METHOD OF GENERATING OPTIMUM PARKING PATH OF UNMANNED DRIVING VEHICLE, AND UNMANNED DRIVING VEHICLE ADOPTING THE METHOD

• US 20150134185A1
• Filed: 05/13/2014
• Published: 05/14/2015
• Est. Priority Date: 11/08/2013
• Status: Active Grant

• Current Assignee: Hanwha Aerospace Co., Ltd. (Hanwha Corporation)
• Original Assignee: Samsung Techwin Corporation (Hanwha Corporation)
• Inventors: LEE, Jin Han
• Granted Patent: US 9,254,870 B2
• Time in Patent Office: Days
• US Class Current: 701/26
• CPC Class Codes: B62D 15/0285 Parking performed automatically
• CPC Class Codes: G05D 1/0214 in accordance with safety or protection criteria, e.g. avoiding hazardous areas monitoring the location of vehicles within a certain area, e.g. forbidden or allowed areas, in traffic control systems for road vehicles G08G1/13

Abstract

A method of generating an optimum parking path of an unmanned driving vehicle which is performed by a controller in the unmanned driving vehicle, wherein the controller changes a moving distance for a plurality of operations in a reference parking path, finds a parking path in which an average obstacle distance, which is an average distance between at least one near-to-path obstacle and the unmanned driving vehicle, is longest among a plurality of candidate parking paths, and sets the parking path having the longest average obstacle distance, as an optimum parking path in response to the longest average obstacle distance being longer than a predetermined limited distance.

Claims

1. A method of generating an optimum parking path of an unmanned driving vehicle, which is performed by a controller in the unmanned driving vehicle, the method comprising:

generating a reference parking path by selectively combining a plurality of operations which comprise head-in straight driving, head-out straight driving, head-in left turning, head-out left turning, head-in right turning, and head-out right turning;

changing a moving distance in the reference parking path to find a parking path in which an average obstacle distance, which is an average distance between at least one near-to-path obstacle and the unmanned driving vehicle, is longest among a plurality of candidate parking paths; and

setting the parking path having the longest average obstacle distance, as the optimum parking path in response to the longest average obstacle distance being longer than a predetermined limited distance.

2. The method of claim 1, wherein the reference parking path is generated as a shortest-distance path among the plurality of candidate parking paths when the near-to-path obstacle is assumed to not be present.

3. The method of claim 1, wherein, in the generating the reference parking path and the changing the moving distance, a same rotational angle δ

is applied to the head-in left turning, the head-out left turning, the head-in right turning, and the head-out right turning.

4. The method of claim 3, wherein the unmanned driving vehicle comprises two front wheels and two rear wheels, and

wherein in the changing the moving distance, when the unmanned driving vehicle is assumed to move through each of the parking paths, in response to the unmanned driving vehicle virtually moving, a unit movement distance, and

calculating an X-axis coordinate, a Y-axis coordinate, and a directed angle of orientation of a center point between the two rear wheels of the unmanned driving vehicle.

5. The method of claim 4, wherein in the changing the moving distance, in response to the center point between the two rear wheels being rotationally moved from a first X-axis coordinate x1, a first Y-axis coordinate y1, and a first directed angle of orientation θ

1 to a second X-axis coordinate x2, a second Y-axis coordinate y2, and a second directed angle of orientation θ

2, according to one operation from among the head-in left turning, the head-out left turning, the head-in right turning, and the head-out right turning,

the second X-axis coordinate x2, the second Y-axis coordinate y2, and the second directed angle of orientation θ

2 are calculated using a virtual circle that is obtained by rotationally moving the unmanned driving vehicle by the rotational angle δ

.

6. The method of claim 1, wherein the changing the moving distance further comprises:

obtaining the average distance between the at least one near-to-path obstacle and the unmanned driving vehicle in one parking path,

wherein the obtaining the average distance between the at least one near-to-path obstacle and the unmanned driving vehicle in one parking path comprises;

calculating a shortest distance between the at least one near-to-path obstacle and the unmanned driving vehicle in respective positions when assuming that the positions of the unmanned driving vehicle are disposed to overlap each other along the parking path;

totaling results of the calculated shortest distance, and setting a value which is obtained by the totaling of the results as the average distance.

7. The method of claim 6, wherein in the calculating the shortest distance between the at least one near-to-path obstacle and the unmanned driving vehicle when assuming that the positions of the unmanned driving vehicle are disposed to overlap each other along the parking path,

the shortest distance has a negative value and is a shortest distance between an outer surface of the unmanned driving vehicle and the at least one near-to-path obstacle in response to the at least one near-to-path obstacle being present inside the unmanned driving vehicle in a location.

8. The method of claim 1, wherein the changing the moving distance comprises:

calculating a reference average obstacle distance, which is an average distance between the at least one near-to-path obstacle and the unmanned driving vehicle in the reference parking path;

changing respective moving distances in the reference parking path,

calculating a first average obstacle distance which is the first average distance between the at least one near-to-path obstacle and the unmanned driving vehicle such that a first parking path is found in which the first average obstacle distance is longer than the reference average obstacle distance; and

setting the first parking path as the parking path having the longest average obstacle distance in response to a difference between the reference average obstacle distance and the first average obstacle distance being less than a set convergence distance.

9. The method of claim 8, wherein the changing the moving distance comprises:

setting the first parking path as a new reference parking path in response to a difference between the reference average obstacle distance and the first average obstacle distance being not less than the set convergence distance; and

performing the calculating the reference average obstacle distance, the changing respective moving distances in the reference parking path, the setting the first parking path as the parking path having the longest average obstacle distance, and the setting the first parking path as the new reference parking path using the new reference parking path as the reference parking path.

