TRAFFIC LIGHT DETECTION AND LANE STATE RECOGNITION FOR AUTONOMOUS VEHICLES

    公开(公告)号:US20210343150A1

    公开(公告)日:2021-11-04

    申请号:US17336856

    申请日:2021-06-02

    Applicant: Waymo LLC

    Abstract: Methods and system are provided for training and using a model to determine states of lanes of interest. For instance, image data including an image and an associated label identifying at least one traffic light, a state of the at least one traffic light, and a lane controlled by the at least one traffic light are received and used to train the model such that the model is configured to, in response to receiving an image and a lane of interest included in the image, output a lane state for the lane of interest. This model is then used by a vehicle in order to determine a state of a lane of interest. This state is then used to control the vehicle in an autonomous driving mode based on the state of the lane of interest.

    Traffic signal response for autonomous vehicles

    公开(公告)号:US10377378B2

    公开(公告)日:2019-08-13

    申请号:US15958365

    申请日:2018-04-20

    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.

    Methods and Systems for Sun-Aware Vehicle Routing

    公开(公告)号:US20190186931A1

    公开(公告)日:2019-06-20

    申请号:US15842055

    申请日:2017-12-14

    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.

    Vision-based detection and classification of traffic lights

    公开(公告)号:US10108868B1

    公开(公告)日:2018-10-23

    申请号:US15861840

    申请日:2018-01-04

    Applicant: Waymo LLC

    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.

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