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.

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: Systems, methods, and non-transitory computer readable media configured to generate enhanced training information. Training information may be obtained. The training information may characterize behaviors of moving objects. The training information may be determined based on observations of the behaviors of the moving objects. Behavior information may be obtained. The behavior information may characterize a behavior of a given object. Enhanced training information may be generated by inserting the behavior information into the training information.

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: Systems and methods are provided for segmenting a data frame to be acquired into a number of incremental data of equal data length. A first incremental data of the data frame can be acquired from one or more sensors. The first incremental data of the data frame can be processed while a next incremental data of the data frame is being acquired from the one or more sensors. The acquiring and processing of incremental data of the data frame can continue until a last incremental data of the data frame is acquired and processed. Processed incremental data can be outputted as a processed data frame.

Abstract: An adaptive filter system and a method for controlling the adaptive filter system are described herein. The system can includes one or more filters to attenuate incoming light. The one or more filters can be moved by one or more actuators. The method can capture image data from an imaging device through the one or more filters. Information can be determined from the captured image data. The one or more filters can be moved to a position for capturing image data based on the information.

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: 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: Embodiments disclosed herein are directed to autonomous vehicles comprising at least one interior compartment including: at least one table; at least one seating unit; at least one closet; at least one window configured to transition between a substantially transparent state and a substantially opaque state and to display at least navigational information; at least one vanity; at least one storage area; or combinations thereof; wherein the vehicle is configured to operate in at least an autonomous mode. In some instance, the vehicle may not include steering equipment (e.g., steering wheel) and/or acceleration or deceleration equipment (e.g., a gas or brake pedal).

Abstract: Embodiments disclosed herein include systems and methods for engaging in an emergency autonomous driving mode for assisted-driving vehicles. The vehicle may include a non-emergency driving mode and an emergency autonomous driving mode, where the vehicle includes an electronic control unit for controlling an operation of the vehicle. The electronic control unit may determine a driving mode of the vehicle, receive a request to revert from the non-emergency driving mode to the emergency autonomous driving mode; and revert back to the non-emergency driving mode when select predetermined conditions are satisfied.

Abstract: Embodiments disclosed herein are directed to autonomous vehicles comprising at least one interior compartment including: at least one table; at least one seating unit; at least one closet; at least one window configured to transition between a substantially transparent state and a substantially opaque state and to display at least navigational information; at least one vanity; at least one storage area; or combinations thereof; wherein the vehicle is configured to operate in at least an autonomous mode. In some instance, the vehicle may not include steering equipment (e.g., steering wheel) and/or acceleration or deceleration equipment (e.g., a gas or brake pedal).

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: A lens mount apparatus mountable on a vehicle and a method for controlling a lens mount apparatus are described. The lens mount apparatus includes a plurality of lenses concentrically arranged around a center, and the plurality of lenses include a first lens having a first focal length and a second lens having a second focal length that is shorter than the first focal length. The method includes positioning one of the plurality of lenses, such that one of the lenses that has a focal length suitable for capturing an object is used for image capturing.

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.