Predictive teleoperator situational awareness
First Claim
1. A teleoperation system comprising:
- at least one processor; and
at least one memory having stored thereon processor-executable instructions that, when executed by the system, configure the teleoperation system to;
obtain via a network interface a first request for teleoperator assistance from a first driverless vehicle and at least one of first operation state data or first sensor data from the first driverless vehicle;
obtain teleoperator input via a user interface;
transmit a first guidance signal to the first driverless vehicle via the network interface based at least in part on the teleoperator input;
store as historical teleoperation data at least part of the teleoperator input and a first descriptor, the first descriptor determined based at least part on at least one of the first request, the first operation state data, or the first sensor data;
obtain via the network interface a second request for teleoperator assistance from a second driverless vehicle and at least one of second operation state data or second sensor data;
determine a second descriptor based at least in part on the second request, the second operation state data, or the second sensor data;
determine a distance between the first descriptor and the second descriptor in a descriptor space; and
perform an action based at least in part on the distance.
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Accused Products
Abstract
A teleoperator device may be configured to obtain a request for teleoperator assistance from a driverless vehicle and obtain teleoperator data in response to the request. The teleoperator device may also be configured to record at least some of the teleoperator input and/or guidance transmitted to the driverless vehicle based on the teleoperator input. Upon receiving a subsequent request, the teleoperator device may be configured to reproduce at least part of the former teleoperator input and/or to provide an option to activate guidance associated with the teleoperator input. The teleoperator device may also be configured to train a model and/or use a model to determine from vehicle data an option for presentation via a teleoperator interface and/or a presentation configuration of the teleoperator interface.
154 Citations
20 Claims
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1. A teleoperation system comprising:
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at least one processor; and at least one memory having stored thereon processor-executable instructions that, when executed by the system, configure the teleoperation system to; obtain via a network interface a first request for teleoperator assistance from a first driverless vehicle and at least one of first operation state data or first sensor data from the first driverless vehicle; obtain teleoperator input via a user interface; transmit a first guidance signal to the first driverless vehicle via the network interface based at least in part on the teleoperator input; store as historical teleoperation data at least part of the teleoperator input and a first descriptor, the first descriptor determined based at least part on at least one of the first request, the first operation state data, or the first sensor data; obtain via the network interface a second request for teleoperator assistance from a second driverless vehicle and at least one of second operation state data or second sensor data; determine a second descriptor based at least in part on the second request, the second operation state data, or the second sensor data; determine a distance between the first descriptor and the second descriptor in a descriptor space; and perform an action based at least in part on the distance. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A non-transitory computer-readable storage medium having computer-executable instructions stored thereupon which, when executed by a computer, cause the computer to:
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cause presentation of vehicle data obtained responsive to a request for assistance from a driverless vehicle via a user interface; capture one or more teleoperator interactions via the user interface; transmit a guidance signal to the driverless vehicle based at least in part on the one or more teleoperator interactions; determine, based at least in part on the vehicle data, a descriptor, the descriptor comprising at least one of a tensor or a vector; and train a model based on at least one of the descriptor, the presentation, the one or more teleoperator interactions, or the guidance signal, the model configured to; receive the descriptor as input; and determine, based at least in part on the input, an output of at least one of; an option for presentation via the user interface, or a presentation configuration of the presentation. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16, 17)
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18. A computer-implemented method comprising:
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obtaining vehicle data from a driverless vehicle; determining a descriptor based at least in part on a subset of the vehicle data, wherein the descriptor comprises a representation of the subset formatted such that the descriptor may be provided as input to a machine-learned model and the subset comprises at least one of sensor data, a detected object, event data, vehicle state data, or environmental data; evaluating the machine-learned model using the descriptor to identify at least one of a teleoperator option or a presentation configuration that corresponds to the at least one of the tensor or the string via the machine-learned model; and causing at least one of presentation of the teleoperator option via a user interface or configuration of the user interface according to the presentation configuration. - View Dependent Claims (19, 20)
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Specification