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公开(公告)号：US20210294340A1
公开(公告)日：2021-09-23
申请号：US16827452
申请日：2020-03-23
申请人： Baidu USA LLC
发明人： Jinyun Zhou , Qi Luo , Shu Jiang , Jiaming Tao , Yu Wang , JiaXuan Xu , KeCheng Xu , Jinghao Miao , Jiangtao Hu
摘要： In one embodiment, a method determines a route from a first location of an autonomous driving vehicle (ADV) to a second location within an open space, the first location being a current location of the ADV. The method determines an objective function based on the route, the objective function having a set of costs for maneuvering the ADV from the first location to the second location. The method determines environmental conditions of the open space and uses the environmental conditions to determine a set of weights, each weight to be applied to a corresponding cost of the objective function. The method optimizes the objective function in view of one or more constraints, such that an output of the objective function reaches minimum while the one or more constraints are satisfied and generates a path trajectory with the optimized objective function to control the ADV autonomously according to the path trajectory.
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公开(公告)号：US11054829B2
公开(公告)日：2021-07-06
申请号：US16037908
申请日：2018-07-17
申请人： Baidu USA LLC
发明人： Yajia Zhang , Dong Li , Liangliang Zhang , Kecheng Xu , Jiaming Tao , Yifei Jiang , Qi Luo , Jiangtao Hu , Jinghao Miao
摘要： Methods and systems for multimodal motion planning framework for autonomous driving vehicles are disclosed. In one embodiment, driving environment data of an autonomous vehicle is received, where the environment data includes a route segment. The route segment is segmented into a number of route sub-segments. A specific driving scenario is assigned to each of the route sub-segments, where each specific driving scenario is included in a set of driving scenarios. A first motion planning algorithm is assigned according to a first assigned driving scenario included in the set of driving scenarios. The first motion planning algorithm is invoked to generate a first set of trajectories. The autonomous vehicle is controlled based on the first set of trajectories.
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公开(公告)号：US10809736B2
公开(公告)日：2020-10-20
申请号：US16233494
申请日：2018-12-27
申请人： Baidu USA LLC
发明人： Kecheng Xu , Haoyang Fan , Yajia Zhang , Qi Luo , Jiacheng Pan , Jinghao Miao
IPC分类号： G05D1/00 , G05D1/02 , G06N20/00 , G06N3/08 , G06K9/00 , B60W40/072 , G06N5/04 , B60W60/00 , B60W30/095
摘要： In one embodiment, a data processing system for an autonomous driving vehicle (ADV) includes a processor, and a memory coupled to the processor to store instructions, which when executed by the processor, cause the processor to perform operations. The operations include generating a station-time (ST) graph based on perception data obtained from one or more sensors of the ADV, the ST graph including representing a location of an obstacle at different points in time, obtaining a tensor based on the ST graph, the tensor including a plurality of layers, the plurality of layers including a first layer having data representing one or more obstacles on a path in which the ADV is moving, applying a machine-learning model to the plurality of layers of the tensor to generate a plurality of numerical values, the plurality of numerical values defining a potential path trajectory of the ADV, and determining a path trajectory of the ADV based on the plurality of numerical values.
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公开(公告)号：US10775790B2
公开(公告)日：2020-09-15
申请号：US15893453
申请日：2018-02-09
申请人： Baidu USA LLC
发明人： Qi Luo , Lin Ma , Chuming Zhao , Wenda Zeng , Zhenguang Zhu , Qi Kong
IPC分类号： G05D1/00
摘要： Methods and systems for operating an autonomous driving vehicle (ADV) are disclosed. A current state of an ADV is sampled at a first time to obtain a set of parameters. A cost, from a cost function that reflects desired control goals, is generated for a future time horizon based at least in part on the set of parameters. The cost is minimized with one or more constraints to obtain target control input values. For each of the target control input values, a lookup operation is performed using the control input value to locate a first mapping entry that approximately corresponds to the control input value. A first control command is derived from the first mapping entry. The ADV is controlled using the derived first control command.
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公开(公告)号：US20190250609A1
公开(公告)日：2019-08-15
申请号：US15893453
申请日：2018-02-09
申请人： Baidu USA LLC
发明人： Qi Luo , Lin Ma , Chuming Zhao , Wenda Zeng , Zhenguang Zhu , Qi Kong
IPC分类号： G05D1/00
摘要： Methods and systems for operating an autonomous driving vehicle (ADV) are disclosed. A current state of an ADV is sampled at a first time to obtain a set of parameters. A cost, from a cost function that reflects desired control goals, is generated for a future time horizon based at least in part on the set of parameters. The cost is minimized with one or more constraints to obtain target control input values. For each of the target control input values, a lookup operation is performed using the control input value to locate a first mapping entry that approximately corresponds to the control input value. A first control command is derived from the first mapping entry. The ADV is controlled using the derived first control command.
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公开(公告)号：US10272924B2
公开(公告)日：2019-04-30
申请号：US15383843
申请日：2016-12-19
申请人： Baidu USA LLC
发明人： Qi Luo , Qi Kong , Fan Zhu , Sen Hu , Xiang Yu , Guang Yang , Jingao Wang
摘要： Described is a system and method that provides the ability for an autonomous driving vehicle (ADV) to determine (or estimate) one or more control characteristics for the ADV. In order to determine these control characteristics, the system may perform one or more driving maneuvers such as an acceleration or deceleration maneuver, and a constant velocity maneuver. By performing these maneuvers using various known forces, the system may then perform various calculations to obtain one or more unknown characteristics. For example, the system may determine as estimated mass of the ADV, and as a result, adjust (or tune) various controls of the ADV based on the estimated mass.
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37.发明授权公开(公告)号：US11453409B2
公开(公告)日：2022-09-27
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：US11430466B2
公开(公告)日：2022-08-30
申请号：US17248196
申请日：2021-01-13
申请人： Baidu USA LLC
发明人： Hongyi Sun , Kecheng Xu , Qi Luo , Zejun Lin , Wei Wang , Wesley Reynolds , Jiangtao Hu , Jinghao Miao
摘要： Systems and methods for sound source detection and localization utilizing an autonomous driving vehicle (ADV) are disclosed. The method includes receiving audio data from a number of audio sensors mounted on the ADV. The audio data comprises sounds captured by the audio sensors and emitted by one or more sound sources. Based on the received audio data, the method further includes determining a number of sound source information. Each sound source information comprises a confidence score associated with an existence of a specific sound. The method further includes generating a data representation to report whether there exists the specific sound within the driving environment of the ADV. The data representation comprises the determined sound source information. The received audio data and the generated data representation are utilized to subsequently train a machine learning algorithm to recognize the specific sound source during autonomous driving of the ADV in real-time.
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公开(公告)号：US11377112B2
公开(公告)日：2022-07-05
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： 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.
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公开(公告)号：US11167770B2
公开(公告)日：2021-11-09
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 , B60W50/00
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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