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    Path planning with a preparation distance for a lane-change
    4.
    发明授权
    Path planning with a preparation distance for a lane-change 有权

    公开(公告)号：US11061403B2

    公开(公告)日：2021-07-13

    申请号：US16712035

    申请日：2019-12-12

    申请人： Baidu USA LLC

    发明人： Jiacheng Pan ,  Jiaxuan Xu ,  Jinyun Zhou ,  Hongyi Sun ,  Shu Jiang ,  Jiaming Tao ,  Yifei Jiang ,  Jiangtao Hu ,  Jinghao Miao

    IPC分类号： G08G1/16 ,  G05D1/00 ,  G05D1/02 ,  G06K9/00

    摘要： A driving environment is perceived based on sensor data obtained from a plurality of sensors mounted on the ADV. In response to a request for changing lane from a first lane to a second lane, path planning is performed. The path planning includes identifying a first lane change point for the ADV to change from the first lane to the second lane in a first trajectory of the ADV, determining a lane change preparation distance with respect to the first lane change point, and generating a second trajectory based on the lane change preparation distance, where the second trajectory having a second lane change point delayed from the first lane change point. Speed planning is performed on the second trajectory to control the ADV to change lane according to the second trajectory with different speeds at different point in time.

    BLIND AREA PROCESSING FOR AUTONOMOUS DRIVING VEHICLES
    5.
    发明申请
    BLIND AREA PROCESSING FOR AUTONOMOUS DRIVING VEHICLES 有权

    公开(公告)号：US20210027629A1

    公开(公告)日：2021-01-28

    申请号：US16522515

    申请日：2019-07-25

    申请人： Baidu USA LLC

    发明人： Jiaming Tao ,  Yifei Jiang ,  Yajia Zhang ,  Jiangtao Hu ,  Jiacheng Pan ,  Jinyun Zhou ,  Hongyi Sun

    IPC分类号： G08G1/16 ,  G05D1/00 ,  G05D1/02 ,  G08G1/01 ,  G08G1/052

    摘要： According to one embodiment, a driving environment surrounding an ADV is perceived based on sensor data obtained from various sensors mounted on the ADV including detecting one or more obstacles. The obstacles of the detected obstacles are determined and tracked based on the perception process, where the obstacle states of the obstacles may be maintained in an obstacle state buffer associated with the obstacles. When it is detected that a first moving obstacle is blocked by an object by the sensors, the further movement of the first moving obstacle is predicted based on the prior obstacle states of the first moving obstacle, while the first moving obstacle is blocked in view by the object. A trajectory is planned for the ADV in view of the predicted movement of the first moving obstacle while the first moving obstacle is in the blind area.

    Planning feedback based decision improvement system for autonomous driving vehicle
    6.
    发明授权
    Planning feedback based decision improvement system for autonomous driving vehicle 有权

    公开(公告)号：US10802484B2

    公开(公告)日：2020-10-13

    申请号：US15351128

    申请日：2016-11-14

    申请人： Baidu USA LLC

    发明人： Yifei Jiang ,  Jiangtao Hu ,  Jiaming Tao ,  Dong Li ,  Liyun Li ,  Guang Yang ,  Jingao Wang

    IPC分类号： G05D1/00 ,  B60W30/00

    摘要： In one embodiment, systems and methods are disclosed for a planning-driven framework for an driving vehicle (ADV) driving decision system. Driving decisions are classified into at least seven categories, including: conservative decision, aggressive decision, conservative parameters, aggressive parameters, early decision, late decision, and non-decision problem. Using the outputs of an ADV decision planning module, an ADV driving decision problem is identified, categorized, and diagnosed. A local driving decision improvement can be determined and executed in a short time frame on the ADV. For a long term solution, if needed, the driving decision problem can be uploaded to an analytics server. The driving decision problems from a large plurality of ADVs can be aggregated and analyzed for improving the ADV decisions system for all ADVs.

    SYSTEM AND METHOD FOR TRAINING A MACHINE LEARNING MODEL DEPLOYED ON A SIMULATION PLATFORM
    7.
    发明申请
    SYSTEM AND METHOD FOR TRAINING A MACHINE LEARNING MODEL DEPLOYED ON A SIMULATION PLATFORM 审中-公开

    公开(公告)号：US20190318267A1

    公开(公告)日：2019-10-17

    申请号：US15952089

    申请日：2018-04-12

    申请人： Baidu USA LLC

    发明人： Liangliang Zhang ,  Siyang Yu ,  Dong Li ,  Jiangtao Hu ,  Jiaming Tao ,  Yifei Jiang

    IPC分类号： G06N99/00 ,  G07C5/08 ,  G06F17/50

    摘要： System and method for training a machine learning model are disclosed. In one embodiment, for each of the driving scenarios, responsive to sensor data from one or more sensors of a vehicle and the driving scenario, driving statistics and environment data of the vehicle are collected while the vehicle is driven by a human driver in accordance with the driving scenario. Upon completion of the driving scenario, the driver is requested to select a label for the completed driving scenario and the selected label is stored responsive to the driver selection. Features are extracted from the driving statistics and the environment data based on predetermined criteria. The extracted features include some of the driving statistics and some of the environment data collected at the different points in time during the driving scenario.

