Determining drivability of objects for autonomous vehicles

    公开(公告)号:US10203696B2

    公开(公告)日:2019-02-12

    申请号:US15292818

    申请日:2016-10-13

    Applicant: Waymo LLC

    Abstract: Aspects of the disclosure relate to maneuvering a vehicle. As an example, sensor information identifying a set of objects as well as a set of characteristics for each object of the set of objects is received from a perception system of a vehicle. The set of objects is filtered to remove objects corresponding to vehicles, bicycles, and pedestrians. An object within an expected future path of the vehicle is selected from the filtered set of objects. The object is classified as drivable or not drivable based on the set of characteristics. Drivable indicates that the vehicle can drive over the object without causing damage to the vehicle. The vehicle is maneuvered based on the classification such that when the object is classified as drivable, maneuvering the vehicle includes driving the vehicle over the object by not altering the expected future path of the vehicle.

    CAMERA SYSTEMS USING FILTERS AND EXPOSURE TIMES TO DETECT FLICKERING ILLUMINATED OBJECTS

    公开(公告)号:US20180336692A1

    公开(公告)日:2018-11-22

    申请号:US15613546

    申请日:2017-06-05

    Applicant: Waymo LLC

    Abstract: The technology relates to camera systems for vehicles having an autonomous driving mode. An example system includes a first camera mounted on a vehicle in order to capture images of the vehicle's environment. The first camera has a first exposure time and being without an ND filter. The system also includes a second camera mounted on the vehicle in order to capture images of the vehicle's environment and having an ND filter. The system also includes one or more processors configured to capture images using the first camera and the first exposure time, capture images using the second camera and the second exposure time, use the images captured using the second camera to identify illuminated objects, use the images captured using the first camera to identify the locations of objects, and use the identified illuminated objects and identified locations of objects to control the vehicle in an autonomous driving mode.

    Vision-based detection and classification of traffic lights

    公开(公告)号:US09779314B1

    公开(公告)日:2017-10-03

    申请号:US14538669

    申请日:2014-11-11

    Applicant: Waymo LLC

    CPC classification number: G06K9/00825 B60W30/00 G06K9/66

    Abstract: The present disclosure is directed to an autonomous vehicle having a vehicle control system. The vehicle control system includes an image processing system. The image processing system receives an image that includes a plurality of image portions. The image processing system also calculates a score for each image portion. The score indicates a level of confidence that a given image portion represents an illuminated component of a traffic light. The image processing system further identifies one or more candidate portions from among the plurality of image portions. Additionally, the image processing system determines that a particular candidate portion represents an illuminated component of a traffic light using a classifier. Further, the image processing system provides instructions to control the autonomous vehicle based on the particular candidate portion representing an illuminated component of a traffic light.

    Methods and systems for sun-aware vehicle routing

    公开(公告)号:US12061091B2

    公开(公告)日:2024-08-13

    申请号:US18156475

    申请日:2023-01-19

    Applicant: Waymo LLC

    Abstract: Example implementations may relate to sun-aware vehicle routing. In particular, a computing system of a vehicle may determine an expected position of the sun relative to a geographic area. Based on the expected position, the computing system may make a determination that travel of the vehicle through certain location(s) within the geographic area is expected to result in the sun being proximate to an object within a field of view of the vehicle's image capture device. Responsively, the computing system may generate a route for the vehicle in the geographic area based at least on the route avoiding travel of the vehicle through these certain location(s), and may then operate the vehicle to travel in accordance with the generated route. Ultimately, this may help reduce or prevent situations where quality of image(s) degrades due to sunlight, which may allow for use of these image(s) as basis for operating the vehicle.

    Multiple Operating Modes to Expand Dynamic Range

    公开(公告)号:US20240223882A1

    公开(公告)日:2024-07-04

    申请号:US18413521

    申请日:2024-01-16

    Applicant: Waymo LLC

    CPC classification number: H04N23/61 H04N23/45 H04N23/73 H04N23/741

    Abstract: Example embodiments relate to multiple operating modes to expand dynamic range. An example embodiment includes a camera system. The camera system may include a first image sensor having a first dynamic range corresponding to a first range of luminance levels in a scene. The system may also include a second image sensor having a second dynamic range corresponding to a second range of luminance levels in the scene. The camera system may further include a processor coupled to the first image sensor and the second image sensor. The processor may be configured to execute instructions to identify objects of a first type in a first image of the scene captured by the first image sensor and identify objects of a second object type in a second image of the scene captured by the second image sensor.

    TRAFFIC SIGNAL RESPONSE FOR AUTONOMOUS VEHICLES

    公开(公告)号:US20220161790A1

    公开(公告)日:2022-05-26

    申请号:US17670900

    申请日:2022-02-14

    Applicant: WAYMO LLC

    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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