Patents by Inventor Jinyun Zhou

Jinyun Zhou has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11511760
    Abstract: Systems and methods are disclosed for collecting driving data from simulated autonomous driving vehicle (ADV) driving sessions and real-world ADV driving sessions. The driving data is processed to exclude manual (human) driving data and to exclude data corresponding to the ADV being stationary (not driving). Data can further be filtered based on driving direction: forward or reverse driving. Driving data records are time stamped. The driving data can be aligned according to the timestamp, then a standardized set of metrics is generated from the collected, filtered, and time-aligned data. The standardized set of metrics are used to grade the performance the control system of the ADV, and to generate an updated ADV controller, based on the standardized set of metrics.
    Type: Grant
    Filed: January 23, 2020
    Date of Patent: November 29, 2022
    Assignees: BAIDU USA LLC, BAIDU.COM TIMES TECHNOLOGY (BEIJING) CO., LTD.
    Inventors: Yu Wang, Qi Luo, Yu Cao, Zongbao Feng, Longtao Lin, Xiangquan Xiao, Jinghao Miao, Jiangtao Hu, Jingao Wang, Shu Jiang, Jinyun Zhou, Jiaxuan Xu
  • Patent number: 11493926
    Abstract: In one embodiment, a system generates a plurality of driving scenarios to train a reinforcement learning (RL) agent and replays each of the driving scenarios to train the RL agent by: applying a RL algorithm to an initial state of a driving scenario to determine a number of control actions from a number of discretized control/action options for the ADV to advance to a number of trajectory states which are based on a number of discretized trajectory state options, determining a reward prediction by the RL algorithm for each of the controls/actions, determining a judgment score for the trajectory states, and updating the RL agent based on the judgment score.
    Type: Grant
    Filed: May 15, 2019
    Date of Patent: November 8, 2022
    Assignee: BAIDU USA LLC
    Inventors: Runxin He, Jinyun Zhou, Qi Luo, Shiyu Song, Jinghao Miao, Jiangtao Hu, Yu Wang, Jiaxuan Xu, Shu Jiang
  • Patent number: 11492008
    Abstract: Systems and methods are disclosed for reducing second order dynamics delays in a control subsystem (e.g. throttle, braking, or steering) in an autonomous driving vehicle (ADV). A control input is received from an ADV perception and planning system. The control input is translated in a control command to a control subsystem of the ADV. A reference actuation output is obtained from a storage of the ADV. The reference actuation output is a smoothed output that accounts for second order actuation dynamic delays attributable to the control subsystem actuator. Based on a difference between the control input and the reference actuation output, adaptive gains are determined and applied to the input control signal to reduce error between the control output and the reference actuation output.
    Type: Grant
    Filed: February 21, 2020
    Date of Patent: November 8, 2022
    Assignee: BAIDU USA LLC
    Inventors: Yu Wang, Qi Luo, Shu Jiang, Jinghao Miao, Jiangtao Hu, Jingao Wang, Jinyun Zhou, Jiaxuan Xu
  • Patent number: 11485353
    Abstract: In one embodiment, a computer-implemented method of autonomously parking an autonomous driving vehicle, includes generating environment descriptor data describing a driving environment surrounding the autonomous driving vehicle (ADV), including identifying a parking space and one or more obstacles within a predetermined proximity of the ADV, generating a parking trajectory of the ADV based on the environment descriptor data to autonomously park the ADV into the parking space, including optimizing the parking trajectory in view of the one or more obstacles, segmenting the parking trajectory into one or more trajectory segments based on a vehicle state of the ADV, and controlling the ADV according to the one or more trajectory segments of the parking trajectory to autonomously park the ADV into the parking space without collision with the one or more obstacles.
    Type: Grant
    Filed: April 30, 2019
    Date of Patent: November 1, 2022
    Assignee: BAIDU USA LLC
    Inventors: Jinyun Zhou, Runxin He, Qi Luo, Jinghao Miao, Jiangtao Hu, Yu Wang, Jiaxuan Xu, Shu Jiang
  • Patent number: 11467591
    Abstract: In one embodiment, a system uses an actor-critic reinforcement learning model to generate a trajectory for an autonomous driving vehicle (ADV) in an open space. The system perceives an environment surrounding an ADV. The system applies a RL algorithm to an initial state of a planning trajectory based on the perceived environment to determine a plurality of controls for the ADV to advance to a plurality of trajectory states based on map and vehicle control information for the ADV. The system determines a reward prediction by the RL algorithm for each of the plurality of controls in view of a target destination state. The system generates a first trajectory from the trajectory states by maximizing the reward predictions to control the ADV autonomously according to the first trajectory.
