LOCALIZING VEHICLE NAVIGATION USING LANE MEASUREMENTS

• US 20180024562A1
• Filed: 07/21/2017
• Published: 01/25/2018
• Est. Priority Date: 07/21/2016
• Status: Active Grant

• Current Assignee: MobilEye Vision Technologies Ltd. (Intel Corporation)
• Original Assignee: MobilEye Vision Technologies Ltd. (Intel Corporation)
• Inventors: Bellaiche, Levi Itzhak
• Granted Patent: US 10,248,124 B2
• Time in Patent Office: Days
• CPC Class Codes: B60R 1/025 comprising special mechanical means for correcting the field of view in relation to particular driving conditions, e.g. change of lane; scanning mirrors
• CPC Class Codes: B60R 11/04 Mounting of cameras operative during drive; Arrangement of controls thereof relative to the vehicle
• CPC Class Codes: B60R 2011/0026 Windows, e.g. windscreen
• CPC Class Codes: B60W 10/20 including control of steering systems
• CPC Class Codes: B60W 2420/403 Image sensing, e.g. optical camera
• CPC Class Codes: B60W 2552/30 Road curve radius
• CPC Class Codes: B60W 2552/50 Barriers
• CPC Class Codes: B60W 2552/53 Road markings, e.g. lane marker or crosswalk
• CPC Class Codes: B60W 2554/20 Static objects
• CPC Class Codes: B60W 2554/4026 Cycles
• CPC Class Codes: B60W 2554/4029 Pedestrians
• CPC Class Codes: B60W 2554/60 Traversable objects, e.g. speed bumps or curbs
• CPC Class Codes: B60W 2554/802 Longitudinal distance
• CPC Class Codes: B60W 2554/804 Relative longitudinal speed
• CPC Class Codes: B60W 2720/10 Longitudinal speed
• CPC Class Codes: B60W 2720/106 Longitudinal acceleration
• CPC Class Codes: B60W 30/12 Lane keeping
• CPC Class Codes: B60W 60/0016 of the vehicle or its occupants
• CPC Class Codes: G01C 21/28 with correlation of data from several navigational instruments
• CPC Class Codes: G01C 21/36 Input/output arrangements for on-board computers
• CPC Class Codes: G01C 21/3602 : Input other than that of destination using image analysis, e.g. detection of road signs, lanes, buildings, real preceding vehicles using a camera
• CPC Class Codes: G01C 21/3658 : Lane guidance
• CPC Class Codes: G01S 13/867 : Combination of radar systems with cameras
• CPC Class Codes: G01S 13/931 : of land vehicles
• CPC Class Codes: G01S 19/42 : Determining position
• CPC Class Codes: G01S 19/485 : whereby the further system is an optical system or imaging system
• CPC Class Codes: G01S 19/52 : Determining velocity
• CPC Class Codes: G05D 1/0212 : with means for defining a desired trajectory involving a plurality of land vehicles G05D1/0287
• CPC Class Codes: G05D 1/0253 : extracting relative motion information from a plurality of images taken successively, e.g. visual odometry, optical flow determining position or orientation from images G06T7/70
• CPC Class Codes: G05D 1/0274 : using mapping information stored in a memory device navigation using map-matching G01C21/30
• CPC Class Codes: G05D 1/0278 : using satellite positioning signals, e.g. GPS
• CPC Class Codes: G05D 1/0285 : using signals transmitted via a public communication network, e.g. GSM network
• CPC Class Codes: G06F 18/24 : Classification techniques
• CPC Class Codes: G06T 2200/08 : involving all processing steps from image acquisition to 3D model generation
• CPC Class Codes: G06T 2207/10024 : Color image
• CPC Class Codes: G06T 2207/10028 : Range image; Depth image; 3D point clouds
• CPC Class Codes: G06T 2207/30241 : Trajectory
• CPC Class Codes: G06T 2207/30256 : Lane; Road marking
• CPC Class Codes: G06T 7/73 : using feature-based methods
• CPC Class Codes: G06T 7/74 : involving reference images or patches
• CPC Class Codes: G06V 20/582 : of traffic signs
• CPC Class Codes: G06V 20/584 : of vehicle lights or traffic lights
• CPC Class Codes: G06V 20/588 : Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
• CPC Class Codes: G08G 1/167 : Driving aids for lane monitoring, lane changing, e.g. blind spot detection
• CPC Class Codes: H04L 67/12 : specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: H04W 4/44 : for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H]

Abstract

Systems and methods are provided for vehicle localization using lane measurements. In one implementation, a method of correcting a position of a vehicle navigating a road segment may include determining, based on an output of at least one navigational sensor, a measured position of the vehicle along a predetermined road model trajectory; receiving at least one image representative of an environment of the vehicle, analyzing the at least one image to identify at least one lane marking, determining, based on the at least one image, a distance from the vehicle to the at least one lane marking, determining an estimated offset of the vehicle from the predetermined road model trajectory based on the measured position of the vehicle and the determined distance, and determining an autonomous steering action for the vehicle based on the estimated offset to correct the position of the vehicle.

