AUTONOMOUS VEHICLE DETECTION OF AND RESPONSE TO YIELD SCENARIOS

• US 20160161270A1
• Filed: 12/09/2014
• Published: 06/09/2016
• Est. Priority Date: 12/09/2014
• Status: Active Grant

• Current Assignee: Toyota Jidosha Kabushiki Kaisha (Toyota Motor Corporation)
• Original Assignee: Toyota Motor Engineering & Manufacturing North America Incorporated (Toyota Motor Corporation)
• Inventors: Okumura, Bunyo
• Granted Patent: US 9,534,910 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B60W 2552/05 Type of road, e.g. motorways, local streets, paved or unpaved roads
• CPC Class Codes: B60W 2554/00 Input parameters relating to objects
• CPC Class Codes: B60W 2554/4026 Cycles
• CPC Class Codes: B60W 2554/4029 Pedestrians
• CPC Class Codes: B60W 2554/4041 Position
• CPC Class Codes: B60W 2554/406 Traffic density
• CPC Class Codes: B60W 2554/80 Spatial relation or speed relative to objects
• 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 30/181 Preparing for stopping
• CPC Class Codes: B60W 30/18154 Approaching an intersection
• CPC Class Codes: B60W 30/18163 Lane change; Overtaking manoeuvres
• CPC Class Codes: B60W 60/0015 specially adapted for safety
• CPC Class Codes: G01C 21/34 Route searching; Route guidance
• CPC Class Codes: G05D 1/0246 using a video camera in combination with image processing means
• CPC Class Codes: G05D 1/0289 with means for avoiding collisions between vehicles vehicle fittings for automatically controlling speed including means for detecting potential obstacles B60K31/0008; avoiding obstacles by action on the steering system B62D; radar, sonar, lidar systems designed for anti-collision purposes G01S13/93, G01S15/93, G01S17/93
• CPC Class Codes: G06V 20/54 of traffic, e.g. cars on the road, trains or boats
• 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: G08G 1/09626 where the origin of the information is within the own vehicle, e.g. a local storage device, digital map
• CPC Class Codes: G08G 1/096725 where the received information generates an automatic action on the vehicle control
• CPC Class Codes: G08G 1/09675 : where a selection from the received information takes place in the vehicle
• CPC Class Codes: G08G 1/096775 : where the origin of the information is a central station
• CPC Class Codes: G08G 1/165 : for passive traffic, e.g. including static obstacles, trees
• CPC Class Codes: G08G 1/166 : for active traffic, e.g. moving vehicles, pedestrians, bikes
• CPC Class Codes: G08G 1/167 : Driving aids for lane monitoring, lane changing, e.g. blind spot detection

Abstract

An automated driving system and methods are disclosed. The automated driving system includes a perception system disposed on an autonomous vehicle. The automated driving system can detect an intersection including a yield scenario and identify a check point between the autonomous vehicle and the yield scenario. Prior to the autonomous vehicle reaching the check point, the automated driving system can send a command to one or more vehicle systems to control the autonomous vehicle to stop at the yield scenario. After the autonomous vehicle reaches the check point, the automated driving system can detect, using the perception system, information for the intersection. If the information indicates clear passage through the intersection for the autonomous vehicle, the automated driving system can send a command to the one or more vehicle systems to drive the autonomous vehicle through the intersection.

Claims

1. An automated driving system, comprising:

a perception system disposed on an autonomous vehicle; and

a computing device in communication with the perception system, comprising;

one or more processors for controlling operations of the computing device; and

a memory for storing data and program instructions used by the one or more processors, wherein the one or more processors are configured to execute instructions stored in the memory to;

detect preliminary information for an intersection including a yield scenario;

identify a check point location between the autonomous vehicle and the yield scenario based on the preliminary information including at least one of traffic density information, an intersection type, an intersection configuration, or a presence of one or more obstacles that could at least partially obstruct a view of the intersection by the autonomous vehicle;

prior to the autonomous vehicle reaching the check point, send a command to one or more vehicle systems to control the autonomous vehicle to stop at the yield scenario;

after the autonomous vehicle reaches the check point, detect, using the perception system, updated information for the intersection; and

if the updated information indicates clear passage through the intersection for the autonomous vehicle, send a command to the one or more vehicle systems to drive the autonomous vehicle past the yield scenario and through the intersection.

2. The automated driving system of claim 1, wherein the yield scenario includes one of a yield sign, a red traffic light, a roundabout, and a lane merge.

5. The automated driving system of claim 1, wherein the updated information includes at least one of information regarding intersection obstacles and information regarding one or more neighboring vehicles.

