Collision mitigation and avoidance

• US 9,610,945 B2
• Filed: 01/25/2016
• Issued: 04/04/2017
• Est. Priority Date: 06/10/2015
• Status: Active Grant

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Inventors: Miller, Alex Maurice, Trombley, Roger Arnold, Deng, Kun, Pilutti, Thomas Edward, Piastowski, Patrick
• Primary Examiner(s): ANTONUCCI, ANNE MARIE
• Application Number:
  US15/005,037
• Publication Number:
  US 20160362104A1
• Time in Patent Office: 435 Days
• Field of Search: 701 48
• CPC Class Codes: B60W 2554/80 Spatial relation or speed relative to objects
• CPC Class Codes: B60W 30/08 Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
• CPC Class Codes: B60W 30/085 Taking automatic action to adjust vehicle attitude in preparation for collision, e.g. braking for nose dropping
• CPC Class Codes: B60W 30/09 Taking automatic action to avoid collision, e.g. braking and steering
• CPC Class Codes: B60W 30/0953 the prediction being responsive to vehicle dynamic parameters
• CPC Class Codes: B60W 30/0956 the prediction being responsive to traffic or environmental parameters
• CPC Class Codes: B60W 30/18154 Approaching an intersection
• CPC Class Codes: B60W 40/04 Traffic conditions
• CPC Class Codes: G07C 5/008 communicating information to a remotely located station transmission systems for measured values G08C
• CPC Class Codes: G07C 5/085 using electronic data carriers

Abstract

An intersection of a host vehicle and a target vehicle is identified. Data relating to the target vehicle are collected. A map of a surrounding environment is developed. A driver intent probability is determined based at least in part on the map. A threat estimation is determined based at least in part on the driver intent probability. At least one of a plurality of safety systems is activated based at least in part on the threat estimation.

Claims

1. A system, comprising:

a computer having a processor and a memory, the memory storing instructions executable by the computer to;

identify a target object;

identify a potential intersection of a host vehicle and the target object;

identify one or more data collectors to provide data for analyzing the intersection;

collect data relating to the host vehicle and the target object from the data collectors;

develop a coordinate map of a surrounding environment based at least in part on the data collected from the host vehicle and the target object;

identify a probable trajectory of the target object based at least in part on the coordinate map;

generate a threat estimation based at least in part on the probable trajectory; and

activate at least one of a plurality of vehicle safety systems based at least in part on a threat estimation obtained by analyzing the map.

2. The system of claim 1, wherein the data include a velocity and an acceleration of the object, wherein the velocity includes at least one of a lateral velocity and a longitudinal velocity, and the acceleration includes at least one of a lateral acceleration and a longitudinal acceleration, and wherein the threat estimation is based on at least one of a brake threat number, a steering threat number, and an acceleration threat number, the brake threat number being a measure of a change in the host vehicle longitudinal acceleration to allow one of the host vehicle to stop or the object to pass the host vehicle, the steering threat number being a measure of a change in the host vehicle lateral acceleration to allow one of the host vehicle and the object to clear a crossing zone, and the acceleration threat number is a measure of a specific longitudinal acceleration to allow one of the host vehicle and the object to pass the other of the host vehicle and the object.

3. The system of claim 2, wherein the at least one vehicle safety system is selectively activated based at least in part on at least one of the lateral velocity, the longitudinal velocity, the lateral acceleration, and the longitudinal acceleration.

4. The system of claim 1, wherein the vehicle safety systems include at least one of brake assist, warning, steering assist, torque assist, passive safety, and head lamp systems.

5. The system of claim 4, wherein the instructions include instructions to adjust a brake sensitivity of the brake assist system based at least in part on the threat estimation.

6. The system of claim 4, wherein the instructions further include instructions to adjust a steering wheel sensitivity of the steering assist system based at least in part on the threat estimation.

7. The system of claim 4, wherein the instructions further include instructions to adjust an acceleration sensitivity of the torque assist system based at least in part on the threat estimation.

8. The system of claim 4, wherein the instructions further include instructions to adjust at least one of a high beam activation, a head lamp aim, and a head lamp photometric pattern of the head lamp system based at least in part on the threat estimation.

9. The system of claim 1, wherein the instructions further include instructions to integrate the map into a digital road network map providing an X-Y-Z Cartesian road network coordinate map.

10. The system of claim 1, wherein the target object is a target vehicle, wherein the instructions further include instructions to use the map to determine a target vehicle driver intent probability based at least in part on the identified probable trajectory of the target vehicle, and a host vehicle driver intent probability, being a measure of a probable trajectory of the host vehicle, and, based at least in part on the target vehicle driver intent probability, produce the threat estimation that is a measure of a probability of a collision between the host vehicle and the target vehicle.

11. A method, comprising:

identifying a target object;

identifying a potential intersection of a host vehicle and the target object;

identifying one or more data collectors to provide data for analyzing the intersection;

collecting data relating to the host vehicle and the target object from the data collectors;

developing a coordinate map of a surrounding environment based at least in part on the data collected from the host vehicle and the target vehicle;

identifying a probable trajectory of the target object based at least in part on the coordinate map;

generating a threat estimation based at least in part on the probable trajectory; and

activating at least one of a plurality of vehicle safety systems based at least in part on the threat estimation.

12. The method of claim 11, wherein the data include a velocity and an acceleration of the target object, wherein the velocity includes at least one of a lateral velocity and a longitudinal velocity, and the acceleration includes at least one of a lateral acceleration and a longitudinal acceleration and wherein the threat estimation is based on at least one of a brake threat number, a steering threat number, and an acceleration threat number, the brake threat number being a measure of a change in the host vehicle longitudinal acceleration to allow one of the host vehicle to stop or the target object to pass the host vehicle, the steering threat number being a measure of a change in the host vehicle lateral acceleration to allow one of the host vehicle and the target object to clear a crossing zone, and the acceleration threat number is a measure of a specific longitudinal acceleration to allow one of the host vehicle and the target object to pass the other of the host vehicle and the target object.

13. The method of claim 12, wherein the at least one vehicle safety system is selectively activated based at least in part on the lateral velocity, the longitudinal velocity, the lateral acceleration, and the longitudinal acceleration.

14. The method of claim 11, wherein the vehicle safety systems include at least one of brake assist, warning, steering assist, torque assist, passive safety, and head lamp systems.

15. The method of claim 14, further comprising adjusts a brake sensitivity of the brake assist system based at least in part on the threat estimation.

16. The method of claim 14, further comprising adjusts a steering wheel sensitivity of the steering assist system based at least in part on the threat estimation.

17. The method of claim 14, further comprising adjusting an acceleration sensitivity of the torque assist system based at least in part on the threat estimation.

18. The method of claim 14, further comprising adjusting at least one of a high beam activation, a head lamp aim, and a head lamp photometric pattern of the head lamp system based at least in part on the threat estimation.

19. The method of claim 11, further comprising integrating the map into a digital road network map providing an X-Y-Z Cartesian road network coordinate map.

20. The method of claim 11, wherein the target object is a target vehicle, the method further comprising using the map to determine a target vehicle driver intent probability that is a measure of a probable trajectory of the target vehicle, and a host vehicle driver intent probability based at least in part on the probable trajectory of the host vehicle, and, based at least in part on the target vehicle driver intent probability, generating the threat estimation that is a measure of a probability of a collision between the host vehicle and the target vehicle.