Claims

1. A system for correcting a position of a vehicle navigating a road segment, the system comprising:

at least one processing device configured to;

determine, based on an output of at least one navigational sensor, a measured position of the vehicle along a predetermined road model trajectory, wherein the predetermined road model trajectory is associated with the road segment;

receive, from an image capture device, at least one image representative of an environment of the vehicle;

analyze the at least one image to identify at least one lane marking, wherein the at least one lane marking is associated with a lane of travel along the road segment;

determine, based on the at least one image, a distance from the vehicle to the at least one lane marking;

determine an estimated offset of the vehicle from the predetermined road model trajectory based on the measured position of the vehicle and the determined distance; and

determine an autonomous steering action for the vehicle based on the estimated offset to correct the position of the vehicle.

2. The system of claim 1, wherein the predetermined road model trajectory includes a three-dimensional polynomial representation of a target trajectory along the road segment.

3. The system of claim 1, wherein the at least one processing device is further configured to adjust a steering system of the vehicle based on the autonomous steering action.

4. The system of claim 1, wherein determining the estimated offset further includes determining, based on the distance to the at least one lane marking, whether the vehicle is on a trajectory that will intersect the at least one lane marking.

5. The system of claim 1, wherein determining the estimated offset further includes determining, based on the distance to the at least one lane marking, whether the vehicle is within a predetermined threshold of the at least one lane marking.

6. The system of claim 1, wherein the at least one navigational sensor includes a speed sensor or an accelerometer.

7. The system of claim 1, wherein determining the autonomous steering action for the vehicle further includes solving for at least one derivative of the predetermined road model trajectory.

8. A method for correcting a position of a vehicle navigating a road segment, the method comprising:

determining, based on an output of at least one navigational sensor, a measured position of the vehicle along a predetermined road model trajectory, wherein the predetermined road model trajectory is associated with the road segment;

receiving, from an image capture device, at least one image representative of an environment of the vehicle;

analyzing the at least one image to identify at least one lane marking, wherein the at least one lane marking is associated with a lane of travel along the road segment;

determining, based on the at least one image, a distance from the vehicle to the at least one lane marking;

determining an estimated offset of the vehicle from the predetermined road model trajectory based on the measured position of the vehicle and the determined distance; and

determining an autonomous steering action for the vehicle based on the estimated offset to correct the position of the vehicle.

9. The method of claim 8, further comprising adjusting a steering system of the vehicle based on the autonomous steering action.

10. The method of claim 8, wherein determining the estimated offset further includes determining, based on the distance to the at least one lane marking, whether the vehicle is on a trajectory that will intersect the at least one lane marking.

11. The method of claim 8, wherein determining the estimated offset further includes determining, based on the distance to the at least one lane marking, whether the vehicle is within a predetermined threshold of the at least one lane marking.

12. The method of claim 8, wherein determining the autonomous steering action for the vehicle further includes solving for at least one derivative of the predetermined road model trajectory.

13. A non-transitory, computer-readable medium storing instructions that, when executed by at least one processing device, cause the device to:

determine, based on an output of at least one navigational sensor, a measured position of the vehicle along a predetermined road model trajectory, wherein the predetermined road model trajectory is associated with the road segment;

receive, from an image capture device, at least one image representative of an environment of the vehicle;

analyze the at least one image to identify at least one lane marking, wherein the at least one lane marking is associated with a lane of travel along the road segment;

determine, based on the at least one image, a distance from the vehicle to the at least one lane marking;

determine an estimated offset of the vehicle from the predetermined road model trajectory based on the measured position of the vehicle and the determined distance; and

determine an autonomous steering action for the vehicle based on the estimated offset to correct the position of the vehicle.

14. The non-transitory, computer-readable medium of claim 13, wherein the predetermined road model trajectory includes a three-dimensional polynomial representation of a target trajectory along the road segment.

15. The non-transitory, computer-readable medium of claim 13, further storing instructions to adjust a steering system of the vehicle based on the autonomous steering action.

16. The non-transitory, computer-readable medium of claim 13, wherein the instructions to determine the estimated offset further include instructions to determine, based on the distance to the at least one lane marking, whether the vehicle is on a trajectory that will intersect the at least one lane marking.

17. The non-transitory, computer-readable medium of claim 13, wherein the instructions to determine the estimated offset further include instructions to determine, based on the distance to the at least one lane marking, whether the vehicle is within a predetermined threshold of the at least one lane marking.

18. The non-transitory, computer-readable medium of claim 13, wherein the instructions to determine the autonomous steering action for the vehicle further include instructions to solve for at least one derivative of the predetermined road model trajectory.