SYSTEMS AND METHODS FOR PRIORITIZED DRIVER ALERTS

• US 20160272215A1
• Filed: 03/20/2015
• Published: 09/22/2016
• Est. Priority Date: 03/20/2015
• Status: Active Grant

• Current Assignee: iOnRoad Technologies Limited (Samsung Group)
• Original Assignee: Harman International Industries Incorporated (Samsung Group)
• Inventors: Laine, Heikki
• Granted Patent: US 9,505,413 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B60W 2040/0818 Inactivity or incapacity of driver
• CPC Class Codes: B60W 2520/10 Longitudinal speed
• CPC Class Codes: B60W 2520/105 Longitudinal acceleration
• CPC Class Codes: B60W 2540/18 Steering angle
• CPC Class Codes: B60W 2540/20 Direction indicator values
• CPC Class Codes: B60W 2540/221 Physiology, e.g. weight, heartbeat, health or special needs
• CPC Class Codes: B60W 2540/225 Direction of gaze
• CPC Class Codes: B60W 2540/30 Driving style
• CPC Class Codes: B60W 2554/00 Input parameters relating to objects
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 2710/30 Auxiliary equipments
• CPC Class Codes: B60W 30/095 Predicting travel path or likelihood of collision
• CPC Class Codes: B60W 40/09 Driving style or behaviour
• CPC Class Codes: B60W 50/14 Means for informing the driver, warning the driver or prompting a driver intervention
• CPC Class Codes: G06V 20/58 Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
• CPC Class Codes: G06V 20/597 Recognising the driver's state or behaviour, e.g. attention or drowsiness
• CPC Class Codes: G08G 1/163 involving continuous checking
• CPC Class Codes: G08G 1/165 for passive traffic, e.g. including static obstacles, trees
• CPC Class Codes: G08G 1/166 for active traffic, e.g. moving vehicles, pedestrians, bikes

Abstract

Various methods and systems are provided for generating prioritized alerts for a driver based on a fusion of data from a plurality of sensors. In one example, a method comprises calculating a first route of a vehicle, calculating a second route of an obstacle, calculating a gaze of a driver of the vehicle, generating an alert responsive to the gaze not including the obstacle and the first route intersecting the second route within a threshold duration, and suppressing a generation of the alert otherwise.

Claims

1. A method, comprising:

calculating a first route of a vehicle;

calculating a second route of an obstacle;

calculating a gaze of a driver of the vehicle;

generating an alert responsive to the gaze not including the obstacle when the first route intersects the second route within a threshold duration; and

suppressing generation of an alert otherwise.

2. The method of claim 1, wherein calculating the first route of the vehicle is based on navigation system data.

3. The method of claim 1, wherein calculating the first route of the vehicle is based on vehicle data including one or more of steering wheel angle, turn signal, and acceleration.

4. The method of claim 1, wherein calculating the second route of the obstacle is based on one or more of light sensor data, camera data, and GPS data, the GPS data received from a computing device carried by the obstacle.

5. The method of claim 1, wherein calculating the gaze of the driver is based on at least one or more of a head tilt angle, head turn angle, and eye position calculated from sensor data, and wherein the gaze of the driver does not include the obstacle when the gaze of the driver does not coincide with a position of the obstacle for a first threshold duration within a second threshold duration.

6. The method of claim 1, wherein the second route of the obstacle is calculated responsive to the obstacle within a threshold range of the vehicle.

7. The method of claim 1, further comprising generating an alert responsive to a change in the second route of the obstacle while the gaze does not include the obstacle.

8. An in-vehicle computing system of a vehicle, the in-vehicle computing system comprising:

an inter-vehicle system communication module communicatively connecting the in-vehicle computing system to one or more vehicle systems of the vehicle;

a processor; and

a storage device storing instructions executable by the processor to;

calculate a first route of the vehicle;

calculate a second route of an obstacle;

calculate a gaze of a driver of the vehicle;

generate an alert responsive to the gaze not including the obstacle when the first route is predicted to intersect the second route during a threshold duration measured from a current time; and

suppress the alert otherwise.

9. The in-vehicle computing system of claim 8, further comprising a navigation subsystem, and wherein calculating the first route of the vehicle is based on navigation data received from the navigation subsystem.

10. The in-vehicle computing system of claim 8, further comprising a gaze sensor, and wherein calculating the gaze of the driver is based on at least one or more of a head tilt angle, head turn angle, and eye position calculated from gaze sensor data received from the gaze sensor, and wherein the gaze of the driver is not directed towards the obstacle when the gaze of the driver does not coincide with a position of the obstacle for a first threshold duration within a second threshold duration.

11. The in-vehicle computing system of claim 8, wherein calculating the first route of the vehicle is based on one or more parameters received from the one or more vehicle systems, the one or more parameters including a vehicle speed, steering wheel angle, turn signal status, and vehicle acceleration.

12. The in-vehicle computing system of claim 8, further comprising an obstacle sensor configured to measure a velocity of the obstacle, and wherein calculating the second route of the obstacle is based on the velocity of the obstacle.

13. The in-vehicle computing system of claim 12, wherein the obstacle sensor comprises one or more cameras, and wherein the velocity of the obstacle is measured from image data acquired by the one or more cameras.

14. The in-vehicle computing system of claim 12, wherein the obstacle sensor comprises a lidar subsystem, and wherein the velocity of the obstacle is measured from light sensor data acquired by the lidar subsystem.

15. The in-vehicle computing system of claim 12, wherein calculating the second route of the obstacle is based on GPS data received from a computing device associated with the obstacle.

16. The in-vehicle computing system of claim 8, wherein the alert comprises one or more of a visual alert and an audible alert perceivable by the driver, and wherein the alert includes indicia regarding a position of the obstacle.

17. A system for a vehicle, comprising:

a sensor subsystem including at least an obstacle sensor and a gaze sensor, the obstacle sensor configured to detect a moving obstacle and a velocity of the moving obstacle, the gaze sensor configured to detect a gaze of a driver of the vehicle;

a user interface configured to provide alerts to the driver;

a navigation subsystem configured to evaluate a route of the vehicle;

a non-transitory memory;

a processor configured with executable instructions stored in the non-transitory memory that when executed cause the processor to;

calculate a route of the moving obstacle based on the velocity of the moving obstacle received from the obstacle sensor;

generate, via the user interface, an alert responsive to at least a first condition and a second condition, the first condition comprising the gaze of the driver not including the moving obstacle and the second condition comprising a prediction that the route of the moving obstacle will intersect the route of the vehicle during a threshold duration measured from a current time; and

suppress generation of an alert otherwise.

18. The system of claim 17, wherein the obstacle sensor comprises at least one camera.

19. The system of claim 17, wherein the obstacle sensor comprises a light radar detector.

20. The system of claim 17, wherein the gaze sensor comprises at least one camera configured to measure at least one or more of a head tilt angle, head turn angle, and eye position.