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公开(公告)号：US10372129B1
公开(公告)日：2019-08-06
申请号：US15488836
申请日：2017-04-17
Applicant: Waymo LLC
Inventor： Christopher Paul Urmson , Dmitri A. Dolgov , Andrew Hughes Chatham , Philip Nemec
Abstract: A system and method are arranged to provide recommendations to a user of a vehicle. In one aspect, the vehicle navigates in an autonomous mode and the sensors provide information that is based on the location of the vehicle and output from sensors directed to the environment surrounding the vehicle. In further aspects, both current and previous sensor data is used to make the recommendations, as well as data based on the sensors of other vehicles.
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公开(公告)号：US20190193733A1
公开(公告)日：2019-06-27
申请号：US16238135
申请日：2019-01-02
Applicant: Waymo LLC
Inventor： Jared Stephen Russell , Dmitri A. Dolgov , Nathaniel Fairfield , Laura Estelle Lindzey , Christopher Paul Urmson
IPC: B60W30/18 , G05D1/02 , G08G1/00 , G01C21/34 , G08G1/0962 , G08G1/0967 , G05D1/00
CPC classification number: B60W30/18 , B60W2400/00 , B60W2550/10 , B60W2550/20 , B60W2720/10 , G01C21/3407 , G05D1/0088 , G05D1/0214 , G08G1/00 , G08G1/09623 , G08G1/09626 , G08G1/096725 , G08G1/167 , G08G1/202
Abstract: Aspects of the disclosure relate to generating a speed plan for an autonomous vehicle. As an example, the vehicle is maneuvered in an autonomous driving mode along a route using pre-stored map information. This information identifies a plurality of keep clear regions where the vehicle should not stop but can drive through in the autonomous driving mode. Each keep clear region of the plurality of keep clear regions is associated with a priority value. A subset of the plurality of keep clear regions is identified based on the route. A speed plan for stopping the vehicle is generated based on the priority values associated with the keep clear regions of the subset. The speed plan identifies a location for stopping the vehicle. The speed plan is used to stop the vehicle in the location.
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公开(公告)号：US10059334B1
公开(公告)日：2018-08-28
申请号：US15278338
申请日：2016-09-28
Applicant: Waymo LLC
Inventor： Jiajun Zhu , David I. Ferguson , Dmitri A. Dolgov
CPC classification number: B60W30/09 , B60W30/08 , B60W30/095 , B60W30/0956 , B60W50/0097 , B60W2550/10 , G01R19/25 , G05D1/0088 , G05D1/0212 , G05D1/0214 , G05D1/0289 , G06K9/00791 , G06K9/00798 , G06K9/00805 , G06K9/00818 , G06K9/00825 , G06K9/3241 , G06N20/00 , G08G1/09623 , G08G1/09626 , G08G1/096725 , G08G1/096741 , G08G1/096775 , G08G1/164 , G08G1/165 , G08G1/166
Abstract: A method and apparatus are provided for determining one or more behavior models used by an autonomous vehicle to predict the behavior of detected objects. The autonomous vehicle may collect and record object behavior using one or more sensors. The autonomous vehicle may then communicate the recorded object behavior to a server operative to determine the behavior models. The server may determine the behavior models according to a given object classification, actions of interest performed by the object, and the object's perceived surroundings.
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Patent Agency Ranking
54.发明申请公开(公告)号：US20180032084A1
公开(公告)日：2018-02-01
申请号：US15718794
申请日：2017-09-28
Applicant: Waymo LLC
Inventor： Dmitri A. Dolgov , Christopher Paul Urmson
Abstract: Models can be generated of a vehicle's view of its environment and used to maneuver the vehicle. This view need not include what objects or features the vehicle is actually seeing, but rather those areas that the vehicle is able to observe using its sensors if the sensors were completely un-occluded. For example, for each of a plurality of sensors of the object detection component, a computer may generate an individual 3D model of that sensor's field of view. Weather information is received and used to adjust one or more of the models. After this adjusting, the models may be aggregated into a comprehensive 3D model. The comprehensive model may be combined with detailed map information indicating the probability of detecting objects at different locations. The model of the vehicle's environment may be computed based on the combined comprehensive 3D model and detailed map information.
