Abstract: Systems, methods, and non-transitory computer readable media configured to generate enhanced three-dimensional information. Three-dimensional information of a scene may be obtained. The three-dimensional information may define a three-dimensional point cloud model of the scene. The three-dimensional information may be determined based on distances of the scene from a location. Image information may be obtained. The image information may define one or more images of an object. The object may be identified based on the image information. A three-dimensional point cloud model of the object may be obtained. Enhanced three-dimensional information of the scene may be generated by inserting the three-dimensional point cloud model of the object into the three-dimensional point cloud model of the scene.

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 objects; determining a target movable object from the one or more detected objects; determining a manner of generating a directed alert notification selectively toward the target movable object; and causing a directed alert notification of the determined manner to be generated toward the target movable object.

Abstract: A system included and a computer-implemented method performed in an autonomous-driving vehicle are described. The system performs: detecting a wireless push signal transmitted from a signal transmitter accompanied by an off-vehicle passer and received by a signal receiver of the autonomous-driving vehicle, the wireless push signal including information about a motion capability level of the off-vehicle passer, determining a position and a motion capability level of the off-vehicle passer at least based on the wireless push signal, and controlling a locomotive mechanism of the autonomous-driving vehicle based on the determined position and motion capability level of the off-vehicle passer.

Abstract: Systems and methods directed to projecting a current trajectory path of the autonomous vehicle on a surface of road is disclosed. In some embodiments, an autonomous vehicle with a light projector is disclosed, where the light projector is on a top surface of an autonomous vehicle. Additionally, in some embodiments, the autonomous vehicle may include an electronic control unit for controlling an operation of the light projector, where the electronic control unit detects whether the autonomous vehicle is turned on. In further embodiments, the electronic control unit receives data of an environmental condition surrounding the autonomous vehicle and receives an upcoming trajectory path of the autonomous vehicle. The electronic control unit may also project a light from the light projector onto a surface of a road indicating the upcoming trajectory path of the autonomous vehicle.

Abstract: A system included and a computer-implemented method performed in an autonomous-driving vehicle are described. The system performs: detecting a wireless push signal transmitted from a signal transmitter accompanied by an off-vehicle passer and received by a signal receiver of the autonomous-driving vehicle, the wireless push signal including information about a motion capability level of the off-vehicle passer, determining a position and a motion capability level of the off-vehicle passer at least based on the wireless push signal, and controlling a locomotive mechanism of the autonomous-driving vehicle based on the determined position and motion capability level of the off-vehicle passer.

Abstract: Systems, methods, and non-transitory computer readable media may be configured to characterize optical characteristics of optical elements. An optical element mount may be configured to carry an optical element. A calibration display may be configured to display a calibration object. The calibration object may include a known visual pattern. Multiple images of the calibration object may be obtained. The multiple images may be acquired using the optical element carried by the optical element mount. The multiple images may include different perspectives of the calibration object. Optical characteristics of the optical element may be characterized based on the known visual pattern and the different perspectives of the calibration object.

Abstract: A set of sensor information may include first sensor information generated based on a first sensor of a first vehicle and second sensor information generated based on a second sensor of a second vehicle. Individual sensor information may characterize positions of objects in an environment of individual sensors. Relevant sensor information for a vehicle may be determined based on the set of sensor information and a position of the vehicle. The relevant sensor information may characterize positions of objects in a maneuver environment of the vehicle. A desired navigation of the vehicle in the maneuver environment of the vehicle may be determined based on the relevant sensor information. An instruction may be provided to the vehicle based on the desired navigation of the vehicle. The instruction may characterize one or more maneuvers to be performed by the vehicle to execute the desired navigation.

Abstract: A system included and a computer-implemented method performed in an autonomous-driving vehicle are described. The system performs: determining a region of interest (RoI) for processing images for an autonomous driving operation; determining an illumination condition for illuminating the determined RoI based on the determined RoI; and illuminating the determined RoI according to the determined illumination condition as the autonomous-driving vehicle travels.

Abstract: Systems, methods, and non-transitory computer readable media may be configured to facilitate prioritization of vehicle navigation. One or more vehicles in an environment of a priority vehicle may be identified. Priorities of the vehicle(s) and the priority vehicle may be determined. A desired navigation of the priority vehicle in the environment may be determined based on the priorities of the vehicle(s) and the priority vehicle. An instruction may be provided to at least one of the vehicle(s) based on the desired navigation of the priority vehicle in the environment. The instruction may characterize one or more maneuvers to be performed by the at least one of the vehicle(s) to facilitate the desired navigation of the priority vehicle.

