METHODS AND SYSTEMS FOR MODEL BASED OPTIMAL LONGITUDINAL PATH PLANNER

    公开(公告)号:US20240425073A1

    公开(公告)日:2024-12-26

    申请号:US18339771

    申请日:2023-06-22

    Inventor: Justin YURKANIN

    Abstract: A method may include obtaining, from a kinematic vehicle model including a differential equation, by one or more processors associated with an autonomous vehicle, one or more candidate trajectories that satisfy one or more constraints relating to movement of the vehicle. The method may include iteratively updating, by the one or more processors, a score of each of the one or more candidate trajectories. The method may include determining, by the one or more processors among the one or more candidate trajectories, a target trajectory having a score that is greater than a threshold. The method may include executing, by the one or more processors, the target trajectory to cause the vehicle to move in the candidate trajectory.

    OBJECT TRACKING FOR AUTONOMOUS VEHICLES USING LONG-RANGE ACOUSTIC BEAMFORMING COMBINED WITH RGB VISUAL DATA

    公开(公告)号:US20240422502A1

    公开(公告)日:2024-12-19

    申请号:US18391537

    申请日:2023-12-20

    Abstract: An autonomous vehicle including a network of sensors including a plurality of acoustic sensors and a plurality of visual sensors, at least one processor, and at least one memory storing instructions is disclosed. The instructions, when executed by the at least one processor, cause the at least one processor to: (i) generate spatial beamforming maps locating a sound source based upon acoustic signals received at the plurality of acoustic sensors; (ii) identify a type of an object generating the acoustic signals received at the plurality of acoustic sensors based upon comparison of the acoustic signals with a plurality of acoustic signals and respective objects stored in a dataset; and (iii) generate feature maps for an application in an autonomous vehicle driving by enhancing visualization maps generated based upon visual signals received by the plurality of visual sensors.

    SYSTEMS AND METHODS FOR SUPPLYING ENERGY TO AN AUTONOMOUS VEHICLE VIA A VIRTUAL INTERFACE

    公开(公告)号:US20240416965A1

    公开(公告)日:2024-12-19

    申请号:US18335265

    申请日:2023-06-15

    Inventor: Joshua WISE

    Abstract: An autonomous vehicle can include a sensor and one or more processors. The processors can be configured to automatically control the autonomous vehicle to an energy supply station responsive to determining to resupply energy to the autonomous vehicle; detect, via the sensor, an object corresponding to the energy supply station, the object indicating to initiate energy supply to the autonomous vehicle; responsive to detecting the object, control the autonomous vehicle to stop at a defined position relative to the energy supply station; and open an energy input receptacle of the autonomous vehicle to receive energy from the energy supply station.

    FUTURE VISUAL FRAME PREDICTION FOR AUTONOMOUS VEHICLES USING LONG-RANGE ACOUSTIC BEAMFORMING AND SYNTHETIC APERTURE EXPANSION

    公开(公告)号:US20240416953A1

    公开(公告)日:2024-12-19

    申请号:US18391527

    申请日:2023-12-20

    Abstract: An autonomous vehicle including a microphone array of a plurality of microphones, a visual sensor network configured to receive visual signals, at least one processor, and at least one memory storing instructions is disclosed. The instructions, when executed by the at least one processor, cause the at least one processor to: (i) generate spatial beamforming maps locating a sound source using a beamforming model corresponding to acoustic signals received at the plurality of microphones of the microphone array; (ii) apply a synthetic aperture expansion to the acoustic signals to increase resolution of the spatial beamforming maps; and (iii) generate a future visual frame based at least partially upon temporal information extracted from the spatial beamforming maps and visualization maps generated based on the visual signals received by the visual sensor network.

    PRECISION MULTI-POINT SENSOR POSITION AND ATTITUDE CALIBRATION BRACKETS

    公开(公告)号:US20240353244A1

    公开(公告)日:2024-10-24

    申请号:US18138723

    申请日:2023-04-24

    CPC classification number: G01D18/00

    Abstract: Disclosed herein are systems, methods, and apparatuses for calibrating sensors of automated vehicles using calibration targets. A bracket holds the calibration targets and attaches to the automated vehicle proximate to a sensor being calibrated. For some sensors, such as GNSS antennas or similar device for receiving location data from a GNSS, a two-target bracket is fixed at the top of the automated vehicle, nearby the GNSS antenna. For IMUs or similar sensors, a three-target bracket is fixed at location of the automated vehicle proximate to the particular IMU, such as a passenger cabin or on the chassis of the automated vehicle. The calibration targets include a retroreflective surface that reflect signals, such as infrared signals, back to a theodolite (or total station). The theodolite or computer includes preprogrammed offset values indicating the relative positions of the sensor being calibrated and each of the calibration targets of the bracket.

    Methods and systems for reducing vehicle delays based on movement prediction

    公开(公告)号:US12017632B1

    公开(公告)日:2024-06-25

    申请号:US18235325

    申请日:2023-08-17

    Abstract: A method may include monitoring, by a processor associated with an autonomous vehicle, a status of a traffic light. The method may include monitoring, by the processor, a movement status of at least one vehicle within a same lane as the autonomous vehicle, the at least one vehicle having a stationary position in relation to the traffic light. The method may include executing, by the processor, a computer model to predict a change of movement status for the at least one vehicle in accordance with the status of the traffic light. The method may include in response to the computer model predicting a change of movement status for the at least one vehicle from the stationary position to a moving status, instructing, by the processor, the autonomous vehicle to increase a torque value of the autonomous vehicle at a predetermined time before the change of the movement status.

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