Method for safely parking vehicle near obstacles

• US 8,571,722 B2
• Filed: 10/22/2010
• Issued: 10/29/2013
• Est. Priority Date: 10/22/2010
• 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: Samples, Michael Edward, James, Michael Robert
• Primary Examiner(s): Badii, Behrang
• Application Number:
  US12/910,581
• Publication Number:
  US 20120101654A1
• Time in Patent Office: 1,103 Days
• Field of Search: 703/1, 701/25, 701/23, 701/532, 701/411, 701/1, 725/105, 382/104, 340/988, 340/990
• US Class Current: 701/1
• CPC Class Codes: G08G 1/096844 where the complete route is dynamically recomputed based on new data
• CPC Class Codes: G08G 1/143 inside the vehicles
• CPC Class Codes: G08G 1/147 where the parking area is within an open public zone, e.g. city centre
• CPC Class Codes: G08G 1/168 Driving aids for parking, e.g. acoustic or visual feedback on parking space

Abstract

Method, storage medium and system of optimizing a destination for a vehicle by obtaining a map corresponding to a desired destination of the vehicle and identifying objectives of the map based on multiple parameters including collision avoidance, driver time, legal constraints and social consensus. A cost function is constructed to determine an optimal destination based on a proximity to the desired destination and the identified objectives, and an optimal destination is identified by minimizing a value of the cost function.

Claims

1. A method of optimizing a destination for a vehicle, comprising:

obtaining a map corresponding to a desired destination of the vehicle;

identifying objectives of the map based on multiple parameters including collision avoidance, driver time, legal constraints and social consensus;

constructing a cost function to determine an optimal destination based on a proximity to the desired destination and the identified objectives; and

identifying the optimal destination of the vehicle by minimizing a value of the cost function.

2. The method according to claim 1, further comprising:

updating the map with updated data from multiple sensors while the vehicle approaches the optimal destination;

updating the identified objectives and the cost function based on the updated map; and

identifying a new optimal destination based on the updated cost function.

3. The method according to claim 2, further comprising:

discarding the previously identified optimal destination and selecting the newly identified optimal destination as the vehicle'"'"'s destination in response to determining the previously identified optimal destination fails to satisfy one of the identified objectives according to the updated map; and

in response to determining the previously identified optimal destination satisfies the identified objectives according to the updated map and in response to determining the newly identified optimal destination is less than a predetermined distance away from the previously identified optimal destination, discarding the newly identified optimal destination and selecting the previously identified optimal destination as the vehicle'"'"'s destination to reduce a number of restarts associated with changing the vehicle'"'"'s destination.

4. The method according to claim 2, wherein the map is updated by sensors mounted to the vehicle.

5. The method according to claim 1, wherein processing for the cost function is restricted to a processing zone encompassing the desired destination and an area surrounding the desired destination having fixed dimensions.

6. The method according to claim 5, wherein the fixed dimensions are adjustable through a user-interface for a controller of the vehicle.

7. The method according to claim 1, wherein the legal constraints parameter includes parking restrictions including an allowable distance of a wheel of a vehicle to a curb and an allowable distance of a vehicle from a fire hydrant or a cross-walk.

8. The method according to claim 7, wherein the distances associated with the legal constraints are adjustable through a user-interface for a controller of the vehicle.

9. The method according to claim 1, wherein the social consensus parameter includes social parking parameters including at least one of consistent vehicle alignment, vehicle alignment with respect to a curb, and spacing between parallel or adjacent vehicles.

10. The method according to claim 9, wherein the spacing and alignment parameters associated with the social consensus parameter constraints are adjustable through a user-interface for a controller of the vehicle.

11. The method according to claim 1, further comprising:

minimizing the value of the cost function by employing branch-and-bound search techniques and conjugate gradient optimization.

12. The method according to claim 1, further comprising:

constructing the map from data from multiple sensors, the sensors including at least two of lidar, camera, radar and infrared.

13. A storage medium including executable instructions, that when executed by a processor performs a method of optimizing a destination for a vehicle, the method comprising:

obtaining a map corresponding to a desired destination of the vehicle;

identifying objectives of the map based on multiple parameters including collision avoidance, driver time, legal constraints and social consensus;

constructing a cost function to determine an optimal destination based on a proximity to the desired destination and the identified objectives; and

identifying the optimal destination of the vehicle by minimizing a value of the cost function.

14. The storage medium according to claim 13, the method further comprising:

updating the map with updated data from multiple sensors while the vehicle approaches the optimal destination;

updating the cost function based on the updated map; and

identifying a new optimal destination based on the updated cost function.

15. The storage medium according to claim 14, the method further comprising:

discarding the previously identified optimal destination and selecting the newly identified optimal destination as the vehicle'"'"'s destination in response to determining the previously identified optimal destination fails to satisfy one of the identified objectives according to the updated map; and

in response to determining the previously identified optimal destination satisfies the identified objectives according to the updated map and in response to determining the newly identified optimal destination is less than a predetermined distance away from the previously identified optimal destination, discarding the newly identified optimal destination and selecting the previously identified optimal destination as the vehicle'"'"'s destination to reduce a number of restarts associated with changing the vehicle'"'"'s destination.

16. The storage medium according to claim 13, wherein processing for the cost function is restricted to a processing zone encompassing the desired destination and an area surrounding the desired destination having fixed dimensions.

17. A system including a processor to optimize a destination for a vehicle, the system comprising:

a map module configured to obtain a map corresponding to a desired destination of the vehicle;

an identification module configured to identify objectives of the map based on multiple parameters including collision avoidance, driver time, legal constraints and social consensus;

a cost function module configured to construct a cost function to determine an optimal destination based on a proximity to the desired destination and the identified objectives; and

a destination module configured to identify the optimal destination of the vehicle by minimizing a value of the cost function.

18. The system according to claim 17, wherein:

the map module updates the map with updated data from multiple sensors while the vehicle approaches the optimal destination;

the cost function module updates the cost function based on the updated map; and

the destination module identifies a new optimal destination based on the updated cost function.

19. The system according to claim 18, wherein:

the destination module discards the previously identified optimal destination and selects the newly identified optimal destination as the vehicle'"'"'s destination in response to determining the previously identified optimal destination fails to satisfy one of the identified objectives according to the updated map; and

in response to determining the previously identified optimal destination satisfies the identified objectives according to the updated map and in response to determining the newly identified optimal destination is less than a predetermined distance away from the previously identified optimal destination, the destination module discards the newly identified optimal destination and selects the previously identified optimal destination as the vehicle'"'"'s destination to reduce a number of restarts associated with changing the vehicle'"'"'s destination.

20. The system according to claim 17, wherein processing for the cost function is restricted to a processing zone encompassing the desired destination and an area surrounding the desired destination having fixed dimensions.