Abstract: An autonomous vehicle including a network of one or more sensors positioned on a body of the autonomous vehicle, one or more display devices mounted on one or more exterior sides of the autonomous vehicle, at least one processor, and at least one memory storing instructions is disclosed. The instructions, when executed by the at least one processor, configure the at least one processor to: (i) receive sensor data from the network of one or more sensors; (ii) generate, from the sensor data, metadata associated with a motor vehicle in proximity of the autonomous vehicle; (iii) determine, based at least in part on the metadata, media content for displaying to a user of the motor vehicle; and (iv) initiate display of the media content on the one or more display devices mounted on the one or more exterior sides of the autonomous vehicle.

Abstract: A perception system is configured to: (i) initialize a grid with default values for a set of points in an environment of the perception system; (ii) based upon a first sensor data, identify a first subset of the set of points and features corresponding to a first point cloud; (iii) perform temporal alignment of the identified features corresponding to the first point cloud; (iv) update the grid using the temporally aligned features corresponding to the first point cloud; (v) based upon a second sensor data, identify a second subset of the set of points and features corresponding to a second point cloud; (vi) perform temporal alignment of the identified features corresponding to the second point cloud; and (vii) update the grid using the temporally aligned features corresponding to the second point cloud to display in a single reference frame with the temporally aligned features corresponding to the first point cloud.

Abstract: An autonomous vehicle including a network of one or more sensors positioned on a body of the autonomous vehicle, one or more display devices mounted on one or more exterior sides of the autonomous vehicle, at least one processor, and at least one memory storing instructions is disclosed. The instructions, when executed by the at least one processor, configure the at least one processor to: (i) receive sensor data from the network of one or more sensors; (ii) generate, from the sensor data, metadata associated with a motor vehicle in proximity of the autonomous vehicle; (iii) determine, based at least in part on the metadata, media content for displaying to a user of the motor vehicle; and (iv) initiate display of the media content on the one or more display devices mounted on the one or more exterior sides of the autonomous vehicle.

Abstract: In one aspect, a method of fusing sensor data from a plurality of sensors is provided. The method comprises identifying first and second sensor data from first and second sensors of the plurality of sensors, respectively, extracting first and second features from the first and second sensor data, respectively, and converting the first and second features to first and second BEV projections of the first and second features, respectively. The method further comprises implementing a spatial transform network that aligns the second BEV projection with the first BEV projection, and generating a fused feature map comprising the aligned second BEV projection and the first BEV projection.

Abstract: Embodiments herein include an automated vehicle performing for identifying vehicles and lanes in roadway by an autonomy system of an automated vehicle. The autonomy system gathers image inputs from cameras or other sensors. The autonomy system assigns index values to the driving lanes and shoulder lanes, and then assigns the index values to the vehicles. The autonomy system generates data segments from the image data, corresponding to creating segments of an image, such that a single image is segmented for portions of the image, such as segmented outputs of each lane line or segmented outputs of portions of the vehicle. The autonomy system compares the segmented portions of the image to detect that a lane contains a vehicle.

Abstract: Embodiments herein include an automated vehicle performing for identifying vehicles and lanes in roadway by an autonomy system of an automated vehicle. The autonomy system gathers image inputs from cameras or other sensors. The autonomy system assigns index values to the driving lanes and shoulder lanes, and then assigns the index values to the vehicles. The autonomy system generates data segments from the image data, corresponding to creating segments of an image, such that a single image is segmented for portions of the image, such as segmented outputs of each lane line or segmented outputs of portions of the vehicle. The autonomy system compares the segmented portions of the image to detect that a lane contains a vehicle.

Abstract: Embodiments herein include an automated vehicle performing for identifying vehicles and lanes in roadway by an autonomy system of an automated vehicle. The autonomy system gathers image inputs from cameras or other sensors. The autonomy system assigns index values to the driving lanes and shoulder lanes, and then assigns the index values to the vehicles. The autonomy system generates data segments from the image data, corresponding to creating segments of an image, such that a single image is segmented for portions of the image, such as segmented outputs of each lane line or segmented outputs of portions of the vehicle. The autonomy system compares the segmented portions of the image to detect that a lane contains a vehicle.

Abstract: A vehicle comprises one or more sensors, and a processor coupled with the one or more sensors and stored inside a housing of the vehicle. The processor can be configured to collect data regarding the environment surrounding the vehicle from the one or more sensors; detect a second vehicle and an observed trajectory of the second vehicle from the collected data, the observed trajectory indicating a position or speed of the second vehicle over a time period; compare the observed trajectory with one or more expected trajectories of the second vehicle; responsive to determining a deviation between the observed trajectory and at least one of the one or more expected trajectories satisfies a condition, generate a record indicating the deviation and including a video of the second vehicle that corresponds to the observed trajectory; and transmit the record to a remote processor.

Abstract: Embodiments of the present invention relate to systems and methods for controlling the recording, storing and transmitting of video content captured by security cameras in order to drastically reduce the overall bandwidth required to remotely monitor a physical space. More specifically, embodiments of the present invention relate to a method of triggering or activating a video camera to record and/or transmit images of a physical environment over a network only when measurements taken by a separate structural sensor camera or depth-sensing device indicate that sufficient physical changes have occurred in the environment to warrant video recording.

Abstract: Embodiments of the present invention relate to systems and methods for controlling the recording, storing and transmitting of video content captured by security cameras in order to drastically reduce the overall bandwidth required to remotely monitor a physical space. More specifically, embodiments of the present invention relate to a method of triggering or activating a video camera to record and/or transmit images of a physical environment over a network only when measurements taken by a separate structural sensor camera or depth-sensing device indicate that sufficient physical changes have occurred in the environment to warrant video recording.