LATERAL MANEUVER PLANNER FOR AUTOMATED DRIVING SYSTEM

• US 20150197246A1
• Filed: 01/16/2014
• Published: 07/16/2015
• Est. Priority Date: 01/16/2014
• 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, Nagasaka, Naoki, Sakai, Katsuhiro, Harada, Masahiro, Kamata, Nobuhide
• Granted Patent: US 9,340,207 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B60W 30/10 Path keeping cruise control for automatically following a preceding vehicle B60W30/165
• CPC Class Codes: B62D 15/025 Active steering aids, e.g. helping the driver by actively influencing the steering system after environment evaluation B62D1/28 takes precedence
• CPC Class Codes: G01C 21/26 specially adapted for navigation in a road network
• CPC Class Codes: G05D 1/0231 using optical position detecting means position-fixing by using electromagnetic waves other than radio waves, e.g. optical position detecting means G01S5/16

Abstract

A system, device, and methods of automated driving are disclosed. One example method includes determining one or more potential vehicle paths based on information specific to the environment surrounding a vehicle and receiving an indication classifying one or more objects proximate to the one or more potential vehicle paths as an object of interest based on input received from one or more sensors disposed on the vehicle. The method further includes selecting a preferred vehicle path from the one or more potential vehicle paths based on properties of the one or more objects of interest and sending a command, to one or more vehicle systems, to control the vehicle to follow the preferred vehicle path.

Claims

1. An automated driving system, comprising:

one or more sensors disposed on a vehicle; and

a computing device in communication with the one or more sensors, comprising;

one or more processors for controlling the 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;

determine, based on information specific to the environment surrounding the vehicle, one or more potential vehicle paths;

receive, based on input from the one or more sensors disposed on the vehicle, an indication classifying one or more objects proximate to the one or more potential vehicle paths as an object of interest;

select, based on properties of the one or more objects of interest, a preferred vehicle path from the one or more potential vehicle paths; and

send a command, to one or more vehicle systems, to control the vehicle to follow the preferred vehicle path.

2. The system of claim 1, wherein the information specific to the environment surrounding the vehicle includes lane information, the lane information including at least one of lane number and lane width and lane edge feature.

3. The system of claim 1, wherein determining one or more potential vehicle paths is further based on a navigation route of the vehicle.

4. The system of claim 1, wherein classifying the one or more objects proximate to the one or more potential vehicles paths as an object of interest includes detecting and analyzing the one or more properties of the one or more objects proximate to the one or more potential vehicles paths.

5. The system of claim 1, wherein the one or more properties of the one or more objects of interest include relative speed and relative motion direction in relation to the vehicle.

6. The system of claim 1, wherein the one or more properties of the one or more objects of interests include at least one of relative distance from the vehicle and from the one or more potential vehicle paths.

7. The system of claim 2, wherein the one or more processors are further configured to:

select, if no objects of interest are classified, a preferred vehicle path based on the one or more potential vehicle paths and the lane information.

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

determining, based on information specific to the environment surrounding a vehicle, one or more potential vehicle paths;

receiving, based on input received from one or more sensors disposed on the vehicle, an indication classifying one or more objects proximate to the one or more potential vehicle paths as an object of interest;

selecting, based on properties of the one or more objects of interest, a preferred vehicle path from the one or more potential vehicle paths; and

sending a command, to one or more vehicle systems, to control the vehicle to follow the preferred vehicle path.

9. The method of claim 8, wherein the information specific to the environment surrounding the vehicle includes lane information, the lane information including at least one of lane number and lane width and lane edge feature.

10. The method of claim 8, wherein calculating one or more potential vehicle paths is further based on a navigation route of the vehicle.

11. The method of claim 8, wherein classifying the one or more objects proximate to the one or more vehicles paths as an object of interest includes detecting and analyzing the one or more properties of the one or more objects proximate to the one or more vehicles paths.

12. The method of claim 8, wherein the one or more properties of the one or more objects of interest include relative speed and relative motion direction in relation to the vehicle.

13. The method of claim 8, wherein the one or more properties of the one or more objects of interests include at least one of relative distance from the vehicle and from the one or more potential vehicle paths.

14. The method of claim 9, further comprising:

selecting, if no objects of interest are classified, a preferred vehicle path based on the one or more potential vehicle paths and the lane information.

15. A computing device, comprising:

one or more processors for controlling the 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;

determine, based on information specific to the environment surrounding a vehicle, one or more potential vehicle paths;

receive, based on input received from one or more sensors disposed on the vehicle, an indication classifying one or more objects proximate to the one or more potential vehicle paths as an object of interest;

select, based on properties of the one or more objects of interest, a preferred vehicle path from the one or more potential vehicle paths; and

send a command, to one or more vehicle systems, to control the vehicle to follow the preferred vehicle path.

16. The computing device of claim 15, wherein the information specific to the environment surrounding the vehicle includes lane information, the lane information including at least one of lane number and lane width and lane edge feature.

17. The computing device of claim 15, wherein calculating one or more potential vehicle paths is further based on a navigation route of the vehicle.

18. The computing device of claim 15, wherein classifying the one or more objects proximate to the one or more vehicles paths as an object of interest includes detecting and analyzing the one or more properties of the one or more objects proximate to the one or more vehicles paths.

19. The computing device of claim 15, wherein the one or more properties of the one or more objects of interest include at least one of relative speed in relation to the vehicle and relative motion direction in relation to the vehicle and relative distance from the vehicle and relative distance from the one or more potential vehicle paths.

20. The computing device of claim 16, wherein the one or more processors are further configured to:

select, if no objects of interest are classified, a preferred vehicle path based on the one or more potential vehicle paths and the lane information.