    Type: Grant
    Filed: May 15, 2019
    Date of Patent: October 11, 2022
    Assignee: BAIDU USA LLC
    Inventors: Runxin He, Jinyun Zhou, Qi Luo, Shiyu Song, Jinghao Miao, Jiangtao Hu, Yu Wang, Jiaxuan Xu, Shu Jiang
  • Publication number: 20220315046
    Abstract: In one embodiment, simulation of an autonomous driving vehicle (ADV) includes capturing first data that includes a control command output by an autonomous vehicle controller of the ADV, and capturing second data that includes the control command being implemented at a control unit of the ADV. The control command, for example, a steering command, a braking command, or a throttle command, is implemented by the ADV to affect movement of the ADV. A latency model is determined based on comparing the first data with the second data, where the latency model defines time delay and/or amplitude difference between the first data and the second data. The latency model is applied in a virtual driving environment.
    Type: Application
    Filed: December 20, 2019
    Publication date: October 6, 2022
    Inventors: Shu JIANG, Qi LUO, Jinghao MIAO, Jiangtao HU, Yu WANG, Jiaxuan XU, Jinyun ZHOU, Kuang HU, Chao MA
  • Patent number: 11462060
    Abstract: An autonomous driving vehicle (ADV) receives instructions for a human test driver to drive the ADV in manual mode and to collect a specified amount of driving data for one or more specified driving categories. As the user drivers the ADV in manual mode, driving data corresponding to the one or more driving categories is logged. A user interface of the ADV displays the one or more driving categories that the human driver is instructed collect data upon, and a progress indicator for each of these categories as the human driving progresses. The driving data is uploaded to a server for machine learning. If the server machine learning achieves a threshold grading amount of the uploaded data to variables of a dynamic self-driving model, then the server generates an ADV self-driving model, and distributes the model to one or more ADVs that are navigated in the self-driving mode.
    Type: Grant
    Filed: April 29, 2019
    Date of Patent: October 4, 2022
    Assignee: BAIDU USA LLC
    Inventors: Shu Jiang, Qi Luo, Jinghao Miao, Jiangtao Hu, Weiman Lin, Jiaxuan Xu, Yu Wang, Jinyun Zhou, Runxin He
  • Patent number: 11453409
    Abstract: Systems and methods are disclosed for reducing second order dynamics delays in a control subsystem (e.g. throttle, braking, or steering) in an autonomous driving vehicle (ADV) and increasing control system bandwidth by accounting for time-latency in a control subsystem actuation system. A control input is received from an ADV's autonomous driving system. The control input is translated into a control command of the control subsystem of the ADV. A reference actuation output and a predicted actuation output are generated corresponding to a by-wire (“real”) actuation action for the control subsystem. A control error is determined between the reference actuation action and the by-wire actuation action. A predicted control error is determined between the predicted actuation action and the between the by-wire actuation action. Adaptive gains are determined and applied to the by-wire actuation action to generate a second by-wire actuation action.
    Type: Grant
    Filed: April 21, 2020
    Date of Patent: September 27, 2022
    Assignee: BAIDU USA LLC
    Inventors: Yu Wang, Qi Luo, Shu Jiang, Jinghao Miao, Jiangtao Hu, Jingao Wang, Jinyun Zhou, Jiaxuan Xu
  • Publication number: 20220284320
    Abstract: Techniques for using machine-learned models to throttle content are provided. In one technique, based on multiple selection events, a distribution of relevance measures is computed, where the relevance measures are associated with the content item selection events. The relevance measures may be generated by one or more machine-learned models. Based on the computed distribution, a threshold relevance measure is computed. Thereafter, a request for content is received over a computer network. In response, a computer system performs, in real-time, multiple steps. For example, an identity of an entity that is associated with the request is identified and, based on that identity, multiple content delivery groups are identified. A relevance measure of one of the content delivery groups relative to the entity is determined and compared to the threshold relevance measure. The content delivery group is selected only after determining that the relevance measure is above the threshold relevance measure.
    Type: Application
    Filed: March 3, 2021
    Publication date: September 8, 2022
    Inventors: Jinyun YAN, Shaunak CHATTERJEE, Runfang ZHOU
  • Patent number: 11409284
    Abstract: In one embodiment, an open space model is generated for a system to plan trajectories for an ADV in an open space. The system perceives an environment surrounding an ADV including one or more obstacles. The system determines a target function for the open space model based on constraints for the one or more obstacles and map information. The system iteratively, performs a first quadratic programming (QP) optimization on the target function based on a first trajectory while fixing a first set of variables, and performs a second QP optimization on the target function based on a result of the first QP optimization while fixing a second set of variables. The system generates a second trajectory based on results of the first and the second QP optimizations to control the ADV autonomously according to the second trajectory.
