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公开(公告)号:US11577758B2
公开(公告)日:2023-02-14
申请号:US16734146
申请日:2020-01-03
申请人: Baidu USA LLC
发明人: Shu Jiang , Jiaming Tao , Jinyun Zhou , Qi Luo , Jinghao Miao , Jiangtao Hu , Jiaxuan Xu , Yu Wang
摘要: In one embodiment, when an autonomous driving vehicle (ADV) is parked, the ADV can determine, based on criteria, whether to operate in an open-space mode or an on-lane mode. The criteria can include whether the ADV is within a threshold distance and threshold heading relative to a vehicle lane. If the criteria are not satisfied, then the ADV can enter the open-space mode. While in the open-space mode, the ADV can maneuver it is within the threshold distance and the threshold heading relative to the vehicle lane. In response to the criteria being satisfied, the ADV can enter and operate in the on-lane mode for the ADV to resume along the vehicle lane.
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公开(公告)号:US11518404B2
公开(公告)日:2022-12-06
申请号:US16826707
申请日:2020-03-23
申请人: Baidu USA LLC
发明人: Yu Wang , Qi Luo , Jinyun Zhou , Shu Jiang , Jiaxuan Xu , Jinghao Miao , Jiangtao Hu
摘要: In one embodiment, static-state curvature error compensation control logic for autonomous driving vehicles (ADV) receives planning and control data associated with the ADV, including a planned steering angle and a planned speed. A steering command is generated based on a current steering angle and the planned steering angle of the ADV. A throttle command is generated based on the planned speed in view of a current speed of the ADV. A curvature error is calculated based on a difference between the current steering angle and the planned steering angle. The steering command is issued to the ADV while withholding the throttle command, in response to determining that the curvature error is greater than a predetermined curvature threshold, such that the steering angle of the ADV is adjusted in view of the planned steering angle without acceleration.
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公开(公告)号:US11492008B2
公开(公告)日:2022-11-08
申请号:US16797833
申请日:2020-02-21
申请人: Baidu USA LLC
发明人: Yu Wang , Qi Luo , Shu Jiang , Jinghao Miao , Jiangtao Hu , Jingao Wang , Jinyun Zhou , Jiaxuan Xu
摘要: 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.
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公开(公告)号:US11485353B2
公开(公告)日:2022-11-01
申请号:US16399579
申请日:2019-04-30
申请人: Baidu USA LLC
发明人: Jinyun Zhou , Runxin He , Qi Luo , Jinghao Miao , Jiangtao Hu , Yu Wang , Jiaxuan Xu , Shu Jiang
摘要: 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.
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25.
公开(公告)号:US11467591B2
公开(公告)日:2022-10-11
申请号:US16413332
申请日:2019-05-15
申请人: Baidu USA LLC
发明人: Runxin He , Jinyun Zhou , Qi Luo , Shiyu Song , Jinghao Miao , Jiangtao Hu , Yu Wang , Jiaxuan Xu , Shu Jiang
摘要: 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.
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公开(公告)号:US11462060B2
公开(公告)日:2022-10-04
申请号:US16397633
申请日:2019-04-29
申请人: Baidu USA LLC
发明人: Shu Jiang , Qi Luo , Jinghao Miao , Jiangtao Hu , Weiman Lin , Jiaxuan Xu , Yu Wang , Jinyun Zhou , Runxin He
IPC分类号: G07C5/08 , G06N20/00 , G05D1/00 , G06F3/0483 , G06F3/0482
摘要: 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.
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公开(公告)号:US20210291855A1
公开(公告)日:2021-09-23
申请号:US16826707
申请日:2020-03-23
申请人: Baidu USA LLC
发明人: Yu Wang , Qi Luo , Jinyun Zhou , Shu Jiang , Jiaxuan Xu , Jinghao Miao , Jiangtao Hu
摘要: In one embodiment, static-state curvature error compensation control logic for autonomous driving vehicles (ADV) receives planning and control data associated with the ADV, including a planned steering angle and a planned speed. A steering command is generated based on a current steering angle and the planned steering angle of the ADV. A throttle command is generated based on the planned speed in view of a current speed of the ADV. A curvature error is calculated based on a difference between the current steering angle and the planned steering angle. The steering command is issued to the ADV while withholding the throttle command, in response to determining that the curvature error is greater than a predetermined curvature threshold, such that the steering angle of the ADV is adjusted in view of the planned steering angle without acceleration.
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公开(公告)号:US20230406345A1
公开(公告)日:2023-12-21
申请号:US17843546
申请日:2022-06-17
申请人: Baidu USA LLC
发明人: Szu-Hao Wu , Shu Jiang , Yu Cao , Weiman Lin , Ang Li , Jiangtao Hu
CPC分类号: B60W60/001 , B60W50/00 , B60W30/18163 , B60W2520/10 , B60W2050/0028 , B60W2555/60 , B60W2520/105
摘要: The present disclosure provides methods and techniques for evaluating and improving algorithms for autonomous driving planning and control (PNC), using one or more metrics (e.g., similarity scores) computed based on expert demonstrations. For example, the one or more metrics allow for improving PNC based on human, as opposed to or in addition to optimizing certain oversimplified properties, such as the least distance or time, as an objective. When driving in certain scenarios, such as taking a turn, people may drive in a distributed probability pattern instead of in a uniform line (e.g., different speeds and different curvatures at the same corner). As such, there can be more than one “correct” control trajectory for an autonomous vehicle to perform in the same turn. Safety, comfort, speeds, and other criteria may lead to different preferences and judgment as to how well the controlled trajectory has been computed.
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29.
公开(公告)号:US11815891B2
公开(公告)日:2023-11-14
申请号:US16659963
申请日:2019-10-22
申请人: Baidu USA LLC
发明人: Runxin He , Yu Wang , Jinyun Zhou , Qi Luo , Jinghao Miao , Jiangtao Hu , Jingao Wang , Jiaxuan Xu , Shu Jiang
CPC分类号: G05D1/0088 , G05D1/0214 , G05D1/0221 , G05D2201/0213
摘要: A method of navigating an autonomous driving vehicle (ADV) includes determining a target function for an open space model based on one or more obstacles and map information within a proximity of the ADV, then iteratively performing first and second quadratic programming (QP) optimizations on the target function. Then, generating a second trajectory based on results of the first and second QP optimizations to control the ADV autonomously using the second trajectory. The first QP optimization is based on fixing a first set of variables of the target function. The second QP optimization is based on maximizing a sum of the distances from the ADV to each of the obstacles over a plurality of points of the first trajectory, and minimizing a difference between a target end-state of the ADV and a determined final state of the ADV using the first trajectory.
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公开(公告)号:US11740628B2
公开(公告)日:2023-08-29
申请号:US16823066
申请日:2020-03-18
申请人: Baidu USA LLC
发明人: Shu Jiang , Qi Luo , Jinghao Miao , Jiangtao Hu , Yu Wang , Jinyun Zhou , Jiaming Tao , Xiangquan Xiao
CPC分类号: G05D1/0088 , B62D15/0285 , G05D1/0223 , G05D1/0274 , G05D2201/0212 , G05D2201/0213
摘要: In one embodiment, control of an autonomous driving vehicle (ADV) includes determining a current scenario of the ADV. Based on the scenario, a control algorithm is selected among a plurality of distinct control algorithms as the active control algorithm. One or more control commands are generated using the active control algorithm, based one or more target inputs. The control commands are applied to effect movement of the ADV.
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