公开(公告)号：US20210004010A1

公开(公告)日：2021-01-07

申请号：US16458853

申请日：2019-07-01

申请人： Baidu USA LLC

发明人： Jiacheng PAN ,  Yifei JIANG ,  Yajia ZHANG ,  Jiaming TAO ,  Jiangtao HU

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

摘要： According to one embodiment, during a first planning cycle, a first lane boundary of a driving environment perceived by an ADV is determined using a first lane boundary determination scheme (e.g., current lane boundary), which has been designated as a current lane boundary determination scheme. A first trajectory is planned based on the first lane boundary to drive the ADV to navigate through the driving environment. The first trajectory is evaluated against a predetermined set of safety rules (e.g., whether it will collide or get too close to an object) to avoid a collision with an object detected in the driving environment. In response to determining that the first trajectory fails to satisfy the safety rules, a second lane determination boundary of the driving environment is determined using a second lane boundary determination scheme and a second trajectory is planned based on the second lane boundary to drive the ADV.

公开(公告)号：US20200031340A1

公开(公告)日：2020-01-30

申请号：US16048003

申请日：2018-07-27

申请人： Baidu USA LLC

发明人： Jiaming TAO ,  Liangliang ZHANG ,  Dong LI ,  Yifei JIANG ,  Jiangtao HU ,  Fan ZHU

IPC分类号： B60W30/095 ,  B60W30/14 ,  B60W30/16 ,  G05D1/02

摘要： In some implementations, a method is provided. The method includes determining a path for an autonomous driving vehicle. The path is located within a first lane of an environment in which the autonomous driving vehicle is currently located. The method also includes obtaining sensor data. The sensor data indicates a set of speeds for a set of moving obstacles located in a second lane of the environment and wherein the second lane is adjacent to the first lane. The method further includes determining whether the set of speeds is lower than a threshold speed. The method further includes determining a new speed for the autonomous driving vehicle in response to determining that the set of speeds is lower than the threshold speed. The method further includes controlling the autonomous driving vehicle based on the path and the new speed.

公开(公告)号：US20190086932A1

公开(公告)日：2019-03-21

申请号：US15707236

申请日：2017-09-18

申请人： Baidu USA LLC

发明人： Haoyang FAN ,  Liangliang ZHANG ,  Yajia ZHANG ,  Weicheng ZHU ,  Yifei JIANG ,  Qi LUO ,  Jiangtao HU ,  Qi KONG

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

摘要： According to some embodiments, a system determines a number of boundary areas having predetermined dimensions centered around each of a number of control points of a first reference line. The system selects a number of two-dimensional polynomials each representing a segment of an optimal reference line between adjacent control points. The system defines a set of constraints to the two-dimensional polynomials to at least ensure the two-dimensional polynomials passes through each of the boundary areas. The system performs a quadratic programming (QP) optimization on a target function such that a total cost of the target function reaches minimum while the set of constraints are satisfied. The system generates a second reference line representing the optimal reference line based on the QP optimization to control the ADV autonomously according to the second reference line.

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

IPC分类号： G10L25/51 ,  H04R1/08 ,  H04R1/40 ,  H04R3/00 ,  G06N20/00 ,  G06N5/04 ,  G05D1/02

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.

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.

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

IPC分类号： B60W50/00 ,  G05D1/00 ,  B60W30/18

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.

公开(公告)号：US20190278290A1

公开(公告)日：2019-09-12

申请号：US15772525

申请日：2018-03-08

申请人： Baidu USA LLC

发明人： Liangliang ZHANG ,  Kairui YANG ,  Jiangtao HU

IPC分类号： G05D1/02 ,  G05D1/00 ,  G06K9/00 ,  G01C21/32 ,  G01S13/93 ,  G01S7/40

摘要： In one embodiment, a system is designed to determine the requirement of a perception range for a particular type of vehicles and a particular planning and control technology. A shadow filter is used to connect a scenario based simulator and a PnC module, and tuning the parameters (e.g. decreasing the filter range, tuning the probability of obstacles to be observed among frames) of shadow filter to mimic the real world perceptions with a limited range and reliabilities. Based on the simulation results (e.g., a failure rate, smoothness, etc.), the system is able to determine the required perception distance for the current PnC module. A PnC module represents a particular autonomous driving planning and control technology for a particular type of autonomous driving vehicles. Notice that the PnC module is replaceable so that this method is suitable for different PnC algorithms representing different autonomous driving technologies.

公开(公告)号：US20170242875A1

公开(公告)日：2017-08-24

申请号：US15051297

申请日：2016-02-23

申请人： Baidu USA LLC

发明人： Yifei JIANG ,  Shuang WU ,  Dong LI ,  Jiangtao HU ,  Fan ZHU ,  Qi KONG ,  Guang YANG ,  Jingao WANG

IPC分类号： G06F17/30

CPC分类号： G06F17/30268 ,  G06F17/3028 ,  G06F17/30554 ,  G06F17/30707 ,  G06F17/30864 ,  G06F17/30867

摘要： According to one embodiment, a content analysis module receives content information of a content item, the content information including a plurality of first keywords associated with the content item. The content analysis module performs an analysis on the first keywords associated with the content item. A keyword classifier categories the first keywords into a plurality of categories based on the analysis, each category including one or more second keywords selected from the first keywords. For each of the categories, one or more images are identified based on the corresponding second keywords. A category/image mapping module generates a category/image mapping table for the content item to map each of the categories to the corresponding identified images. The category/image mapping table is utilized to match the content item to one of the images based on a subsequent category determined in response to a search query.

公开(公告)号：US20240001966A1

公开(公告)日：2024-01-04

申请号：US17810012

申请日：2022-06-30

申请人： Baidu USA LLC

发明人： Shu JIANG ,  Yu CAO ,  Weiman LIN ,  Szu Hao WU ,  Jiangtao HU

IPC分类号： B60W60/00 ,  G06V20/58 ,  G06V10/82

CPC分类号： B60W60/00276 ,  G06V20/58 ,  G06V10/82 ,  B60W2554/4046

摘要： According to various embodiments, the disclosure discloses systems, methods and media for formulating training datasets for learning-based components in an autonomous driving vehicle (ADV). In an embodiment, an exemplary method includes allocating training datasets for training a learning-based model in the ADV, each training dataset being allocated to one of multiple predefined driving scenarios; determining a weight of each training dataset out of the training datasets; and optimizing the weight of each training dataset in one or more iterations according to a predetermined algorithm until a performance of the learning-based model reaches a predetermined threshold. The predetermined algorithm is one of a random search algorithm, a grid search algorithm, or a Bayesian algorithm.

公开(公告)号：US20230391356A1

公开(公告)日：2023-12-07

申请号：US17805000

申请日：2022-06-01

申请人： Baidu USA LLC

发明人： Shu JIANG ,  Szu Hao WU ,  Yu CAO ,  Weiman LIN ,  Jiangtao HU

IPC分类号： B60W60/00 ,  G06V20/56 ,  G06V20/58

CPC分类号： B60W60/001 ,  G06V20/588 ,  G06V20/582 ,  G06K9/6257

摘要： According to some embodiments, systems, methods and media for dynamically generating scenario parameters for an autonomous driving vehicles (ADV) are described. In one embodiment, when an ADV enters a driving scenario, the ADV can invoke a map-based scenario checker to determine the type of scenario, and invokes a corresponding neural network model to generate a set of parameters for the scenario based on real-time environmental conditions (e.g., traffics) and vehicle status information (e.g., speed). The set of scenario parameters can be a set of extra constraints for configuring the ADV to drive in a driving mode corresponding to the scenario.