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公开(公告)号：US20170167881A1
公开(公告)日：2017-06-15
申请号：US15376574
申请日：2016-12-12
IPC分类号： G01C21/32 , G01N21/47 , G05D1/00 , B60W30/18 , B60W40/068
摘要： A vehicle determines a traction value for a surface of a road segment, and associates the traction value with a location of the surface. The vehicle stores the traction value and location as part of a traction map.
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公开(公告)号：US10452070B2
公开(公告)日：2019-10-22
申请号：US15705507
申请日：2017-09-15
摘要： The present disclosure provides systems and methods that employ tolerance values defining a level of vehicle control precision for motion control of an autonomous vehicle. More particularly, a vehicle controller can obtain a trajectory that describes a proposed motion path for the autonomous vehicle. A constraint set of one or more tolerance values (e.g., a longitudinal tolerance value and/or lateral tolerance value) defining a level of vehicle control precision can be determined or otherwise obtained. Motion of the autonomous vehicle can be controlled to follow the trajectory within the one or more tolerance values (e.g., longitudinal tolerance value(s) and/or a lateral tolerance value(s)) identified by the constraint set. By creating a motion control framework for autonomous vehicles that includes an adjustable constraint set of tolerance values, autonomous vehicles can more effectively implement different precision requirements for different driving situations.
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公开(公告)号：US20190220013A1
公开(公告)日：2019-07-18
申请号：US15983491
申请日：2018-05-18
CPC分类号： G05D1/0088 , B60R16/023 , G01S13/723 , G01S13/865 , G01S13/867 , G01S13/931 , G01S17/023 , G01S17/66 , G01S17/933 , G01S17/936 , G01S2013/9342 , G01S2013/9346 , G01S2013/935 , G01S2013/9367 , G01S2013/9382 , G05D1/0238 , G05D1/0257 , G05D2201/0213 , G06N5/04 , G06N20/00
摘要： Generally, the present disclosure is directed to systems and methods for streaming processing within one or more systems of an autonomy computing system. When an update for a particular object or region of interest is received by a given system, the system can control transmission of data associated with the update as well as a determination of other aspects by the given system. For example, the system can determine based on a received update for a particular aspect and a priority classification and/or interaction classification determined for that aspect whether data associated with the update should be transmitted to a subsequent system before waiting for other updates to arrive.
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公开(公告)号：US20190056484A1
公开(公告)日：2019-02-21
申请号：US15679338
申请日：2017-08-17
IPC分类号： G01S7/497
摘要： A LIDAR calibration system can detect a first set of return signals from a plurality of fiducial targets in a calibration facility for a lower set of laser scanners of the LIDAR module. The LIDAR calibration system can also detect a second set of return signals from one or more planar surfaces associated with a calibration trigger location on a road network for an upper set of laser scanners of the LIDAR module. Based on the first and second sets of return signals, the LIDAR calibration system can generate a set of calibration transforms to adjust a set of intrinsic parameters of the LIDAR module.
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公开(公告)号：US20180342033A1
公开(公告)日：2018-11-29
申请号：US15602204
申请日：2017-05-23
摘要： An on-demand transportation management system can perform trip classification operations based at least on risk by establishing a set of risk thresholds for safety-driven autonomous vehicles, fully autonomous vehicles, and/or the software versions executable by such vehicles. Based on the trip classifications, the on-demand transportation management system can perform vehicle matching operation with requesting users.
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公开(公告)号：US20180341888A1
公开(公告)日：2018-11-29
申请号：US15602327
申请日：2017-05-23
摘要： An on-demand transportation management system can collect historical data of harmful events of human-driven vehicles (HDVs) operating throughout a given region. For each road segment of the given region, the system can determine a fractional risk value for the HDVs, and based on the fractional risk value for each road segment, the system can route drivers within the given region along lowest risk route options.
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公开(公告)号：US20180341887A1
公开(公告)日：2018-11-29
申请号：US15602313
申请日：2017-05-23
摘要： An on-demand transportation management system can receive transport requests from requesting users for an on-demand transportation service for a given region, each transport request indicating a pick-up location and a destination. The system can determine a candidate set of vehicles, within a proximity of the pick-up location, to service each transport request. The system may then determine an individual risk value for each vehicle in the candidate set of vehicles for servicing the transport request, based, at least in part, on the individual risk value for each vehicle of the candidate set of vehicles, the system can select a vehicle from the candidate set of vehicles to service the transport request.
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公开(公告)号：US20180341571A1
公开(公告)日：2018-11-29
申请号：US15602244
申请日：2017-05-23
摘要： An autonomous vehicle software management system can distribute AV software versions to safety-driven autonomous vehicles (SDAVs) operating within a given region. The system can receive log data from the SDAVs indicating any trip anomalies of the SDAVs while executing the AV software version. When a predetermined safety standard has been met based on the log data, the system can verify the AV software version for execution on fully autonomous vehicles (FAVs) operating within the given region.
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公开(公告)号：US20180341276A1
公开(公告)日：2018-11-29
申请号：US15602292
申请日：2017-05-23
摘要： An autonomous vehicle (AV) software management system can collect historical data of harmful events of human-driven vehicles (HDVs) within an autonomy grid on which AVs operate. For each path segment of the autonomy grid, the system can determine a fractional risk value for HDVs. The system may also receive AV data from a fleet of AVs operating throughout the autonomy grid, and for each path segment of the autonomy grid, the system can evaluate AV performance against the fractional risk values for HDVs based on the received AV data.
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公开(公告)号：US10019011B1
公开(公告)日：2018-07-10
申请号：US15791646
申请日：2017-10-24
CPC分类号： G05D1/0221 , B60W30/0953 , B60W30/0956 , B60W30/18109 , B60W30/18154 , B60W2550/22 , G05D1/0088 , G05D1/0223 , G05D2201/0213 , G08G1/0112 , G08G1/0129 , G08G1/09623 , G08G1/166
摘要： The present disclosure provides autonomous vehicle systems and methods that include or otherwise leverage a machine-learned yield model. In particular, the machine-learned yield model can be trained or otherwise configured to receive and process feature data descriptive of objects perceived by the autonomous vehicle and/or the surrounding environment and, in response to receipt of the feature data, provide yield decisions for the autonomous vehicle relative to the objects. For example, a yield decision for a first object can describe a yield behavior for the autonomous vehicle relative to the first object (e.g., yield to the first object or do not yield to the first object). Example objects include traffic signals, additional vehicles, or other objects. The motion of the autonomous vehicle can be controlled in accordance with the yield decisions provided by the machine-learned yield model.
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