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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：US20220223170A1
公开(公告)日：2022-07-14
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：US20220219736A1
公开(公告)日：2022-07-14
申请号：US17149638
申请日：2021-01-14
申请人： Baidu USA LLC
发明人： Kecheng XU , Hongyi SUN , Qi LUO , Wei WANG , Zejun LIN , Wesley REYNOLDS , Feng LIU , Jiangtao HU , Jinghao MIAO
IPC分类号： B60W60/00 , H04R1/08 , G10L25/51 , G10L25/30 , G06K9/62 , G06K9/00 , G06K9/20 , H04R1/40 , H04R3/00 , H04N5/247 , B60W10/20 , B60W30/18 , B60W10/18 , G06N3/04 , G05B13/02
摘要： In one embodiment, an emergency vehicle detection system can be provided in the ADV travelling on a road to detect the presence of an emergency vehicle in a surrounding environment of the ADV using both audio data and visual data. The emergency vehicle detection system can use a trained neutral network to independently generate a detection result from the audio data, and use another trained network to independently generate another detection result from the visual data. The emergency vehicle detection system can fuse the two detection results to determine the position and moving direction of the emergency vehicle. The ADV can take appropriate actions in response to the position and moving direction of the emergency vehicle.
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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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公开(公告)号：US20220223037A1
公开(公告)日：2022-07-14
申请号：US17149659
申请日：2021-01-14
申请人： Baidu USA LLC
发明人： Kecheng XU , Hongyi SUN , Qi LUO , Wei WANG , Zejun LIN , Wesley REYNOLDS , Feng LIU , Jiangtao HU , Jinghao MIAO
IPC分类号： G08G1/0967 , G08G1/01 , G08G1/04 , G08G1/133 , G08G1/0965 , G06N3/04
摘要： According to various embodiments, systems, methods, and mediums for operating an autonomous driving vehicles (ADV) are described. The embodiments use a number of machine learning models to extract features individually from audio data and visual data captured by sensors mounted on the ADV, and then to fuse these extracted features to create a concatenated feature vectors. The concatenated feature vector is provided to a multiplayer perceptron (MLP) as input to generate a detection result related to the presence of an emergency vehicle in the surrounding environment. The detection result can be used by the ADV to take appropriate actions to comply with the local traffic rules.
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公开(公告)号：US20220097728A1
公开(公告)日：2022-03-31
申请号：US17039685
申请日：2020-09-30
申请人： Baidu USA LLC
发明人： Weiman LIN , Yu CAO , Yu WANG , Qi LUO , Shu JIANG , Xiangquan XIAO , Longtao LIN , Jinghao MIAO , Jiangtao HU
摘要： Systems and methods are disclosed for optimizing values of a set of tunable parameters of an autonomous driving vehicle (ADV). The controllers can be a linear quadratic regular, a “bicycle model,” a model-reference adaptive controller (MRAC) that reduces actuation latency in control subsystems such as steering, braking, and throttle, or other controller (“controllers”). An optimizer selects a set tunable parameters for the controllers. A task distribution system pairs each set of parameters with each of a plurality of simulated driving scenarios, and dispatches a task to the simulator to perform the simulation with the set of parameters. Each simulation is scored. A weighted score is generated from the simulation. The optimizer uses the weighted score as a target objective for a next iteration of the optimizer, for a fixed number of iterations. A physical real-world ADV is navigated using the optimized set of parameters for the controllers in the ADV.
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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：US20180374360A1
公开(公告)日：2018-12-27
申请号：US15542412
申请日：2017-06-22
发明人： Jinghao MIAO , Liyun LI , Zhongpu XIA
摘要： In one embodiment, in response to perception data perceiving a driving environment surrounding an ADV, a map image of a map covering a location associated with the driving environment is obtained. An image recognition is performed on the map image to recognize one or more objects from the map image. An object may represent a particular road, a building structure (e.g., a parking lot, an intersection, or a roundabout). One or more features are extracted from the recognized objects, where the features may indicate or describe the traffic condition of the driving environment. Behaviors of one or more traffic participants perceived from the perception data are predicted based on the extracted features. A trajectory for controlling the ADV to navigate through the driving environment is planned based on the predicted behaviors of the traffic participants. A traffic participant can be a vehicle, a cyclist, or a pedestrian.
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公开(公告)号：US20230060776A1
公开(公告)日：2023-03-02
申请号：US17446648
申请日：2021-09-01
申请人： Baidu USA LLC
发明人： Shu JIANG , Weiman LIN , Yu CAO , Yu WANG , Qi LUO , Jiangtao HU , Jinghao MIAO
IPC分类号： B60W60/00 , B60W30/095 , B60W30/18 , G01C21/34
摘要： Embodiments of the invention are intended to evaluate the performance of a planning module of the ADV in terms of decision consistency in addition to other metrics, such as comfort, latency, controllability, and safety. In one embodiment, an exemplary method includes receiving, at an autonomous driving simulation platform, a record file recorded by the ADV that was automatically driving on a road segment; simulating operations of a dynamic model of the ADV in the autonomous driving simulation platform during one or more driving scenarios on the road segment based on the record file. The method further includes performing a comparison between each planned trajectory generated by a planning module of the dynamic model after an initial period of time with each trajectory stored in a buffer; and modifying a performance score generated by a planning performance profiler in the autonomous driving simulation platform based on a result of the comparison.
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