin Levihn, Trevor P. Barron, Jamie R. Lesser
-
Patent number: 11555706Abstract: A graph representation of a tactical map representing a plurality of static components of an environment of a vehicle is generated. Nodes of the graph represent static components, and edges represent relationships between multiple static components. Different edge types are used to indicate respective relationship semantics among the static components. Individual nodes are represented as having the same number and types of edges in the graph. Using the graph as input to a neural network based model, a set of results is obtained. A motion control directive based at least in part on the results is transmitted to a motion-control subsystem of the vehicle.Type: GrantFiled: September 26, 2018Date of Patent: January 17, 2023Assignee: Apple Inc.Inventors: Martin Levihn, Jürgen Wiest, Pekka Tapani Raiko, Anayo Kenechukwu Akametalu
-
Publication number: 20220374712Abstract: A behavior planner for a vehicle generates a plurality of conditional action sequences of the vehicle using a tree search algorithm and heuristics obtained from one or more machine learning models. Each sequence corresponds to a sequence of anticipated states of the vehicle. At least some of the action sequences are provided to a motion selector of the vehicle. The motion selector generates motion-control directives based on the received conditional action sequences and on data received from one or more sensors of the vehicle, and transmits the directives to control subsystems of the vehicle.Type: ApplicationFiled: July 29, 2022Publication date: November 24, 2022Applicant: Apple Inc.Inventors: Joshua D. Redding, Luke B. Johnson, Martin Levihn, Nicolas F. Meuleau, Sebastian Brechtel
-
Patent number: 11403526Abstract: A behavior planner for a vehicle generates a plurality of conditional action sequences of the vehicle using a tree search algorithm and heuristics obtained from one or more machine learning models. Each sequence corresponds to a sequence of anticipated states of the vehicle. At least some of the action sequences are provided to a motion selector of the vehicle. The motion selector generates motion-control directives based on the received conditional action sequences and on data received from one or more sensors of the vehicle, and transmits the directives to control subsystems of the vehicle.Type: GrantFiled: September 4, 2020Date of Patent: August 2, 2022Assignee: Apple Inc.Inventors: Joshua D. Redding, Luke B. Johnson, Martin Levihn, Nicolas F. Meuleau, Sebastian Brechtel
-
Patent number: 11243532Abstract: A set of actions corresponding to a particular state of the environment of a vehicle is identified. A respective encoding is generated for different actions of the set, using elements such as distinct colors to distinguish attributes such as target lane segments. Using the encodings as inputs to respective instances of a machine learning model, respective value metrics are estimated for each of the actions. One or more motion-control directives to implement a particular action selected using the value metrics are transmitted to motion-control subsystems of the vehicle.Type: GrantFiled: September 26, 2018Date of Patent: February 8, 2022Assignee: Apple Inc.Inventors: Martin Levihn, Pekka Tapani Raiko
-
Publication number: 20210089041Abstract: Implementations described and claimed herein provide systems and methods for controlling an autonomous vehicle. In one implementation, the autonomous vehicle is navigated towards a flow of traffic with a first gap between first and second vehicles and a second gap following the second vehicle. A motion plan for directing the autonomous vehicle into the flow of traffic at an interaction zone is generated based on whether an ability of the autonomous vehicle to enter the interaction zone at the second gap exceeds a confidence threshold. The autonomous vehicle is autonomously navigated into the flow of traffic at the first gap when the confidence threshold is exceeded. The motion plan forgoes navigation of the autonomous vehicle into the flow of traffic at the first and second gaps when the ability of the autonomous vehicle to enter the interaction zone at the second gap does not exceed the confidence threshold.Type: ApplicationFiled: September 11, 2020Publication date: March 25, 2021Inventors: Ujjwal Das Gupta, Sandip Aine, Martin Levihn, Trevor P. Barron, Jamie R. Lesser
-
Publication number: 20200401892Abstract: A behavior planner for a vehicle generates a plurality of conditional action sequences of the vehicle using a tree search algorithm and heuristics obtained from one or more machine learning models. Each sequence corresponds to a sequence of anticipated states of the vehicle. At least some of the action sequences are provided to a motion selector of the vehicle. The motion selector generates motion-control directives based on the received conditional action sequences and on data received from one or more sensors of the vehicle, and transmits the directives to control subsystems of the vehicle.Type: ApplicationFiled: September 4, 2020Publication date: December 24, 2020Applicant: Apple Inc.Inventors: Joshua D. Redding, Luke B. Johnson, Martin Levihn, Nicolas F. Meuleau, Sebastian Brechtel
-
Patent number: 10769525Abstract: A behavior planner for a vehicle generates a plurality of conditional action sequences of the vehicle using a tree search algorithm and heuristics obtained from one or more machine learning models. Each sequence corresponds to a sequence of anticipated states of the vehicle. At least some of the action sequences are provided to a motion selector of the vehicle. The motion selector generates motion-control directives based on the received conditional action sequences and on data received from one or more sensors of the vehicle, and transmits the directives to control subsystems of the vehicle.Type: GrantFiled: September 22, 2017Date of Patent: September 8, 2020Assignee: Apple Inc.Inventors: Joshua D. Redding, Luke B. Johnson, Martin Levihn, Nicolas F. Meuleau, Sebastian Brechtel
-
Publication number: 20180089563Abstract: A behavior planner for a vehicle generates a plurality of conditional action sequences of the vehicle using a tree search algorithm and heuristics obtained from one or more machine learning models. Each sequence corresponds to a sequence of anticipated states of the vehicle. At least some of the action sequences are provided to a motion selector of the vehicle. The motion selector generates motion-control directives based on the received conditional action sequences and on data received from one or more sensors of the vehicle, and transmits the directives to control subsystems of the vehicle.Type: ApplicationFiled: September 22, 2017Publication date: March 29, 2018Applicant: Apple Inc.Inventors: Joshua D. Redding, Luke B. Johnson, Martin Levihn, Nicolas F. Meuleau, Sebastian Brechtel