6. The automated driving system of claim 5, wherein the information regarding the one or more neighboring vehicles includes at least one of position, velocity, acceleration, and deceleration for the one or more neighboring vehicles.

7. The automated driving system of claim 1, wherein the one or more processors are further configured to:

if the updated information does not indicate clear passage through the intersection for the autonomous vehicle, send a command to the one or more vehicle systems to stop the autonomous vehicle at the yield scenario.

22. The automated driving system of claim 1, wherein detecting the updated information for the intersection is performed regardless of the yield scenario.

3-4. -4. (canceled)

8. A computer-implemented method of automated driving, comprising:

detecting preliminary information for an intersection including a yield scenario;

identifying a check point location between an autonomous vehicle and the yield scenario based on the preliminary information including at least one of traffic density information, an intersection type, an intersection configuration, or a presence of one or more obstacles that could at least partially obstruct a view of the intersection by the autonomous vehicle;

prior to the autonomous vehicle reaching the check point, sending a command to one or more vehicle systems to control the autonomous vehicle to stop at the yield scenario;

after the autonomous vehicle reaches the check point, detecting, using a perception system disposed on the autonomous vehicle, updated information for the intersection; and

if the updated information indicates clear passage through the intersection for the autonomous vehicle, sending a command to the one or more vehicle systems to drive the autonomous vehicle past the yield scenario and through the intersection.

9. The method of claim 8, wherein the yield scenario includes one of a yield sign, a red traffic light, a roundabout, and a lane merge.

12. The method of claim 8, wherein the updated information includes at least one of information regarding intersection obstacles and information regarding one or more neighboring vehicles.

13. The method of claim 12, wherein the information regarding the one or more neighboring vehicles includes at least one of position, velocity, acceleration, and deceleration for the one or more neighboring vehicles.

14. The method of claim 8, further comprising:

if the updated information does not indicate clear passage through the intersection for the autonomous vehicle, send a command to the one or more vehicle systems to stop the autonomous vehicle at the yield scenario.

10-11. -11. (canceled)

15. A computing device, comprising:

one or more processors for controlling operations of the computing device; and

a memory for storing data and program instructions used by the one or more processors, wherein the one or more processors are configured to execute instructions stored in the memory to;

detect an intersection including a yield scenario;

identify a check point location between the autonomous vehicle and the yield scenario based on at least one of traffic density information, intersection type, intersection configuration, or a presence of one or more obstacles that could at least partially obstruct a view of the intersection by the autonomous vehicle;

prior to the autonomous vehicle reaching the check point, send a command to one or more vehicle systems to control the autonomous vehicle to stop at the yield scenario;

after the autonomous vehicle reaches the check point, detect, using the perception system, information for the intersection; and

if the information indicates clear passage through the intersection for the autonomous vehicle, send a command to the one or more vehicle systems to drive the autonomous vehicle through the intersection.

16. The computing device of claim 15, wherein the yield scenario includes one of a yield sign, a red traffic light, a roundabout, and a lane merge.

17. The computing device of claim 15, wherein the information for the intersection includes at least one of map-based information and information regarding intersection obstacles and information regarding one or more neighboring vehicles.

18. The computing device of claim 17, wherein the map-based information includes at least one of an intersection type and an intersection configuration.

19. The computing device of claim 17, wherein the information regarding the one or more neighboring vehicles includes at least one of position, velocity, acceleration, and deceleration for the one or more neighboring vehicles.

20. The computing device of claim 15, wherein the one or more processors are further configured to:

if the information does not indicate clear passage through the intersection for the autonomous vehicle, send a command to the one or more vehicle systems to stop the autonomous vehicle at the yield scenario.

21. An automated driving system, comprising:

a perception system disposed on an autonomous vehicle; and

a computing device in communication with the perception system, comprising;

one or more processors for controlling operations of the computing device; and

a memory for storing data and program instructions used by the one or more processors, wherein the one or more processors are configured to execute instructions stored in the memory to;

detect preliminary information for an intersection including a yield scenario;

identify a check point between the autonomous vehicle and the yield scenario based on the preliminary information;

prior to the autonomous vehicle reaching the check point, send a command to one or more vehicle systems to control the autonomous vehicle to stop at the yield scenario;

after the autonomous vehicle reaches the check point, detect, using the perception system, updated information for the intersection, wherein detecting the updated information for the intersection is performed regardless of the yield scenario; and

if the updated information indicates clear passage through the intersection for the autonomous vehicle, send a command to the one or more vehicle systems to drive the autonomous vehicle past the yield scenario and through the intersection.