Abstract: A traffic signal analysis system for an autonomous vehicle (AV) can receive image data from one or more cameras, the image data including an upcoming traffic signaling system located at an intersection. The system can determine an action for the AV through the intersection and access a matching signal map specific to the upcoming traffic signaling system. Using the matching signal map, the system can generate a signal template for the upcoming traffic signaling system and determine a first subset and a second subset of the plurality of traffic signal faces that apply to the action. The system can dynamically analyze the first subset and the second subset to determine a state of the upcoming traffic signaling system for the action, and generate an output for the AV indicating the state of the upcoming traffic signaling system for the action.

Abstract: A traffic signal analysis system for an autonomous vehicle can receive image data from one or more cameras, the image data including an upcoming traffic signaling system located at an intersection. The system can determine an action for the AV through the intersection and access a matching signal map specific to the upcoming traffic signaling system. Using the matching signal map, the system can generate a signal template for the upcoming traffic signaling system and determine a first subset and a second subset of the plurality of traffic signal faces that apply to the action. The system can dynamically analyze the first subset and the second subset to determine a state of the upcoming traffic signaling system for the action, and generate an output for the AV indicating the state of the upcoming traffic signaling system for the action.

Abstract: A traffic signal analysis system for an autonomous vehicle (AV) can receive image data from one or more cameras, the image data including an upcoming traffic signaling system located at an intersection. The system can determine an action for the AV through the intersection and access a matching signal map specific to the upcoming traffic signaling system. Using the matching signal map, the system can generate a signal template for the upcoming traffic signaling system and determine a first subset and a second subset of the plurality of traffic signal faces that apply to the action. The system can dynamically analyze the first subset and the second subset to determine a state of the upcoming traffic signaling system for the action, and generate an output for the AV indicating the state of the upcoming traffic signaling system for the action.

Abstract: A self-driving vehicle (SDV) can operate by analyzing sensor data to autonomously control acceleration, braking, and steering systems of the SDV along a current route. The SDV includes a number of sensors generating the sensor data and a control system to detect conditions relating to the operation of the SDV, such as vehicle speed and local weather, select a set of sensors based on the detected conditions, and prioritize the sensor data generated from the selected set of sensors to control aspects relating to the operation of the SDV.

Abstract: An image capture device can include one or more image sensors and one or more image processors. The image sensor(s) can be configured to detect incoming light provided incident to a surface of each image sensor, each image sensor configured to provide full image frames of image capture data at a first resolution. The image processor(s) can be coupled to the image sensor(s) and configured to receive the image capture data at the first resolution, downsample the image capture data outside one or more regions of interest, and provide a digital image output having a second resolution within the one or more regions of interest and a third resolution outside the one or more regions of interest, wherein the third resolution is less than the second resolution.

Abstract: The present disclosure provides systems and methods for detecting, localizing, and classifying objects that are proximate to an autonomous vehicle. A sensor system can include one or more ranging systems and a plurality of cameras. The plurality of cameras can be positioned such that a field of view for each camera of the plurality of cameras overlaps a field of view of at least one adjacent camera. The one or more ranging systems can be configured to transmit ranging data to a perception system for detecting objects of interest and the plurality of cameras can be configured to transmit image data to the perception system for classifying the objects of interest.

Abstract: A self-driving vehicle (SDV) can operate by analyzing sensor data to autonomously control acceleration, braking, and steering systems of the SDV along a current route. The SDV includes a number of sensors generating the sensor data and a control system to detect conditions relating to the operation of the SDV, such as vehicle speed and local weather, select a set of sensors based on the detected conditions, and prioritize the sensor data generated from the selected set of sensors to control aspects relating to the operation of the SDV.

Abstract: A traffic signal analysis system for an autonomous vehicle can receive image data from one or more cameras, the image data including an upcoming traffic signaling system located at an intersection. The system can determine an action for the AV through the intersection and access a matching signal map specific to the upcoming traffic signaling system. Using the matching signal map, the system can generate a signal template for the upcoming traffic signaling system and determine a first subset and a second subset of the plurality of traffic signal faces that apply to the action. The system can dynamically analyze the first subset and the second subset to determine a state of the upcoming traffic signaling system for the action, and generate an output for the AV indicating the state of the upcoming traffic signaling system for the action.

Abstract: An image capture device can include one or more image sensors and one or more image processors. The image sensor(s) can be configured to detect incoming light provided incident to a surface of each image sensor, each image sensor configured to provide full image frames of image capture data at a first resolution. The image processor(s) can be coupled to the image sensor(s) and configured to receive the image capture data at the first resolution, downsample the image capture data outside one or more regions of interest, and provide a digital image output having a second resolution within the one or more regions of interest and a third resolution outside the one or more regions of interest, wherein the third resolution is less than the second resolution.

Abstract: A traffic signal analysis system can receive image data from one or more cameras of an autonomous vehicle, where the image data includes a traffic signaling system located at an intersection. The traffic signal analysis system can determine a pass-through action for the autonomous vehicle through the intersection, and access a matching signal map that includes characteristic information indicating properties of the traffic signaling system. Based on the characteristic information and the image data, the traffic signal analysis system can identify a state of the traffic signaling system for the pass-through action, and generate an output for the autonomous vehicle indicating the state of the traffic signaling system for the pass-through action.

Abstract: A traffic signal analysis system can receive image data from one or more cameras of an autonomous vehicle, where the image data includes a traffic signaling system located at an intersection. The traffic signal analysis system can determine a pass-through action for the autonomous vehicle through the intersection, and access a matching signal map that includes characteristic information indicating properties of the traffic signaling system. Based on the characteristic information and the image data, the traffic signal analysis system can identify a state of the traffic signaling system for the pass-through action, and generate an output for the autonomous vehicle indicating the state of the traffic signaling system for the pass-through action.

Abstract: The disclosed terrain model is a generative, probabilistic approach to modeling terrain that exploits the 3D spatial structure inherent in outdoor domains and an array of noisy but abundant sensor data to simultaneously estimate ground height, vegetation height and classify obstacles and other areas of interest, even in dense non-penetrable vegetation. Joint inference of ground height, class height and class identity over the whole model results in more accurate estimation of each quantity. Vertical spatial constraints are imposed on voxels within a column via a hidden semi-Markov model. Horizontal spatial constraints are enforced on neighboring columns of voxels via two interacting Markov random fields and a latent variable. Because of the rules governing abstracts, this abstract should not be used to construe the claims.