Abstract: Described herein are apparatuses and methods for selectively controlling the application of a fluid to a sensor enclosure such as a camera housing to protect the housing from overheating. An apparatus that includes a protective shield and a conduit such as tubing for supplying a fluid is described. The protective shield is provided so as to protect an exterior surface of the camera housing from heat caused by sun exposure. The tubing includes an inlet for supplying a fluid such as water or air, can extend through or around an exterior of the camera housing, and includes an outlet with one or more nozzles for ejecting the fluid into a space between the protective shield and the camera housing. Sensor data is received from various vehicle sensors to assess the temperature of the housing, the velocity of the vehicle, and so forth to determine when the fluid should be supplied.

Abstract: Provided herein is a system and method implemented on a vehicle. The system comprises one or more sensors, one or more processors, and a memory storing instructions that, when executed by the one or more processors, causes the system to perform: obtaining data from the one or more sensors; comparing the obtained data from the one or more sensors with reference data; determining whether one or more characteristics of the obtained data deviate from corresponding characteristics of the reference data by more than a respective threshold; in response to determining that one or more characteristics of the data obtained deviate from corresponding characteristics of the reference data by more than a respective threshold, determining an action of the vehicle based on amounts of the one or more deviations; and performing the determined action.

Abstract: Systems, methods, and non-transitory computer-readable media are provided for implementing a tracking camera system onboard an autonomous vehicle. Coordinate data of an object can be received. The tracking camera system actuates, based on the coordinate data, to a position such that the object is in view of the tracking camera system. Vehicle operation data of the autonomous vehicle can be received. The position of the tracking camera system can be adjusted, based on the vehicle operation data, such that the object remains in view of the tracking camera system while the autonomous vehicle is in motion. A focus of the tracking camera system can be adjusted to bring the object in focus. The tracking camera system captures image data corresponding to the object.

Abstract: Described herein is a sensor device. The sensor device includes a housing with a front plate and a back plate. The front plate includes mounting holes and the back plate includes second mounting holes and alignment holes. The sensor device includes a printed circuit board encased by the housing, wherein the printed circuit board comprises an image sensor, an image sensor processor, and a serializer.

Abstract: Described herein are systems, methods, and non-transitory computer readable media for using 3D point cloud data such as that captured by a LiDAR as ground truth data for training an instance segmentation deep learning model. 3D point cloud data captured by a LiDAR can be projected on a 2D image captured by a camera and provided as input to a 2D instance segmentation model. 2D sparse instance segmentation masks may be generated from the 2D image with the projected 3D data points. These 2D sparse masks can be used to propagate loss during training of the model. Generation and use of the 2D image data with the projected 3D data points as well as the 2D sparse instance segmentation masks for training the instance segmentation model obviates the need to generate and use actual instance segmentation data for training, thereby providing an improved technique for training an instance segmentation model.

Abstract: A vehicle generates a city-scale map. The vehicle includes one or more Lidar sensors configured to obtain point clouds at different positions, orientations, and times, one or more processors, and a memory storing instructions that, when executed by the one or more processors, cause the system to perform registering, in pairs, a subset of the point clouds based on respective surface normals of each of the point clouds; determining loop closures based on the registered subset of point clouds; determining a position and an orientation of each of the subset of the point clouds based on constraints associated with the determined loop closures; and generating a map based on the determined position and the orientation of each of the subset of the point clouds.

Abstract: Provided herein is a system and method of a vehicle that determines an action of a vehicle. The system comprises one or more sensors; one or more processors; and a memory storing instructions that, when executed by the one or more processors, causes the system to perform determining a location of one or more other vehicles relative to the vehicle; determining an action of the vehicle based on the determined location of one or more other vehicles; sending a signal to the one or more other vehicles indicating the determined action; and performing the determined action of the vehicle.

Abstract: Provided herein is a system and method for heat exchange of a vehicle. The system comprises an enclosure disposed on the vehicle. The enclosure comprises a vent at a base of the enclosure. The enclosure houses one or more sensors. The enclosure comprises a fan disposed at a base of the enclosure. The heat exchange system comprises an deflector disposed on the vehicle outside the enclosure and configured to direct an airflow into the vent of the enclosure. The heat exchange system comprises a motor configured to: generate electricity from the airflow and selectively supply electricity to operate the fan. The heat exchange system comprises a controller configured to adjust the deflector and regulate an amount of electricity supplied from the motor to the fan.

Abstract: A system included and a computer-implemented method performed in an autonomous-driving vehicle are described. The system performs: detecting one or more movable traffic objects; determining one or more target movable traffic objects from the one or more detected movable traffic objects; determining a type of the one or more target movable traffic objects and an traffic object that has a right of way (ROW) in a situation involving the autonomous-driving vehicle. The system further performs: determining a manner of generating a vehicle behavior notification to the target movable traffic object based on the type of the one or more target movable traffic objects and the ROW; and causing a vehicle behavior notification of the determined manner to be generated to the one or more target movable traffic objects.

Abstract: Provided herein is a system and method for cooling a sensor enclosure of a vehicle. The system comprises one or more sensors configured to determine a speed of the vehicle, an internal temperature of an enclosure, and an external temperature. The system comprises an enclosure to house the one or more sensors. The system comprises a fan disposed at a base of the enclosure. The system comprises a controller configured to regulate a rotation speed of the fan based on the speed of the vehicle, the internal temperature of the enclosure, the external temperature, or the difference between the internal temperature of the enclosure and the external temperature. The controller operates the fan at the regulated rotation speed.

