Abstract: The subject disclosure relates to techniques for adjusting an exposure setting. A process of the disclosed technology can include steps for determining a localization parameter of an autonomous vehicle, the localization parameter including a geographic position of the autonomous vehicle, determining a region of interest based on the localization parameter of the autonomous vehicle, receiving a first image including the region of interest based on the localization parameter of the autonomous vehicle, determining an exposure setting for the region of interest in the first image, and adjusting an exposure setting of the first image to the exposure setting for the region of interest in the first image. Systems and machine-readable media are also provided.

Abstract: An autonomous vehicle incorporating a multimodal multi-technique signal fusion system is described herein. The signal fusion system is configured to receive at least one sensor signal that is output by at least one sensor system (multimodal), such as at least one image sensor signal from at least one camera. The at least one sensor signal is provided to a plurality of object detector modules of different types (multi-technique), such as an absolute detector module and a relative activation detector module, that generate independent directives based on the at least one sensor signal. The independent directives are fused by a signal fusion module to output a fused directive for controlling the autonomous vehicle.

Abstract: Systems, methods, and computer-readable media are provided for receiving traffic object data from a plurality of autonomous vehicles, the traffic object data including a geographic location of a traffic object, comparing the traffic object data of each of the plurality of autonomous vehicles with known traffic object data, determining a discrepancy between the traffic object data of each of the plurality of autonomous vehicles and the known traffic object data, grouping the traffic object data of each of the plurality of autonomous vehicles based on the determining of the discrepancy between the traffic object data of each of the plurality of autonomous vehicles and the known traffic object data, determining whether a group of traffic object data of the grouping of the traffic object data of each of the plurality of autonomous vehicles exceeds a threshold; and updating a traffic object map based on the traffic object data of the group that exceeds the threshold.

Abstract: The subject disclosure relates to techniques for improving map labeling and in particular, for automating process of semantically labeling maps used for autonomous vehicle (AV) navigation. In some aspects, a process of the disclosed technology includes steps for receiving a three-dimensional (3D) Light Detection and Ranging (LiDAR) map, processing the 3D LiDAR map to produce a 2D map, rasterizing the 2D map into a plurality of map tiles, and providing one or more of the map tiles to a machine-learning (ML) labeler, wherein the ML labeler is configured to identify and label image features in at least one of the one or more map tiles. Systems and machine-readable media are also provided.

Abstract: The subject disclosure relates to techniques for adjusting an exposure setting. A process of the disclosed technology can include steps for determining a localization parameter of an autonomous vehicle, the localization parameter including a geographic position of the autonomous vehicle, determining a region of interest based on the localization parameter of the autonomous vehicle, receiving a first image including the region of interest based on the localization parameter of the autonomous vehicle, determining an exposure setting for the region of interest in the first image, and adjusting an exposure setting of the first image to the exposure setting for the region of interest in the first image. Systems and machine-readable media are also provided.

Abstract: The subject disclosure relates to techniques for detecting an object. A process of the disclosed technology can include steps for receiving three-dimensional (3D) Light Detection and Ranging (LiDAR) data of the object at a first time, generating a first point cloud based on the 3D LiDAR data at the first time, receiving 3D LiDAR data of the object at a second time, generating a second point cloud based on the 3D LiDAR data at the second time, aggregating the first point cloud and the second point cloud to form an aggregated point cloud, and placing a bounding box around the aggregated point cloud. Systems and machine-readable media are also provided.

Abstract: The subject disclosure relates to techniques for adjusting an exposure setting. A process of the disclosed technology can include steps for determining a localization parameter of an autonomous vehicle, the localization parameter including a geographic position of the autonomous vehicle, determining a region of interest based on the localization parameter of the autonomous vehicle, receiving a first image including the region of interest based on the localization parameter of the autonomous vehicle, determining an exposure setting for the region of interest in the first image, and adjusting an exposure setting of the first image to the exposure setting for the region of interest in the first image. Systems and machine-readable media are also provided.

Abstract: Systems, methods, and computer-readable media are provided for receiving traffic object data from a plurality of autonomous vehicles, comparing the traffic object data of each of the plurality of autonomous vehicles with known traffic object data, determining a discrepancy between the traffic object data of each of the plurality of autonomous vehicles and the known traffic object data, grouping the traffic object data of each of the plurality of autonomous vehicles based on the determining of the discrepancy between the traffic object data of each of the plurality of autonomous vehicles and the known traffic object data, determining whether a group of traffic object data of the grouping of the traffic object data of each of the plurality of autonomous vehicles exceeds a threshold, and updating a traffic object map based on the traffic object data of the group that exceeds the threshold.

Abstract: The subject disclosure relates to techniques for detecting an object. A process of the disclosed technology can include steps for receiving three-dimensional (3D) Light Detection and Ranging (LiDAR) data of the object at a first time, generating a first point cloud based on the 3D LiDAR data at the first time, receiving 3D LiDAR data of the object at a second time, generating a second point cloud based on the 3D LiDAR data at the second time, aggregating the first point cloud and the second point cloud to form an aggregated point cloud, and placing a bounding box around the aggregated point cloud. Systems and machine-readable media are also provided.

Abstract: The subject disclosure relates to techniques for inserting of bounding boxes around image objects. A process of the disclosed technology can include steps for receiving, from a first data set, an image comprising a first image object, processing the image to identify a pixel region associated with the first image object, and placing a first bounding box around the first image object based on the identified pixel region. In some aspects, the process further includes steps for receiving a user input comprising an indication of whether the first bounding box is accurately placed around the first image object. Systems and machine-readable media are also provided.

