Mapping active and inactive construction zones for autonomous driving

• US 10,317,906 B2
• Filed: 12/06/2016
• Issued: 06/11/2019
• Est. Priority Date: 04/10/2013
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Waymo LLC (Alphabet Inc.)
• Inventors: Ferguson, David I., Burnette, Donald Jason
• Primary Examiner(s): Berona, Kimberly S
• Assistant Examiner(s): Malhotra, Sanjeev
• Application Number:
  US15/370,361
• Publication Number:
  US 20170176996A1
• Time in Patent Office: 917 Days
• Field of Search: 701 26, 701 28, 701 314, 701 36, 701456, 701 50, 701465, 382199, 348118, 345418, 340901, 4060602
• CPC Class Codes: B60W 10/04 including control of propulsion units
• CPC Class Codes: B60W 10/20 including control of steering systems
• CPC Class Codes: B60W 2710/20 Steering systems
• CPC Class Codes: B60W 2720/106 Longitudinal acceleration
• CPC Class Codes: B60W 30/00 Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
• CPC Class Codes: B60W 30/143 Speed control B60W30/16 takes precedence
• CPC Class Codes: B60W 60/00184 related to infrastructure
• CPC Class Codes: B60W 60/0053 from vehicle to occupant
• CPC Class Codes: G01C 21/26 specially adapted for navigation in a road network
• CPC Class Codes: G01C 21/3407 specially adapted for specific applications
• CPC Class Codes: G01C 21/3815 Road data
• CPC Class Codes: G01S 19/42 Determining position
• CPC Class Codes: G01S 2013/9316 combined with communication equipment with other vehicles or with base stations
• CPC Class Codes: G05D 1/00 Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots drive control systems specially adapted for autonomous road vehicles B60W60/00
• CPC Class Codes: G05D 1/0236 in combination with a laser lasers per se H01S
• CPC Class Codes: G05D 1/0246 using a video camera in combination with image processing means
• CPC Class Codes: G05D 1/0255 using acoustic signals, e.g. ultra-sonic singals sonar systems designed for anti-collision purposes G01S15/93
• CPC Class Codes: G05D 1/0257 using a radar radar systems designed for anti-collision purposes between land vehicles or between land vehicle and fixed obstacles G01S13/931
• CPC Class Codes: G05D 1/0276 using signals provided by a source external to the vehicle involving a plurality of vehicles G05D1/0287; automatically controlling vehicle speed responsive to externally generated signals B60K31/0058
• CPC Class Codes: G06V 20/582 of traffic signs
• 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

Aspects of the present disclosure relate to differentiating between active and inactive construction zones. In one example, this may include identifying a construction object associated with a construction zone. The identified construction object may be used to map the area of the construction zone. Detailed map information may then be used to classify the activity of the construction zone. The area of the construction zone and the classification may be added to the detailed map information. Subsequent to adding the construction zone and the classification to the detailed map information, the construction object (or another construction object) may be identified. The location of the construction object may be used to identify the construction zone and classification from the detailed map information. The classification of the classification may be used to operate a vehicle having an autonomous mode.

Claims

1. A method comprising:

accessing map information identifying a roadway;

detecting one or more construction objects;

defining, in response to detecting one or more construction objects and using one or more processors, an area along the roadway as a construction zone based at least in part on the one or more construction objects;

detecting a feature of the construction zone;

classifying, using the one or more processors, the construction zone as active or inactive based on whether the feature is different from the map information;

storing, using the one or more processors, the classification of the construction zone in the map information; and

autonomously driving a vehicle more cautiously through the construction zone when the construction zone is classified as active than when the construction zone is classified as inactive.

2. The method of claim 1 wherein classifying the construction zone comprises classifying the construction zone as inactive when there are no differences or minor differences between the feature and the map information.

3. The method of claim 2 wherein a difference between the feature and the map information is a minor difference when the difference would not affect autonomous driving.

4. The method of claim 3 wherein the minor difference comprises a change outside of lanes of the roadway.

5. The method of claim 1 further comprising sending the classification to a second vehicle.

6. The method of claim 5 further comprising autonomously driving the second vehicle more cautiously through the construction zone when the construction zone is classified as active.

7. The method of claim 1 wherein detecting a feature comprises detecting a position of a lane and wherein the construction zone is classified as active when a position of a lane stored in the map information is different from the detected position of the lane.

8. The method of claim 1 wherein autonomously driving a vehicle more cautiously through the construction zone comprises driving the vehicle more slowly.

9. The method of claim 1 autonomously driving a vehicle more cautiously through the construction zone comprises increasing a distance between the vehicle and objects in the roadway.

18. The vehicle of claim 15 wherein the instructions further comprise method of claim 1 further sending the classification to a different vehicle.

19. The vehicle of claim 18 wherein sending the classification to the different vehicle comprises broadcasting the classification to the different vehicle.

20. The vehicle of claim 18 wherein sending the classification to the different vehicle comprises sending the classification to a server and the server relaying the classification to the different vehicle.

10. A system comprising:

one or more processors; and

memory storing instructions and map information, the instructions being executable by the one or more computing devices, the map information identifying a roadway;

wherein the instructions comprise;

receiving sensor data collected by a first vehicle;

detecting one or more construction objects based on the sensor data;

defining, in response to detecting one or more construction objects and using one or more processors, an area along the roadway as a construction zone based at least in part on the one or more construction objects;

detecting a feature of the construction zone;

classifying, using the one or more processors, the construction zone as active or inactive based on whether the feature is different from the map information; and

sending the classification of the construction zone to a second vehicle for use by the second vehicle when the second vehicle is in an autonomous driving mode.

11. The system of claim 10 wherein sending the classification to the second vehicle comprises the first vehicle broadcasting the classification to the second vehicle.

12. The system of claim 10 wherein sending the classification to the second vehicle comprises the first vehicle sending the classification to a server and the server relaying the classification to the second vehicle.

13. The system of claim 10 wherein the instructions further comprise autonomously driving the second vehicle more cautiously through the construction zone when the construction zone is classified as active.

14. The system of claim 10 wherein the instructions further comprise storing the classification in the map information.

15. A vehicle comprising:

an acceleration system;

a sensor;

one or more processors in communication with the acceleration system; and

memory storing instructions and map information, the instructions being executable by the one or more computing devices, the map information identifying a roadway;

wherein the instructions comprise;

detecting one or more construction objects;

defining, in response to detecting one or more construction objects and using one or more processors, an area along the roadway as a construction zone based at least in part on the one or more construction objects;

detecting a feature of the construction zone;

classifying, using the one or more processors, the construction zone as active or inactive based on whether the feature is different from the map information; and

autonomously operating the acceleration system based on the classification of the construction zone.

16. The vehicle of claim 15 wherein autonomously operating the acceleration system based on the classification of the construction zone comprises autonomously driving the vehicle more cautiously through the construction zone when the construction zone is classified as active than when the construction zone is classified as inactive.

17. The vehicle of claim 15 wherein autonomously operating the acceleration system based on the classification of the construction zone comprises autonomously driving the vehicle more slowly through the construction zone when the construction zone is classified as active than when the construction zone is classified as inactive.