TRAFFIC LIGHT DETECTION AND LANE STATE RECOGNITION FOR AUTONOMOUS VEHICLES
First Claim
1. A method of training a model for determining states of lanes of interest, the method comprising:
- receiving, by one or more server computing devices, image data including an image and an associated label identifying at least one traffic light, a state of the at least one traffic light, and a lane controlled by the at least one traffic light; and
training, by the one or more server computing devices, the model using the image data such that the model is configured to, in response to receiving an image and a lane of interest included in the image, output a lane state for the lane of interest.
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Accused Products
Abstract
Aspects of the disclosure relate to training and using a model for determine states of lanes of interest. For instance, image data including an image and an associated label identifying at least one traffic light, a state of the at least one traffic light, and a lane controlled by the at least one traffic light may be received and used to train the mode such that the model is configured to, in response to receiving an image and a lane of interest included in the image, output a lane state for the lane of interest. This model may then be used by a vehicle in order to determine a state of a lane of interest. This state may then be used to control the vehicle in an autonomous driving mode based on the state of the lane of interest.
13 Citations
20 Claims
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1. A method of training a model for determining states of lanes of interest, the method comprising:
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receiving, by one or more server computing devices, image data including an image and an associated label identifying at least one traffic light, a state of the at least one traffic light, and a lane controlled by the at least one traffic light; and training, by the one or more server computing devices, the model using the image data such that the model is configured to, in response to receiving an image and a lane of interest included in the image, output a lane state for the lane of interest. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A method of using a model to determine states of lanes of interest, the method comprising:
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receiving, by one or more processors, an image generated by a perception system of a vehicle; identifying, by the one or more processors, a lane of interest; using, by the one or more processors, the image and the lane of interest as input into the model to output a state of the lane of interest according to a state of a traffic light in the image; and controlling, by the one or more processors, the vehicle in an autonomous driving mode based on the state of the lane of interest. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 19)
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18. A system for using a model to determine states of lanes of interest, the system comprising one or more processors configured to:
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receive an image generated by a perception system of a vehicle; identify a lane of interest; use the image and the lane of interest as input into the model to output a state of the lane of interest according to a state of a traffic light in the image; and control the vehicle in an autonomous driving mode based on the state of the lane of interest. - View Dependent Claims (20)
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Specification