Abstract: The subject disclosure relates to techniques for adjusting an exposure setting. A process of the disclosed technology can include steps for determining a localization parameter of an autonomous vehicle, the localization parameter including a geographic position of the autonomous vehicle, determining a region of interest based on the localization parameter of the autonomous vehicle, receiving a first image including the region of interest based on the localization parameter of the autonomous vehicle, determining an exposure setting for the region of interest in the first image, and adjusting an exposure setting of the first image to the exposure setting for the region of interest in the first image. Systems and machine-readable media are also provided.

Abstract: The subject disclosure relates to techniques for adjusting an exposure setting. A process of the disclosed technology can include steps for determining a localization parameter of an autonomous vehicle, the localization parameter including a geographic position of the autonomous vehicle, determining a region of interest based on the localization parameter of the autonomous vehicle, receiving a first image including the region of interest based on the localization parameter of the autonomous vehicle, determining an exposure setting for the region of interest in the first image, and adjusting an exposure setting of the first image to the exposure setting for the region of interest in the first image. Systems and machine-readable media are also provided.

Abstract: Systems, methods, and computer-readable media are provided for receiving traffic object data from a plurality of autonomous vehicles, the traffic object data including a geographic location of a traffic object, comparing the traffic object data of each of the plurality of autonomous vehicles with known traffic object data, determining a discrepancy between the traffic object data of each of the plurality of autonomous vehicles and the known traffic object data, grouping the traffic object data of each of the plurality of autonomous vehicles based on the determining of the discrepancy between the traffic object data of each of the plurality of autonomous vehicles and the known traffic object data, determining whether a group of traffic object data of the grouping of the traffic object data of each of the plurality of autonomous vehicles exceeds a threshold; and updating a traffic object map based on the traffic object data of the group that exceeds the threshold.

Abstract: The subject disclosure relates to techniques for inserting of bounding boxes around image objects. A process of the disclosed technology can include steps for receiving, from a first data set, an image comprising a first image object, processing the image to identify a pixel region associated with the first image object, and placing a first bounding box around the first image object based on the identified pixel region. In some aspects, the process further includes steps for receiving a user input comprising an indication of whether the first bounding box is accurately placed around the first image object. Systems and machine-readable media are also provided.

Abstract: The subject disclosure relates to techniques for inserting of bounding boxes around image objects. A process of the disclosed technology can include steps for receiving an image comprising an image object, receiving a centroid input, wherein the centroid input indicates an approximate centroid location of the image object, and processing the first image and the centroid input to identify a pixel region associated with the first image object. In some aspects, the process can further include steps for placing a bounding box around the image object based on the identified pixel region. Systems and machine-readable media are also provided.

Abstract: The subject disclosure relates to techniques for detecting an object. A process of the disclosed technology can include steps for receiving three-dimensional (3D) Light Detection and Ranging (LiDAR) data of the object at a first time, generating a first point cloud based on the 3D LiDAR data at the first time, receiving 3D LiDAR data of the object at a second time, generating a second point cloud based on the 3D LiDAR data at the second time, aggregating the first point cloud and the second point cloud to form an aggregated point cloud, and placing a bounding box around the aggregated point cloud. Systems and machine-readable media are also provided.

Abstract: The subject disclosure relates to techniques for adjusting an exposure setting. A process of the disclosed technology can include steps for determining a localization parameter of an autonomous vehicle, the localization parameter including a geographic position of the autonomous vehicle, determining a region of interest based on the localization parameter of the autonomous vehicle, receiving a first image including the region of interest based on the localization parameter of the autonomous vehicle, determining an exposure setting for the region of interest in the first image, and adjusting an exposure setting of the first image to the exposure setting for the region of interest in the first image. Systems and machine-readable media are also provided.

Abstract: The subject disclosure relates to techniques for improving map labeling and in particular, for automating process of semantically labeling maps used for autonomous vehicle (AV) navigation. In some aspects, a process of the disclosed technology includes steps for receiving a three-dimensional (3D) Light Detection and Ranging (LiDAR) map, processing the 3D LiDAR map to produce a 2D map, rasterizing the 2D map into a plurality of map tiles, and providing one or more of the map tiles to a machine-learning (ML) labeler, wherein the ML labeler is configured to identify and label image features in at least one of the one or more map tiles. Systems and machine-readable media are also provided.

Abstract: Systems and methods are provided for analyzing traffic signal lights in order to control an autonomous vehicle. A method includes receiving an image from a camera regarding at least one traffic signal light and receiving data related to the traffic signal light. Neural networks determine location and characteristics of the traffic signal light.

Abstract: Systems and method are provided for controlling a vehicle. In one embodiment, a method includes calculating, via a router of a vehicle system that accesses road map data, at least one route to a destination based on the road map data, thereby producing route solution data. The vehicle system enters a remote assistance mode in response to remote assistance decision data received from a blockage arbiter of the vehicle system. In the remote assistance mode, the method includes determining, via the router, at least one road segment of the road map data that is permitted to be blacklisted, thereby producing permitted blacklist data. The method includes transmitting the permitted blacklist data and the route solution data, via a vehicle communications module of the vehicle system, to a remote vehicle assistance system. The method includes updating, via the router, the road map data to exclude at least one blacklisted road segment defined by the permitted blacklist data.