Abstract: A set of sensor information may include first sensor information generated based on a first sensor of a first vehicle and second sensor information generated based on a second sensor of a second vehicle. Individual sensor information may characterize positions of objects in an environment of individual sensors. Relevant sensor information for a vehicle may be determined based on the set of sensor information and a position of the vehicle. The relevant sensor information may characterize positions of objects in a maneuver environment of the vehicle. A desired navigation of the vehicle in the maneuver environment of the vehicle may be determined based on the relevant sensor information. An instruction may be provided to the vehicle based on the desired navigation of the vehicle. The instruction may characterize one or more maneuvers to be performed by the vehicle to execute the desired navigation.

Abstract: A distributed database transaction processing method and device based on a GPS atomic clock, the method includes: receiving a plurality of transaction requests by the first node server; determining a concurrency conflict between transaction requests received by the first node server; obtaining start time of each transaction in a case that the concurrency conflict exists, wherein the start time is local time of the second node server when the transaction request is sent; and local time of the second node server is synchronized with time of the GPS atomic clock server in an area which the second node server locates; processing all transactions by the first node server according to the sequence of the start time of each transaction. Throughput of distributed database system can be increased and an arrangement complexity of servers is reduced.

Abstract: Enclosed are a method and apparatus for operating a database.

Abstract: A method comprises obtaining autonomous vehicle sensor data of an autonomous vehicle. One or more autonomous vehicle actions of the autonomous vehicle are predicted based on the autonomous vehicle sensor data. Interactive content is identified from a library of interactive content. The interactive content is adjusted based on the predicted one or more autonomous vehicle actions, and the adjusted interactive content is presented within the autonomous vehicle.

Abstract: A computer-implemented method and a system for training a computer-based autonomous driving model used for an autonomous driving operation by an autonomous vehicle are described. The method includes: creating time-dependent three-dimensional (3D) traffic environment data using at least one of real traffic element data and simulated traffic element data; creating simulated time-dependent 3D traffic environmental data by applying a time-dependent 3D generic adversarial network (GAN) model to the created time-dependent 3D traffic environment data; and training a computer-based autonomous driving model using the simulated time-dependent 3D traffic environmental data.

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 objects; determining a target movable object from the one or more detected objects; determining a manner of generating a directed alert notification selectively toward the target movable object; and causing a directed alert notification of the determined manner to be generated toward the target movable object.

Abstract: A system included and a computer-implemented method performed in one of a plurality of self-driving vehicles that are connected through a network are described. The system performs: processing image data of one or more scene images received by said one of the plurality of self-driving vehicles, to detect one or more objects included in the one or more scene images; determining a target object from the one or more detected objects at least based on the processed image data; predicting movement of the target object at least based on a current position and a current movement state of the target object; and performing a self-driving operation to drive said one of the plurality of self-driving vehicles based on the predicted movement of the target object.

Abstract: Systems, methods, and non-transitory computer readable media may be configured to characterize optical characteristics of optical elements. An optical element mount may be configured to carry an optical element. A calibration display may be configured to display a calibration object. The calibration object may include a known visual pattern. Multiple images of the calibration object may be obtained. The multiple images may be acquired using the optical element carried by the optical element mount. The multiple images may include different perspectives of the calibration object. Optical characteristics of the optical element may be characterized based on the known visual pattern and the different perspectives of the calibration object.

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: Systems, methods, and non-transitory computer-readable media are provided for acquiring driving records from an autonomous vehicle. One or more patterns can be determined from the driving records. One or more criteria can be generated based on the one or more patterns. One or more suspicious points can be identified in the driving records by applying the one or more criteria to the driving records.

Abstract: A system included and a computer-implemented method performed in one of a plurality of self-driving vehicles that are connected through a network are described. The system performs: processing image data of one or more scene images received by said one of the plurality of self-driving vehicles, to detect one or more objects included in the one or more scene images; determining a target object from the one or more detected objects at least based on the processed image data; predicting movement of the target object at least based on a current position and a current movement state of the target object; and performing a self-driving operation to drive said one of the plurality of self-driving vehicles based on the predicted movement of the target object.