公开(公告)号：US20220082403A1

公开(公告)日：2022-03-17

申请号：US17294984

申请日：2019-11-26

Applicant: Mobileye Vision Technologies Ltd.

Inventor： Dori SHAPIRA ,  Daniel BRAUNSTEIN ,  Yoram GDALYAHU ,  Kfir VIENTE ,  Maxim SCHWARTZ ,  Eli PEKER ,  David HUBERMAN ,  Moshe LEVIN ,  Jonathan BARLEV ,  Ora ZACKAY ,  Adi HAYAT ,  Andras FERENCZ ,  Dor EAGELBERG

IPC: G01C21/36 ,  G01C21/00 ,  G06V10/762 ,  G06V10/80 ,  G06V20/56

Abstract: Systems and methods are disclosed for mapping lanes for use in vehicle navigation. In one implementation, at least one processing device may be programmed to receive navigational information from a first vehicle and a second vehicle that have navigated along a road segment including a lane split feature; receive at least one image associated with the road segment; determine, from the first navigational information, a first actual trajectory of the first vehicle and a second actual trajectory of the second vehicle; determine a divergence between the first actual trajectory and the second actual trajectory; determine, based on analysis of the at least one image, that the divergence between the first actual trajectory and the second actual trajectory is indicative of the lane split feature; and update a vehicle road navigation model to include a first target trajectory and a second target trajectory that branches from the first target trajectory after the lane split feature.

公开(公告)号：US20230280183A1

公开(公告)日：2023-09-07

申请号：US18116084

申请日：2023-03-01

Applicant: Mobileye Vision Technologies Ltd.

Inventor： Adi HAYAT ,  Jonathan BARLEV

IPC: G01C21/00

CPC classification number: G01C21/3841 ,  G01C21/3819

Abstract: Systems and methods are provided for generating a crowd-sourced map for use in vehicle navigation. In one implementation, a system may include at least one processor configured to receive drive information collected from vehicles that traversed a junction; aggregate the received drive information to determine positions of traffic lights and spline representations for drivable paths; input the determined positions and the spline representations to a trained model configured to generate a traffic light relevancy mapping indicating a traffic light relevancy for traffic light to drivable path pairs of the junction; input an observed vehicle behavior to the at least one trained model to generate an updated traffic light relevancy mapping; store in the crowd-sourced map the indicators of traffic light relevancy for the traffic light to drivable path pairs; and transmit the crowd-sourced map to a vehicle for use in navigating the road segment.