Driving path planning apparatus and method for autonomous vehicle

• US 9,718,466 B2
• Filed: 08/24/2015
• Issued: 08/01/2017
• Est. Priority Date: 11/12/2014
• Status: Active Grant

• Current Assignee: Hyundai Motor Company (Hyundai Motor Group)
• Original Assignee: Hyundai Motor Company (Hyundai Motor Group)
• Inventors: Yoo, Su Jung, Shin, Min Yong, Kim, Hoi Won, Lee, Kyoung Jun
• Primary Examiner(s): Trivedi, Atul
• Application Number:
  US14/834,213
• Publication Number:
  US 20160129907A1
• Time in Patent Office: 708 Days
• Field of Search: 701 26
• CPC Class Codes: B60K 2360/175 Autonomous driving
• CPC Class Codes: B60K 35/28 characterised by the type of the output information, e.g. video entertainment or vehicle dynamics information; characterised by the purpose of the output information, e.g. for attracting the attention of the driver
• CPC Class Codes: B60W 2520/10 Longitudinal speed
• CPC Class Codes: B60W 2552/00 Input parameters relating to infrastructure
• 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 2554/80 Spatial relation or speed relative to objects
• CPC Class Codes: B60W 2554/801 Lateral distance
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 30/09 Taking automatic action to avoid collision, e.g. braking and steering
• CPC Class Codes: B60W 30/12 Lane keeping
• CPC Class Codes: B60W 30/14 Adaptive cruise control
• CPC Class Codes: B60W 30/16 Control of distance between vehicles, e.g. keeping a distance to preceding vehicle
• 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: G05D 1/0223 involving speed control of the vehicle vehicle fittings for automatically controlling, i.e. preventing speed from exceeding an arbitrarily established velocity or maintaining speed at a particular velocity, as selected by the vehicle operator B60K31/00
• CPC Class Codes: G05D 1/0246 using a video camera in combination with image processing means
• 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 20/588 Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
• CPC Class Codes: G08G 1/165 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

A driving path planning apparatus for an autonomous vehicle includes a driving information obtainer to obtain crossroad information, current velocity, and velocity setting of the vehicle. A global path planner plans a base frame, and an environment recognizer recognizes obstacle on a path and lane information of the vehicle. The apparatus also includes a velocity profile generator to generate a velocity profile for the vehicle, using current velocity and velocity setting, a candidate path planner to plan candidate paths for the vehicle, using velocity profile and base frame, and a path selector to check whether or not the candidate paths have collision risks and select one candidate path of the candidate paths as a driving path for the autonomous vehicle.

Claims

1. A driving path planning apparatus for an autonomous vehicle, the driving path planning apparatus comprising a processor configured to perform steps of:

obtaining crossroad information, current velocity, and velocity setting of the autonomous vehicle;

planning a base frame;

recognizing an obstacle on a path and lane information of the autonomous vehicle;

generating a velocity profile for the autonomous vehicle, using the current velocity and the velocity setting;

planning one or more candidate paths for the autonomous vehicle, using the velocity profile and the base frame;

checking whether or not the one or more candidate paths have collision risks; and

selecting one candidate path of the one or more candidate paths as a driving path for the autonomous vehicle, based on a checked result,

wherein the processor plans the one or more candidate paths for each longitudinal velocity of the autonomous vehicle based on the current velocity by taking account of variation in velocity of the autonomous vehicle when the one or more candidate paths have collision risks.

2. The driving path planning apparatus according to claim 1, wherein the processor generates a virtual target when the autonomous vehicle enters within a predetermined distance from a crossroad, based on the crossroad information.

3. The driving path planning apparatus according to claim 2, wherein the processor generates the virtual target, which is in a stopped state, at a point spaced apart from the autonomous vehicle by a distance obtained by adding a distance between the autonomous vehicle and the crossroad and a spare distance.

4. The driving path planning apparatus according to claim 3, wherein the spare distance is a distance between the autonomous vehicle and a preceding vehicle at the time of a longitudinal control.

5. The driving path planning apparatus according to claim 1, wherein the processor generates a longitudinal acceleration and deceleration profile for the autonomous vehicle, using velocity of the autonomous vehicle at the time of starting at a starting point on the path and velocity of the autonomous vehicle at the time of arriving at a destination, and wherein the velocity profile generator generates the velocity profile based on the longitudinal acceleration and deceleration profile.

6. The driving path planning apparatus according to claim 5, wherein the longitudinal acceleration and deceleration profile is an acceleration profile when acceleration is constant.

7. The driving path planning apparatus according to claim 5, wherein the longitudinal acceleration and deceleration profile is an acceleration profile when a rate of change of acceleration is constant.

8. The driving path planning apparatus according to claim 1, wherein the processor selects a candidate path for the autonomous vehicle, of which driving cost is minimal based on a cost function.

9. The driving path planning apparatus according to claim 1, wherein the processor checks whether or not the one or more candidate paths have collision risk and selects the driving path among the one or more candidate paths when the one or more candidate paths have collision risk.

10. The driving path planning apparatus according to claim 9, wherein the processor selects the driving path by taking account of a degree of collision risk, driving stability, and target path proximity.

11. The driving path planning apparatus according to claim 1, wherein the processor selects the driving path among candidate paths that do not have collision risk when some of the one or more candidate paths do not have collision risk.

12. The driving path planning apparatus according to claim 11, wherein the processor selects the driving path by taking account of driving stability and target path proximity.

13. A driving path planning method for an autonomous vehicle, the driving path planning method comprising:

checking, by a processor, whether or not the autonomous vehicle is in a lane change mode;

planning, by the processor, one or more candidate paths by taking account of current velocity of the autonomous vehicle within a current lane and a lane to be changed, when the autonomous vehicle is in the lane change mode;

checking, by the processor, whether or not the one or more candidate paths planned by taking account of the current velocity have collision risk;

planning, by the processor, one or more candidate paths for each longitudinal velocity of the autonomous vehicle based on the current velocity by taking account of variation in velocity of the autonomous vehicle when the one or more candidate paths planned by taking account of the current velocity have collision risk;

checking, by the processor, whether the one or more candidate paths for each longitudinal velocity have collision risk; and

selecting, by the processor, a candidate path from the one or more candidate paths as a driving path when the one or more candidate paths for each longitudinal velocity have collision risk.

14. The driving path planning method according to claim 13, wherein when the one or more the candidate paths do not have collision risk, a candidate path of the candidate paths that do not have collision risk is selected as the driving path.

15. The driving path planning method according to claim 14, wherein the driving path is selected by taking account of a degree of collision risk, driving stability, and target path proximity.

16. The driving path planning method according to claim 13, further comprising planning the candidate paths by taking account of velocity setting within the current lane when the autonomous vehicle is not in the lane change mode.