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公开(公告)号：US09868446B1
公开(公告)日：2018-01-16
申请号：US15383198
申请日：2016-12-19
Applicant: Waymo LLC
Inventor： Jiajun Zhu , Dmitri A. Dolgov , Christopher Paul Urmson
IPC: H04N7/18 , B60R1/00 , B60Q9/00 , G08G1/16 , G01D18/00 , B60W50/02 , B60W50/14 , G06K9/03 , G06K9/00 , B60W50/00
CPC classification number: B60W50/0205 , B60Q9/008 , B60R1/00 , B60R2300/8093 , B60W50/14 , B60W2050/0043 , B60W2050/0215 , B60W2050/146 , B60W2420/42 , B60W2420/52 , B60W2420/62 , G01D18/00 , G01S7/40 , G01S7/497 , G01S13/723 , G01S13/862 , G01S13/865 , G01S13/867 , G01S13/931 , G01S17/023 , G01S17/936 , G06K9/00791 , G06K9/03 , G08G1/163 , G08G1/166 , H04N7/181
Abstract: Methods and systems are disclosed for cross-validating a second sensor with a first sensor. Cross-validating the second sensor may include obtaining sensor readings from the first sensor and comparing the sensor readings from the first sensor with sensor readings obtained from the second sensor. In particular, the comparison of the sensor readings may include comparing state information about a vehicle detected by the first sensor and the second sensor. In addition, comparing the sensor readings may include obtaining a first image from the first sensor, obtaining a second image from the second sensor, and then comparing various characteristics of the images. One characteristic that may be compared are object labels applied to the vehicle detected by the first and second sensor. The first and second sensors may be different types of sensors.
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公开(公告)号：US20170341643A1
公开(公告)日：2017-11-30
申请号：US15618461
申请日：2017-06-09
Applicant: Waymo LLC
Inventor： Jens-Steffen Ralf Gutmann , Andreas Wendel , Nathaniel Fairfield , Dmitri A. Dolgov , Donald Jason Burnette
IPC: B60W30/09 , G08G1/0962
CPC classification number: B60W30/09 , G08G1/09623 , G08G1/09626 , G08G1/096725 , G08G1/096783 , G08G1/096791
Abstract: Aspects of the disclosure relate to determining whether a vehicle should continue through an intersection. For example, the one or more of the vehicle's computers may identify a time when the traffic signal light will turn from yellow to red. The one or more computers may also estimate a location of a vehicle at the time when the traffic signal light will turn from yellow to red. A starting point of the intersection may be identified. Based on whether the estimated location of the vehicle is at least a threshold distance past the starting point at the time when the traffic signal light will turn from yellow to red, the computers can determine whether the vehicle should continue through the intersection.
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公开(公告)号：US09707960B2
公开(公告)日：2017-07-18
申请号：US14448299
申请日：2014-07-31
Applicant: Waymo LLC
Inventor： Jens-Steffen Ralf Gutmann , Andreas Wendel , Nathaniel Fairfield , Dmitri A. Dolgov , Donald Jason Burnette
CPC classification number: B60W30/09 , G08G1/09623 , G08G1/09626 , G08G1/096725 , G08G1/096783 , G08G1/096791
Abstract: Aspects of the disclosure relate to determining whether a vehicle should continue through an intersection. For example, the one or more of the vehicle's computers may identify a time when the traffic signal light will turn from yellow to red. The one or more computers may also estimate a location of a vehicle at the time when the traffic signal light will turn from yellow to red. A starting point of the intersection may be identified. Based on whether the estimated location of the vehicle is at least a threshold distance past the starting point at the time when the traffic signal light will turn from yellow to red, the computers can determine whether the vehicle should continue through the intersection.
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公开(公告)号：US09690296B1
公开(公告)日：2017-06-27
申请号：US14872270
申请日：2015-10-01
Applicant: Waymo LLC
Inventor： Dmitri A. Dolgov , Christopher Paul Urmson
CPC classification number: G05D1/0214 , B60W30/08 , B60W30/09 , B60W30/095 , B60W30/0956 , B60W30/12 , B60W30/16 , B60W50/0097 , B60W2550/20 , B60W2720/10 , G01C21/26 , G05D1/0061 , G05D1/0088 , G08G1/16 , G08G1/166 , G08G1/167
Abstract: Aspects of the disclosure relate generally to detecting and avoiding blind spots of other vehicles when maneuvering an autonomous vehicle. Blind spots may include both areas adjacent to another vehicle in which the driver of that vehicle would be unable to identify another object as well as areas that a second driver in a second vehicle may be uncomfortable driving. In one example, a computer of the autonomous vehicle may identify objects that may be relevant for blind spot detecting and may determine the blind spots for these other vehicles. The computer may predict the future locations of the autonomous vehicle and the identified vehicles to determine whether the autonomous vehicle would drive in any of the determined blind spots. If so, the autonomous driving system may adjust its speed to avoid or limit the autonomous vehicle's time in any of the blind spots.
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