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公开(公告)号：US20220315046A1
公开(公告)日：2022-10-06
申请号：US16627257
申请日：2019-12-20
发明人： Shu JIANG , Qi LUO , Jinghao MIAO , Jiangtao HU , Yu WANG , Jiaxuan XU , Jinyun ZHOU , Kuang HU , Chao MA
摘要： 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.
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公开(公告)号：US20210229678A1
公开(公告)日：2021-07-29
申请号：US16643154
申请日：2020-01-23
发明人： Yu WANG , Qi LUO , Yu CAO , Feng Zongbao , Lin LONGTAO , Xiao XIANGQUAN , Jinghao MIAO , Jingtao HU , Jingao WANG , Shu JIANG , Jinyun ZHOU , Jiaxuan XU
IPC分类号： B60W40/105 , G06F16/23 , G06F16/9035
摘要： 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.
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公开(公告)号：US20210197865A1
公开(公告)日：2021-07-01
申请号：US16727799
申请日：2019-12-26
申请人： Baidu USA LLC
发明人： Jinyun ZHOU , Shu JIANG , Jiaming TAO , Qi LUO , Jinghao MIAO , Jiangtao HU , Jiaxuan XU , Yu WANG
摘要： 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.
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公开(公告)号：US20210139038A1
公开(公告)日：2021-05-13
申请号：US16682445
申请日：2019-11-13
申请人： Baidu USA LLC
发明人： Yu WANG , Qi LUO , Shu JIANG , Jinghao MIAO , Jiangtao HU , Jingao WANG , Jinyun ZHOU , Runxin HE , Jiaxuan XU
摘要： In one embodiment, a method of generating control effort to control an autonomous driving vehicle (ADV) includes determining a gear position (forward or reverse) in which the ADV is driving and selecting a driving model and a predictive model based upon the gear position. In a forward gear, the driving model is a dynamic model, such as a “bicycle model,” and the predictive model is a look-ahead model. In a reverse gear, the driving model is a hybrid dynamic and kinematic model and the predictive model is a look-back model. A 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, and an augmented control logic determines a second, additional, control effort, to determine a final control effort that is output to a control module of the ADV to drive the ADV.
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5.发明申请公开(公告)号：US20210323564A1
公开(公告)日：2021-10-21
申请号：US16854718
申请日：2020-04-21
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) 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.
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公开(公告)号：US20210261160A1
公开(公告)日：2021-08-26
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：US20210116916A1
公开(公告)日：2021-04-22
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
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：US20210253118A1
公开(公告)日：2021-08-19
申请号：US16790036
申请日：2020-02-13
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
IPC分类号： B60W50/08 , B60W50/035
摘要： 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.
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公开(公告)号：US20210139022A1
公开(公告)日：2021-05-13
申请号：US16678387
申请日：2019-11-08
申请人： Baidu USA LLC
发明人： Jiaming TAO , Jiaxuan XU , Jiacheng PAN , Jinyun ZHOU , Hongyi SUN , Yifei JIANG , Jiangtao HU
IPC分类号： B60W30/095 , B60W30/09 , B60W30/18 , G05D1/00 , G06K9/00
摘要： In one embodiment, a process is performed during controlling Autonomous Driving Vehicle (ADV). A confidence level associated with a sensed obstacle is determined. If the confidence level is below a confidence threshold, and a distance between the ADV and a potential point of contact with the sensed obstacle is below a distance threshold, then performance of a driving decision is delayed. Otherwise, the driving decision is performed to reduce risk of contact with the sensed obstacle.
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公开(公告)号：US20200342693A1
公开(公告)日：2020-10-29
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
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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