    Type: Grant
    Filed: May 15, 2019
    Date of Patent: August 9, 2022
    Assignee: BAIDU USA LLC
    Inventors: Runxin He, Jinyun Zhou, Qi Luo, Shiyu Song, Jinghao Miao, Jiangtao Hu, Yu Wang, Jiaxuan Xu, Shu Jiang
  • Patent number: 11377112
    Abstract: Generating control effort to control an autonomous driving vehicle (ADV) includes determining a direction (forward or reverse) in which the ADV is driving and selecting a driving model and a predictive model based upon the direction. In a forward direction, the driving model is a dynamic model, such as a “bicycle model,” and the predictive model is a look-ahead model. In a reverse direction, the driving model is a hybrid dynamic and kinematic model and the predictive model is a look-back model. Current and predicted lateral error and heading error are determined using the driving model and predictive model, respectively. A linear quadratic regulator (LQR) uses the current and predicted lateral error and heading errors to determine a first control effort An augmented control logic determines a second, additional, control effort, to determine a final control effort that is output to a control module to drive the ADV.
    Type: Grant
    Filed: November 13, 2019
    Date of Patent: July 5, 2022
    Assignee: BAIDU USA LLC
    Inventors: Yu Wang, Qi Luo, Shu Jiang, Jinghao Miao, Jiangtao Hu, Jingao Wang, Jinyun Zhou, Runxin He, Jiaxuan Xu
  • Patent number: 11352010
    Abstract: In one embodiment, an autonomous driving system of an autonomous driving vehicle perceives a driving environment surrounding the autonomous driving vehicle traveling along a path, including perceiving an obstacle in the driving environment. The system detects a vertical acceleration of the autonomous driving vehicle based on sensor data obtained from a sensor on the autonomous driving vehicle. The system further calibrates the perceived obstacle based on the vertical acceleration of the autonomous driving vehicle. The system then controls the autonomous driving vehicle to navigate through the driving environment in view of the calibrated perceived obstacle.
    Type: Grant
    Filed: September 30, 2019
    Date of Patent: June 7, 2022
    Assignee: BAIDU USA LLC
    Inventors: Shu Jiang, Qi Luo, Jinghao Miao, Jiangtao Hu, Jiaxuan Xu, Jingao Wang, Yu Wang, Jinyun Zhou, Runxin He
  • Patent number: 11338819
    Abstract: In one embodiment, a computer-implemented method for calibrating autonomous driving vehicles at a cloud-based server includes receiving, at the cloud-based server, one or more vehicle calibration requests from at least one user, each vehicle calibration request including calibration data for one or more vehicles and processing in parallel, by the cloud-based server, the one or more vehicle calibration requests for the at least one user to generate a calibration result for each vehicle. The method further includes sending, by the cloud-based server, the calibration result for each vehicle to the at least one user.
    Type: Grant
    Filed: September 30, 2019
    Date of Patent: May 24, 2022
    Assignee: BAIDU USA LLC
    Inventors: Shu Jiang, Qi Luo, Jinghao Miao, Jiangtao Hu, Xiangquan Xiao, Jiaxuan Xu, Yu Wang, Jinyun Zhou, Runxin He
  • Patent number: 11300955
    Abstract: In one embodiment, a set of predetermined driving parameters is determined from a set of driving statistics data collected from a number of vehicles, which may be driven by human drivers. For each pair of the predetermined driving parameters, a distribution of the pair of driving parameters is plotted based on their relationship on a two-dimensional (2D) distribution space. The 2D distribution space is partitioned into a number of grid cells, each grid cell representing a particular pair of driving parameters. For each of the grid cells, a probability is calculated that the pair of driving parameter likely falls in the grid cell. A grid table is generated corresponding to the pair of driving parameters. The grid table can be utilized during the autonomous driving at real-time or during simulation to determine a ride stability of an autonomous driving vehicle (ADV) in view of the pair of driving parameters.
    Type: Grant
    Filed: December 12, 2019
    Date of Patent: April 12, 2022
    Assignee: BAIDU USA LLC
    Inventors: Yifei Jiang, Jinyun Zhou, Jiacheng Pan, Jiaxuan Xu, Hongyi Sun, Jiaming Tao, Shu Jiang, Jinghao Miao, Jiangtao Hu
  • Publication number: 20220081000
    Abstract: In one embodiment, a system/method generates a driving trajectory for an autonomous driving vehicle (ADV). The system perceives an environment of an autonomous driving vehicle (ADV). The system determines one or more bounding conditions based on the perceived environment. The system generates a first trajectory using a neural network model, wherein the neural network model is trained to generate a driving trajectory. The system evaluates/determines if the first trajectory satisfies the one or more bounding conditions. If the first trajectory satisfies the one or more bounding conditions, the system controls the ADV autonomously according to the first trajectory. Otherwise, the system controls the ADV autonomously according to a second trajectory, where the second trajectory is generated based on an objective function, where the objective function is determined based on at least the one or more bounding conditions.