Abstract: A system included and a computer-implemented method performed in an autonomous-driving vehicle are described. The system performs: receive a request to meet a person at a location; drive the vehicle to the location; identify the person at the location; and providing an instruction for the person to interact with the vehicle.

Abstract: Described herein are systems, methods, and computer readable media for performing data conversion on sensor data to obtain modified sensor data that is formatted/structured appropriately for downstream processes that rely on the sensor data as input. The sensor data can include point cloud data captured by a LiDAR, for example. A grid structure and corresponding grid characteristics can be determined and the sensor data can be converted to grid-based sensor data by associating the grid structure and its characteristics with the sensor data. Generating the grid-based sensor data can include reformatting the point cloud data to superimpose the grid structure and its grid characteristics onto the point cloud data. Various downstream processing that cannot feasibly be performed on the raw sensor data can then be performed efficiently on the modified grid-based sensor data by virtue of the grid structure imbuing the sensor data with spatial proximity information.

Abstract: A sensor enclosure comprising a domed cover and a base. The base can be encased by the domed cover. The base comprises an inner frame, an outer frame, one or more wipers, and a powertrain. The inner frame can provide surfaces for one or more sensors. The outer frame, disposed underneath the inner frame, the outer frame includes a slewing ring. The slewing ring comprises an inner ring to which the domed cover is attached and an outer ring attached to the outer frame. The one or more wipers extends vertically from the outer frame, each wiper having a first end attached to the outer frame and a second end attached to a support ring, and each wiper making a contact with the dome cover. The powertrain, disposed within the outer frame, configured to rotate the ring and the dome cover attached to the inner ring.

Abstract: Described herein are systems, methods, and non-transitory computer readable media for memory address encoding of multi-dimensional data in a manner that optimizes the storage and access of such data in linear data storage. The multi-dimensional data may be spatial-temporal data that includes two or more spatial dimensions and a time dimension. An improved memory architecture is provided that includes an address encoder that takes a multi-dimensional coordinate as input and produces a linear physical memory address. The address encoder encodes the multi-dimensional data such that two multi-dimensional coordinates close to one another in multi-dimensional space are likely to be stored in close proximity to one another in linear data storage. In this manner, the number of main memory accesses, and thus, overall memory access latency is reduced, particularly in connection with real-world applications in which the respective probabilities of moving along any given dimension are very close.

Abstract: Described herein is a memory architecture that is configured to dynamically determine an address encoding to use to encode multi-dimensional data such as multi-coordinate data in a manner that provides a coordinate bias corresponding to a current memory access pattern. The address encoding may be dynamically generated in response to receiving a memory access request or may be selected from a set of preconfigured address encodings. The dynamically generated or selected address encoding may apply an interleaving technique to bit representations of coordinate values to obtain an encoded memory address. The interleaving technique may interleave a greater number of bits from the bit representation corresponding to the coordinate direction in which a coordinate bias is desired than from bit representations corresponding to other coordinate directions.

Abstract: Systems and methods are directed to obtaining autonomous vehicle sensor data of an autonomous vehicle. In these system and methods that include determining a direction of motion of a vehicle based on a predicted navigational position of the vehicle, determining, based at least in part on the predicted navigational position, a change in a future light positional information that may be received by one or more sensors compared to a current light positional information being received by the one or more sensors and cleaning the one or more sensors of the vehicle prior to the change in the future light positional information and prior to the vehicle reaching the predicted navigational position.

Abstract: Systems, methods, and non-transitory computer-readable media are provided for implementing a preemptive suspension control for an autonomous vehicle to improve ride quality. Data from one or more sensors onboard the autonomous vehicle can be acquired. A surface imperfection of a road can be identified from the data. A next action for the autonomous vehicle can be determined based on the road condition. A signal can be outputted that causes the autonomous vehicle to act in accordance with the next action after adjusting the suspension preemptively.

Abstract: A computer implemented method for operating a wiper system of a sensor enclosure. The wiper system can be configured to receive a camera operating information from one or more cameras. The one or more cameras can be determined to be in an exposure mode based on the camera operating information. A first speed of one or more wipers can be adjusted such that the one or more wipers are not in field of views of the one or more cameras while the one or more cameras are in the exposure mode.

Abstract: Provided herein is a system and method for regulating a sensor enclosure of a vehicle. The system comprises an enclosure comprising a vent at a base of the enclosure, one or more sensors configured to determine a parameter of the vehicle or the enclosure, a fan configured to regulate an internal temperature of the enclosure, and a controller configured to regulate a rotation speed of the fan based on the parameter of the vehicle or the enclosure. The regulating system further comprises a deflector connected to the enclosure and configured to direct an airflow into the vent based on the parameter.

Abstract: Described herein are systems, methods, and non-transitory computer readable media for assessing an awareness level of a vehicle occupant such as a vehicle operator and taking one or more measures to raise the awareness level of the vehicle occupant if deemed necessary. In particular, if the awareness level of the vehicle occupant falls below a minimum threshold level of awareness for safe vehicle operation, one or more response measures may be taken to raise the awareness level above the threshold level. The awareness level of the vehicle occupant can be quantitatively determined based on a physiological and/or behavioral response of the vehicle occupant to an applied stimulus such as one or more light pulses, an audible sound, or the like.