Prioritized constraints for a navigational system

• US 10,591,929 B2
• Filed: 06/06/2019
• Issued: 03/17/2020
• Est. Priority Date: 01/05/2016
• Status: Active Grant

• Current Assignee: MobilEye Vision Technologies Ltd. (Intel Corporation)
• Original Assignee: MobilEye Vision Technologies Ltd. (Intel Corporation)
• Inventors: Shalev-Shwartz, Shai, Shashua, Amnon, Shammah, Shaked
• Primary Examiner(s): Kan, Yuri
• Application Number:
  US16/433,824
• Publication Number:
  US 20190286154A1
• Time in Patent Office: 285 Days
• CPC Class Codes: B60W 2050/0088 Adaptive recalibration
• CPC Class Codes: B60W 2420/403 Image sensing, e.g. optical camera
• CPC Class Codes: B60W 2520/16 Pitch
• CPC Class Codes: B60W 2520/18 Roll
• CPC Class Codes: B60W 2552/15 Road slope, i.e. the inclination of a road segment in the longitudinal direction
• CPC Class Codes: B60W 2552/30 Road curve radius
• CPC Class Codes: B60W 2552/53 Road markings, e.g. lane marker or crosswalk
• CPC Class Codes: B60W 2554/00 Input parameters relating to objects
• CPC Class Codes: B60W 2554/20 Static objects
• CPC Class Codes: B60W 2554/4029 Pedestrians
• CPC Class Codes: B60W 2554/4046 Behavior, e.g. aggressive or erratic
• CPC Class Codes: B60W 2554/802 Longitudinal distance
• CPC Class Codes: B60W 2554/804 Relative longitudinal speed
• CPC Class Codes: B60W 30/09 Taking automatic action to avoid collision, e.g. braking and steering
• CPC Class Codes: B60W 30/0953 the prediction being responsive to vehicle dynamic parameters
• CPC Class Codes: B60W 30/0956 the prediction being responsive to traffic or environmental parameters
• CPC Class Codes: B60W 30/18163 Lane change; Overtaking manoeuvres
• CPC Class Codes: B60W 50/0097 Predicting future conditions
• CPC Class Codes: B60W 50/045 Monitoring control system parameters
• CPC Class Codes: B60W 60/0011 involving control alternatives for a single driving scenario, e.g. planning several paths to avoid obstacles
• CPC Class Codes: B60W 60/00276 : for two or more other traffic participants
• CPC Class Codes: G01C 21/34 : Route searching; Route guidance
• CPC Class Codes: G01C 21/3453 : Special cost functions, i.e. other than distance or default speed limit of road segments
• 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: G05D 1/0055 : with safety arrangements
• CPC Class Codes: G05D 1/0231 : using optical position detecting means position-fixing by using electromagnetic waves other than radio waves, e.g. optical position detecting means G01S5/16
• CPC Class Codes: G05D 1/0246 : using a video camera in combination with image processing means
• 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: G06N 20/00 : Machine learning
• CPC Class Codes: G06N 3/00 : Computing arrangements based on biological models
• CPC Class Codes: G06N 3/006 : based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
• CPC Class Codes: G06N 3/044 : Recurrent networks, e.g. Hopfield networks
• CPC Class Codes: G06N 3/08 : Learning methods
• CPC Class Codes: G06N 5/046 : Forward inferencing; Production systems
• CPC Class Codes: G06N 7/01 : Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G06V 20/56 : exterior to a vehicle by using sensors mounted on the vehicle
• CPC Class Codes: G06V 20/58 : Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
• 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

Abstract

A navigation system for a host vehicle is provided. The system may comprise at least one processing device programmed to receive, from a camera, a plurality of images representative of an environment of the host vehicle; analyze the plurality of images to identify a navigational state associated with the host vehicle; determine a first predefined navigational constraint and a second predefined navigational constraint implicated by the navigational state; determine, based on the identified navigational state, a first navigational action for the host vehicle where both the first predefined navigational constraint and the second predefined navigational constraint can be satisfied; determine, based on the identified navigational state, a second navigational action for the host vehicle where the first predefined navigational constraint and the second predefined navigational constraint cannot both be satisfied; and cause at least one adjustment of a navigational actuator of the host vehicle.

Claims

1. A navigation system for a host vehicle, the system comprising:

at least one processing device programmed to;

receive, from a camera, a plurality of images representative of an environment of the host vehicle;

analyze the plurality of images to determine a navigational state associated with the host vehicle, the navigational state being associated with sensed information associated with the environment of the host vehicle;

determine a first predefined navigational constraint and a second predefined navigational constraint implicated by the navigational state, wherein the first predefined navigational constraint differs from the second predefined navigational constraint, and wherein the second predefined navigational constraint has a priority higher than the first predefined navigational constraint;

determine, based on the identified navigational state, a first navigational action for the host vehicle satisfying both the first predefined navigational constraint and the second predefined navigational constraint where both the first predefined navigational constraint and the second predefined navigational constraint can be satisfied;

determine, based on the identified navigational state, a second navigational action for the host vehicle satisfying the second predefined navigational constraint, but not satisfying the first predefined navigational constraint, where the first predefined navigational constraint and the second predefined navigational constraint cannot both be satisfied; and

cause at least one adjustment of a navigational actuator of the host vehicle in response to the determined first navigational action or the determined second navigational action for the host vehicle.