10. The method of claim 9, wherein additional conditions for finding the first parking path in the changing respective moving distances in the reference parking path are used such that

a deviation between a X-axis coordinate of the unmanned driving vehicle at a virtual arrival location and a X-axis coordinate of the unmanned driving vehicle at a target arrival location is less than a X set limit value,

a deviation between a Y-axis coordinate of the unmanned driving vehicle at the virtual arrival location and a Y-axis coordinate of the unmanned driving vehicle at the target arrival location is less than a Y set limit value, and

a deviation between a directed angle of orientation of the unmanned driving vehicle at the virtual arrival location and a directed angle of orientation of the unmanned driving vehicle at the target arrival location is less than a directed angle set limit value.

11. The method of claim 9, wherein the changing respective moving distances in the reference parking path comprises:

calculating a reduced average obstacle distance in a reduced path among the plurality of candidate parking paths, which is a reduced average distance between the at least one near-to-path obstacle and the unmanned driving vehicle in the reduced path, wherein the reduced path is obtained as a result of reducing respective moving distances in the reference parking path by a reference set distance;

calculating an extended average obstacle distance in an extended path among the plurality of candidate parking paths, which is an extended average distance between the at least one near-to-path obstacle and the unmanned driving vehicle in the extended path, wherein the extended path is obtained as a result of extending respective moving distances in the reference parking path by the reference set distance;

changing the respective moving distances based on a result of comparing the reduced average obstacle distance in the reduced path to the extended average obstacle distance in the extended path; and

calculating the first average obstacle distance, which is the first average distance between the at least one near-to-path obstacle and the unmanned driving vehicle such that the first parking path is found in which the first average obstacle distance is longer than the reference average obstacle distance.

12. The method of claim 11, wherein in the changing respective moving distances the respective moving distances in the reduced path is reduced in response to the reduced average obstacle distance in the reduced path being longer than the extended average obstacle distance in the extended path;

calculating the first average obstacle distance, which is the first average distance between the at least one near-to-path obstacle and the unmanned driving vehicle such that the first parking path is found in which the first average obstacle distance is longer than the reference average obstacle distance in response to the respective moving distances in the reduced path being reduced.

13. The method of claim 12, wherein in the changing respective moving distances, a rate of reducing the moving distance is proportional to a difference between the reduced average obstacle distance in the reduced path and the extended average obstacle distance in the extended path in response to respective moving distances being reduced in the reduced path.

14. The method of claim 11, wherein in the changing respective moving distances, in response to the extended average obstacle distance in the extended path being longer than the reduced average obstacle distance in the reduced path, the respective moving distances in the extended path are extended,

calculating the first average obstacle distance, which is the first average distance between the at least one near-to-path obstacle and the unmanned driving vehicle, such that the first parking path is found, in which the first average obstacle distance is longer than the reference average obstacle distance.

15. The method of claim 14, wherein in the changing respective moving distances, a rate of extending the moving distance is proportional to a difference between the reduced average obstacle distance in the reduced path and the extended average obstacle distance in the extended path in response to respective moving distances being extended in the extended path.

16. An unmanned driving vehicle for generating an optimum parking path, the unmanned driving vehicle comprises:

a controller which is configured to execute;

generating a reference parking path by selectively combining a plurality of operations which comprise head-in straight driving, head-out straight driving, head-in left turning, head-out left turning, head-in right turning, and head-out right turning;

changing a moving distance in the reference parking path to find a parking path in which an average obstacle distance, which is an average distance between at least one near-to-path obstacle and the unmanned driving vehicle, is longest among a plurality of candidate parking paths; and

setting the parking path having the longest average obstacle distance, as an optimum parking path, in response to the longest average obstacle distance being longer than a predetermined limited distance,

wherein the unmanned driving vehicle performs a parking operation.

17. The unmanned driving vehicle of claim 16, wherein the controller is configured to apply a same rotational angle δ

to the head-in left turning, the head-out left turning, the head-in right turning, and the head-out right turning.

18. The unmanned driving vehicle of claim 17, wherein the unmanned driving vehicle comprises two front wheels and two rear wheels, and

wherein when the controller assumes that the unmanned driving vehicle moves through the parking path and the unmanned driving vehicle virtually moves a unit movement distance, the controller is configured to calculate an X-axis coordinate, a Y-axis coordinate, and a directed angle of orientation of a center point between the two rear wheels of the unmanned driving vehicle.

19. The unmanned driving vehicle of claim 16, wherein, in order to obtain the average distance between the at least one near-to-path obstacle and the unmanned driving vehicle in the parking path, the controller is configured to calculate a shortest distance between the at least one near-to-path obstacle and the unmanned driving vehicle in respective locations when assuming that positions of the unmanned driving vehicle are disposed to overlap with each other along the parking path, and total results of the calculated shortest distance, and set a value that is obtained by the totaling of the results as the average distance.

20. A method of generating an optimum parking path of an unmanned driving vehicle, the method comprising:

receiving a parking command signal;

generating a reference parking path by combining a plurality of parking operations which comprise head-in straight driving, head-out straight driving, head-in left turning, head-out left turning, head-in right turning, and head-out right turning in response to the received parking command signal; and

changing a moving distance in the reference parking path to find a parking path in which an average obstacle distance between at least one near-to-path obstacle and the unmanned driving vehicle is longest among a plurality of candidate parking paths.

21. The method of claim 20, further comprising:

setting the parking path as the optimum parking path in response to the longest average obstacle distance being longer than a predetermined limited distance.

22. The method of claim 21, further comprising:

performing a parking operation of the unmanned driving vehicle using the optimum parking path.

23. The method of claim 20, further comprising:

transmitting a signal which comprises information informing that a parking operation of the unmanned driving vehicle is impossible in response to the longest average obstacle distance being shorter than a predetermined limited distance.