    Type: Application
    Filed: September 15, 2020
    Publication date: March 17, 2022
    Inventors: YIFEI JIANG, JINYUN ZHOU, JIAMING TAO, SHU JIANG, JIANGTAO HU, JINGHAO MIAO, SHIYU SONG
  • Patent number: 11269329
    Abstract: In one embodiment, a set of parameters representing a first state of an autonomous driving vehicle (ADV) to be simulated and a set of control commands to be issued at a first point in time. In response, a localization predictive model is applied to the set of parameters to determine a first position (e.g., x, y) of the ADV. A localization correction model is applied to the set of parameters to determine a set of localization correction factors (e.g., ?x, ?y). The correction factors may represent the errors between the predicted position of the ADV by the localization predictive model and the ground truth measured by sensors of the vehicle. Based on the first position of the ADV and the correction factors, a second position of the ADV is determined as the simulated position of the ADV.
    Type: Grant
    Filed: October 21, 2019
    Date of Patent: March 8, 2022
    Assignee: BAIDU USA LLC
    Inventors: Shu Jiang, Qi Luo, Jinghao Miao, Jiangtao Hu, Jiaxuan Xu, Jingao Wang, Yu Wang, Jinyun Zhou, Runxin He
  • Publication number: 20220054322
    Abstract: Disclosed is a pair of medical compression stocking, each comprising a body, an auxiliary pressure part and a present sensing part. The body is formed by means of knitting knitted yarns and inlay yarns. The auxiliary pressure part is integrated with the body, is located at an ankle of a lower limb of each medical compression stocking, and can be in contact with an ankle of a wearer. The pressure sensing part comprises a conducting part and a signal receiving part, wherein the conducting part is integrated with the body and is used for sensing pressure at a corresponding part of the medical compression stocking; and the signal receiving part can receive a signal from the conducting part, and same determines the value of the pressure from the corresponding part according to the signal.
    Type: Application
    Filed: February 25, 2019
    Publication date: February 24, 2022
    Applicant: The Hong Kong Research Institute of Textiles and Apparel Limited
    Inventors: Xiaoming Tao, Ying Xiong, Jinyun Zhou, Shirui Liu, Chad Cheuk-Wa Tse, Xiuyuan Hu
  • Patent number: 11180165
    Abstract: In one embodiment, an autonomous driving vehicle (ADV) operates in an on-lane mode, where the ADV follows a path along a vehicle lane. In response to determining that the ADV is approaching a dead-end, the ADV switches to an open-space mode. While in the open-space mode, the ADV conducts a three-point turn using a series of steering and throttle commands to generate forward and reverse movements until the ADV is within a) a threshold heading, and b) a threshold distance, relative to the vehicle lane. The ADV can then return to the on-lane mode and resume along the vehicle lane away from the dead-end.
    Type: Grant
    Filed: December 26, 2019
    Date of Patent: November 23, 2021
    Assignee: BAIDU USA LLC
    Inventors: Jinyun Zhou, Shu Jiang, Jiaming Tao, Qi Luo, Jinghao Miao, Jiangtao Hu, Jiaxuan Xu, Yu Wang
  • Patent number: 11183059
    Abstract: According to one embodiment, in response to a request to park an ADV into a parking lot, a remote server is accessed over a network (e.g., a VX2 link) to obtain a list of parking spaces that appear to be available in the parking lot. Based on the list of available parking spaces and the map associated with the parking lot, a route is generated to navigate through at least the available parking spaces. The ADV is driven according to the route to locate at least one of the available parking spaces and to park the ADV into the located available parking space. The centralized server is configured to periodically receive signals from a number of parking lots indicating which of the parking spaces of the parking lots are apparently available.
    Type: Grant
    Filed: April 22, 2019
    Date of Patent: November 23, 2021
    Assignee: BAIDU USA LLC
    Inventors: Jinyun Zhou, Runxin He, Qi Luo, Jinghao Miao, Jiangtao Hu, Yu Wang, Jiaxuan Xu, Shu Jiang
  • Patent number: 11167770
    Abstract: Systems and methods are disclosed for identifying time-latency and subsystem control actuation dynamic delay due to second order dynamics that are neglected in control systems of the prior art. Embodiments identify time-latency and subsystem control actuation delays by developing a discrete-time dynamic model having parameters and estimating the parameters using a least-squares method over selected crowd-driving data. After estimating the model parameters, the model can be used to identify dynamic actuation delay metrics such as time-latency, rise time, settling time, overshoot, bandwidth, and resonant peak of the control subsystem. Control subsystems can include steering, braking, and throttling.
    Type: Grant
    Filed: February 13, 2020
    Date of Patent: November 9, 2021
    Assignee: BAIDU USA LLC
    Inventors: Yu Wang, Qi Luo, Shu Jiang, Jinghao Miao, Jiangtao Hu, Jingao Wang, Jinyun Zhou, Jiaxuan Xu