    LEARNING BASED SPEED PLANNER FOR AUTONOMOUS DRIVING VEHICLES
    8.
    发明申请
    LEARNING BASED SPEED PLANNER FOR AUTONOMOUS DRIVING VEHICLES 审中-公开

    公开(公告)号：US20190317520A1

    公开(公告)日：2019-10-17

    申请号：US15954366

    申请日：2018-04-16

    申请人： Baidu USA LLC

    发明人： Liangliang Zhang ,  Dong Li ,  Jiangtao Hu ,  Jiaming Tao ,  Yifei Jiang

    IPC分类号： G05D1/02 ,  G05D1/00 ,  B60W50/00

    摘要： A learning based speed planner for autonomous driving vehicles (ADV) is disclosed. An ADV is set into human-driving mode. Driving control elements are under control of a human driver, and other ADV logic is enabled. The ADV plans a route path on a segment of the route having an obstacle. ADV logic generates a station-time graph for the path of the segment, and a grid of cells to encompass the path and obstacle. A feature vector is generated from the grid. Human driving behavior is recorded as the ADV is navigated along the path. Recorded driving data for a large plurality of paths, obstacles and ADVs is transmitted to a server to generate a speed model. The speed model is downloaded to one or more ADVs for use in autonomous driving mode, to determine an initial speed to use in similar driving situations.

    SENSOR AGGREGATION FRAMEWORK FOR AUTONOMOUS DRIVING VEHICLES
    9.
    发明申请
    SENSOR AGGREGATION FRAMEWORK FOR AUTONOMOUS DRIVING VEHICLES 审中-公开

    公开(公告)号：US20190317513A1

    公开(公告)日：2019-10-17

    申请号：US15952101

    申请日：2018-04-12

    申请人： Baidu USA LLC

    发明人： Liangliang Zhang ,  Dong Li ,  Jiangtao Hu ,  Jiaming Tao ,  Yifei Jiang

    IPC分类号： G05D1/02 ,  G06N99/00 ,  G05D1/00 ,  G01C21/34

    摘要： A sensor aggregation framework for autonomous driving vehicles is disclosed. In one embodiment, sensor data is collected from one or more sensors mounted on an autonomous driving vehicle (ADV) while the ADV is moving within a region of interest (ROI) that includes a number of obstacles. The sensor data includes obstacle information of the obstacles and vehicle data of the ADV. Each of the vehicle data is timestamped with a current time at which the vehicle data is captured to generate a number of timestamps that correspond to the vehicle data. The obstacle information, the vehicle data, and the corresponding timestamps are aggregated into training data. The training data is used to train a set of parameters that is subsequently utilized to predict at least in part future obstacle behaviors and vehicle movement of the ADV.

    Evaluation framework for decision making of autonomous driving vehicle
    10.
    发明授权
    Evaluation framework for decision making of autonomous driving vehicle 有权

    公开(公告)号：US10421460B2

    公开(公告)日：2019-09-24

    申请号：US15347659

    申请日：2016-11-09

    申请人： Baidu USA LLC

    发明人： Yifei Jiang ,  Dong Li ,  Jiaming Tao ,  Jiangtao Hu ,  Liyun Li ,  Guang Yang ,  Jingao Wang

    IPC分类号： B60W40/09 ,  G06N20/00 ,  G06F16/22 ,  G06F16/23 ,  B60W50/04 ,  G05D1/02 ,  G05D1/00 ,  B60W50/00

    摘要： In one embodiment, systems and methods are disclosed for evaluating autonomous driving vehicle (ADV) driving decisions. A driving scenario is selected, such as a route or destination or type of driving condition. ADV planning and control modules are turned off and do not control the ADV. As a user drives the ADV, sensors detect and periodically log a plurality of objects external to the ADV. Driving control inputs of the human driver are also logged periodically. An ADV driving decision module generates driving decisions with respect to each object detected by the sensors. The ADV driving decisions are logged, but are not used to control the ADV. An ADV driving decision is identified in the logs, and a corresponding human driving decision is extracted, graded, and compared to the ADV driving decision. The ADV driving decision can be graded using the logs and graded human driving decision.