2. The navigation system of claim 1, wherein determination of the second navigational action occurs in a trained navigational system.

3. The navigation system of claim 1, wherein the first predefined navigational constraint includes a target vehicle envelope defining a first buffer zone within which navigation of the host vehicle is prohibited, and wherein the second predefined navigational constraint includes a pedestrian envelope defining a second buffer zone within which navigation of the host vehicle is prohibited.

4. The navigation system of claim 3, wherein at least a portion of the first buffer zone extends a predetermined distance from a detected target vehicle.

5. The navigation system of claim 3, wherein at least a portion of the second buffer zone extends a predetermined distance from a detected pedestrian.

6. The navigation system of claim 1, wherein the first predefined navigational constraint includes at least one of a stationary object envelope, a road barrier buffer zone, a maximum speed of travel when passing within an influence zone of a detected pedestrian, or a maximum deceleration rate for the host vehicle, and wherein the second predefined navigational constraint includes at least one of a target vehicle envelope or a pedestrian envelope.

7. The navigation system of claim 1, wherein the navigational actuator includes at least one of a steering mechanism, a brake, or an accelerator.

8. An autonomous vehicle, the autonomous vehicle comprising:

a frame;

a body attached to the frame;

a camera; and

a navigation system, the navigation system comprising;

at least one processing device programmed to;

receive, from a camera, a plurality of images representative of an environment of the autonomous vehicle;

analyze the plurality of images to determine a navigational state associated with the autonomous vehicle, the navigational state being associated with sensed information associated with the environment of the host vehicle;

determine a first predefined navigational constraint and a second predefined navigational constraint implicated by the navigational state, wherein the first predefined navigational constraint differs from the second predefined navigational constraint, and wherein the second predefined navigational constraint has a priority higher than the first predefined navigational constraint;

determine, based on the identified navigational state, a first navigational action for the autonomous vehicle satisfying both the first predefined navigational constraint and the second predefined navigational constraint where both the first predefined navigational constraint and the second predefined navigational constraint can be satisfied;

determine, based on the identified navigational state, a second navigational action for the autonomous vehicle satisfying the second predefined navigational constraint, but not satisfying the first predefined navigational constraint, where the first predefined navigational constraint and the second predefined navigational constraint cannot both be satisfied; and

cause at least one adjustment of a navigational actuator of the autonomous vehicle in response to the determined first navigational action or the determined second navigational action for the autonomous vehicle.

9. The autonomous vehicle of claim 8, wherein determination of the second navigational action occurs in a trained navigational system.

10. The autonomous vehicle of claim 8, wherein the first predefined navigational constraint includes a target vehicle envelope defining a first buffer zone within which navigation of the autonomous vehicle is prohibited, and wherein the second predefined navigational constraint includes a pedestrian envelope defining a second buffer zone within which navigation of the autonomous vehicle is prohibited.

11. The autonomous vehicle of claim 10, wherein at least a portion of the first buffer zone extends a predetermined distance from a detected target vehicle.

12. The autonomous vehicle of claim 10, wherein at least a portion of the second buffer zone extends a predetermined distance from a detected pedestrian.

13. The autonomous vehicle of claim 8, wherein the first predefined navigational constraint includes at least one of a stationary object envelope, a road barrier buffer zone, a maximum speed of travel when passing within an influence zone of a detected pedestrian, or a maximum deceleration rate for the autonomous vehicle, and wherein the second predefined navigational constraint includes at least one of a target vehicle envelope or a pedestrian envelope.

14. The autonomous vehicle of claim 8, wherein the navigational actuator includes at least one of a steering mechanism, a brake, or an accelerator.

15. A method of navigating an autonomous vehicle, the method comprising:

receiving, from a camera, a plurality of images representative of an environment of the autonomous vehicle;

analyzing the plurality of images to determine a navigational state associated with the autonomous vehicle, the navigational state being associated with sensed information associated with the environment of the host vehicle;

determining a first predefined navigational constraint and a second predefined navigational constraint implicated by the navigational state, wherein the first predefined navigational constraint differs from the second predefined navigational constraint, and wherein the second predefined navigational constraint has a priority higher than the first predefined navigational constraint;

determining, based on the identified navigational state, a first navigational action for the autonomous vehicle satisfying both the first predefined navigational constraint and the second predefined navigational constraint where both the first predefined navigational constraint and the second predefined navigational constraint can be satisfied;

determining, based on the identified navigational state, a second navigational action for the autonomous vehicle satisfying the second predefined navigational constraint, but not satisfying the first predefined navigational constraint, where the first predefined navigational constraint and the second predefined navigational constraint cannot both be satisfied; and

causing at least one adjustment of a navigational actuator of the autonomous vehicle in response to the determined first navigational action or the determined second navigational action for the autonomous vehicle.