MERGE BEHAVIOR SYSTEMS AND METHODS FOR MAINLINE VEHICLES

• US 20190329779A1
• Filed: 04/27/2018
• Published: 10/31/2019
• Est. Priority Date: 04/27/2018
• Status: Active Grant

• Current Assignee: Honda Motor Co., Ltd. (Honda Motor Company)
• Original Assignee: Honda Motor Co., Ltd. (Honda Motor Company)
• Inventors: D'sa, Jovin, Rajab, Samer, Saigusa, Shigenobu, Bai, Xue
• Granted Patent: US 11,117,584 B2
• Time in Patent Office: Days
• CPC Class Codes: B60W 2050/0031 Mathematical model of the vehicle
• CPC Class Codes: B60W 2554/00 Input parameters relating to objects
• CPC Class Codes: B60W 2554/801 Lateral distance
• CPC Class Codes: B60W 2554/804 Relative longitudinal speed
• CPC Class Codes: B60W 30/0956 the prediction being responsive to traffic or environmental parameters
• CPC Class Codes: B60W 30/18163 Lane change; Overtaking manoeuvres
• 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: B60W 60/00276 for two or more other traffic participants
• CPC Class Codes: G05D 1/0088 characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G06N 20/10 using kernel methods, e.g. support vector machines [SVM]
• CPC Class Codes: G06N 20/20 Ensemble learning
• CPC Class Codes: G06N 5/01 Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound

Abstract

A merge behavior system assists a host vehicle positioned in a mainline lane that is adjacent a merge lane. The merge behavior system includes an identification module that identifies at least one proximate vehicle in the merge lane. The merge behavior system also includes a prediction module that selects one or more models based on the at least one proximate vehicle, calculates one or more merge factors corresponding to the one or more models, and predicts a merge location based on the one or more merge factors. The merge behavior system further includes a control module configured to adjust a kinematic parameter of the host vehicle to create a gap at the predicted merge location.

Claims

1. A merge behavior system for assisting a host vehicle positioned in a mainline lane that is adjacent a merge lane, the merge behavior system comprising:

an identification module configured to identify at least one proximate vehicle in the merge lane;

a prediction module configured to;

select one or more vehicle models based on the at least one proximate vehicle,

calculate one or more merge factors corresponding to the one or more vehicle models, and

predict a merge location based on the one or more merge factors; and

a control module configured to adjust a kinematic parameter of the host vehicle to create a gap at the predicted merge location.

2. The merge behavior system of claim 1, wherein the one or more vehicle models are based on naturalistic datasets that approximate human behavioral outcomes.

3. The merge behavior system of claim 1, wherein a vehicle model of the one or more vehicle models is selected based on a relative location of the at least one proximate vehicle to the host vehicle.

4. The merge behavior system of claim 1, wherein the prediction module is further configured to compare the one or more merge factors to at least one threshold value, and wherein predicted merge location is based on the comparison.

5. The merge behavior system of claim 1, further comprising a merge module configured to determine whether the gap at the predicted merge location is a sufficient size for the proximate vehicle, and in response to determining that the gap does not have a sufficient size, initiating the prediction module to predict an updated merge location.

6. The merge behavior system of claim 1, wherein the at least one proximate vehicle is a preceding vehicle, a vehicle model of the one or more vehicle models is a preceding vehicle model, and wherein the preceding vehicle model is based on a preceding gap length between the host vehicle and the preceding vehicle, a host vehicle velocity, and a relative preceding velocity of the preceding vehicle relative to the host vehicle.

7. The merge behavior system of claim 6, wherein the preceding vehicle model incorporates a following vehicle variable that has a binary value based on the at least one proximate vehicle further including a following vehicle in the mainline lane.

8. The merge behavior system of claim 1, wherein the at least one proximate vehicle is a following vehicle, a vehicle model of the one or more vehicle models is a following vehicle model, and wherein the following vehicle model is based on a following gap length between the host vehicle and the following vehicle, a host vehicle velocity, and a relative following velocity of the following vehicle relative to the host vehicle.

9. The merge behavior system of claim 1, wherein the kinematic parameter is a velocity of the host vehicle.

10. The merge behavior system of claim 1, wherein the control module adjusts the kinematic parameter with an advanced driver-assistance system.

11. A merge behavior system for assisting a host vehicle positioned in a mainline lane that is adjacent a merge lane, the merge behavior system comprising:

an identification module configured to identify at least one proximate vehicle in the merge lane;

a prediction module configured to;

select one or more vehicle models based on a relative location of the at least one proximate vehicle to the host vehicle, and

predict a merge location based on the one or more vehicle models,

wherein the merge location is ahead or behind the host vehicle; and

a control module configured to adjust a kinematic parameter of the host vehicle to create a gap at the predicted merge location.

12. The merge behavior system of claim 11, wherein the one or more vehicle models incorporate naturalistic datasets that approximate human behavioral outcomes.

13. The merge behavior system of claim 11, wherein the kinematic parameter is a velocity of the host vehicle.

14. The merge behavior system of claim 11, wherein the control module adjusts the kinematic parameter with an advanced driver-assistance system.

15. The merge behavior system of claim 11, wherein in response to determining that the gap does not have a sufficient size, initiating a merge module configured to determine whether a gap at the predicted merge location is a sufficient size for the host vehicle, and in response to determining that the gap has a sufficient size, initiating a merge maneuver.

16. A merge behavior method for assisting a host vehicle positioned in a mainline lane that is adjacent a merge lane, the merge behavior method comprising:

identifying at least one proximate vehicle in the merge lane;

selecting one or more vehicle models based on the at least one proximate vehicle,

calculating one or more merge factors corresponding to the one or more vehicle models, and

predicting a merge location based on the one or more merge factors; and

adjusting a kinematic parameter of the host vehicle to create a gap at the predicted merge location.

17. The merge behavior method of claim 16, further comprising:

determining whether a gap at the predicted merge location is a sufficient size for the host vehicle, and

predicting an updated merge location.

18. The merge behavior method of claim 16, wherein the one or more vehicle models are based on naturalistic datasets that approximate human behavioral outcomes.

19. The merge behavior method of claim 16, wherein a vehicle model of the one or more vehicle models are selected based on a relative location of the at least one proximate vehicle to the host vehicle.

20. The merge behavior method of claim 16, further comprising comparing the one or more merge factors to at least one threshold value, and wherein predicted merge location is based on the comparison.