AUTOMATED DYNAMIC VEHICLE BLIND SPOT DETERMINATION

• US 20100049393A1
• Filed: 08/21/2008
• Published: 02/25/2010
• Est. Priority Date: 08/21/2008
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Rish, Irina, Kanevsky, Dimitri, Emam, Ossama
• Granted Patent: US 8,489,284 B2
• Time in Patent Office: Days
• US Class Current: 701/29
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G08G 1/161 Decentralised systems, e.g. inter-vehicle communication

Abstract

A driver'"'"'s orientation within a vehicle is monitored. A change in the driver'"'"'s orientation is detected. A change to a blind spot of the vehicle is calculated based upon the detected change in the driver'"'"'s orientation. This abstract is not to be considered limiting, since other embodiments may deviate from the features described in this abstract.

Claims

1. A method, comprising:

monitoring a driver'"'"'s orientation within a first vehicle;

detecting a change in the driver'"'"'s orientation; and

calculating a change to a blind spot of the first vehicle based upon the detected change in the driver'"'"'s orientation.

2. The method of claim 1, where detecting the change in the driver'"'"'s orientation further comprises detecting a change in at least one of an eye position of the driver, a head position of the driver, a body position of the driver, and an activity of the driver.

3. The method of claim 1, where calculating the change to the blind spot further comprises calculating a change to at least one of a blind spot shape, blind spot dimensions, and a blind spot location.

4. The method of claim 1, further comprising:

determining at least one characteristic associated with the first vehicle, the at least one characteristic comprising at least one of a size of the first vehicle, a mirror adjustment associated with the first vehicle, a speed of the first vehicle, a driver'"'"'s seat height, a driver'"'"'s seat position, and a steering angle of the first vehicle; and

where calculating the change to the blind spot further comprises calculating the change to the blind spot based upon the determined at least one characteristic associated with the first vehicle.

5. The method of claim 1, further comprising:

applying at least one of the detected change in the driver'"'"'s orientation and the calculated change to the blind spot to a statistical model of dangerous situations; and

predicting a dangerous situation associated with the first vehicle based upon a result of the at least one of the detected change in the driver'"'"'s orientation and the calculated change to the blind spot applied to the statistical model of dangerous situations.

6. The method of claim 5, further comprising communicating information associated with at least one of the calculated change to the blind spot and the predicted dangerous situation to at least one of the first vehicle and a second vehicle.

7. The method of claim 5, where the statistical model of dangerous situations further comprises a model of at least one of dangerous driver characteristics, dangerous blind spot coordinates, dangerous information about the first vehicle, and dangerous characteristics of an environment surrounding the first vehicle.

8. The method of claim 5, where the statistical model of dangerous situations further comprises a probabilistic function comprising at least one of a Gaussian distribution and a uniform distribution.

9. The method of claim 5, further comprising updating the statistical model of dangerous situations based upon data associated with at least one of an actual collision and a near collision.

10. The method of claim 9, where updating the statistical model of dangerous situations based upon data associated with at least one of an actual collision and a near collision further comprises updating the statistical model of dangerous situations with at least one of a new dangerous driver characteristic, new dangerous blind spot coordinates, new dangerous information about the first vehicle, and a new dangerous characteristic of the environment surrounding the first vehicle.

11. A system comprising:

a memory adapted to store vehicle characteristics associated with a first vehicle; and

a processor programmed to;

monitor a driver'"'"'s orientation within the first vehicle;

detect a change in the driver'"'"'s orientation; and

calculate a change to a blind spot of the first vehicle based upon the detected change in the driver'"'"'s orientation and the stored vehicle characteristics.

12. The system of claim 11, where the processor is further programmed to detect a change in at least one of an eye position of the driver, a head position of the driver, a body position of the driver, and an activity of the driver.

13. The system of claim 11, where the processor is further programmed to calculate a change to at least one of a blind spot shape, blind spot dimensions, and a blind spot location.

14. The system of claim 11, where the processor is further programmed to:

determine at least one characteristic associated with the first vehicle, the at least one characteristic comprising at least one of a size of the first vehicle, a mirror adjustment associated with the first vehicle, a speed of the first vehicle, a driver'"'"'s seat height, a driver'"'"'s seat position, and a steering angle of the first vehicle; and

calculate the change to the blind spot based upon the determined at least one characteristic associated with the first vehicle.

15. The system of claim 11, where the processor is further programmed to:

apply at least one of the detected change in the driver'"'"'s orientation and the calculated change to the blind spot to a statistical model of dangerous situations; and

predict a dangerous situation associated with the first vehicle based upon a result of the at least one of the detected change in the driver'"'"'s orientation and the calculated change to the blind spot applied to the statistical model of dangerous situations.

16. The system of claim 15, where the processor is further programmed to communicate information associated with at least one of the calculated change to the blind spot and the predicted dangerous situation to at least one of the first vehicle and a second vehicle.

17. The system of claim 15, where the statistical model of dangerous situations further comprises at least one of a Gaussian model and a uniform model of at least one of dangerous driver characteristics, dangerous blind spot coordinates, dangerous information about the first vehicle, and dangerous characteristics of an environment surrounding the first vehicle.

18. The system of claim 15, where the processor is further programmed to update the statistical model of dangerous situations based upon data associated with at least one of an actual collision and a near collision.

19. The system of claim 18, where the processor is further programmed to update the statistical model of dangerous situations with at least one of a new dangerous driver characteristic, new dangerous blind spot coordinates, new dangerous information about the first vehicle, and a new dangerous characteristic of the environment surrounding the first vehicle.

20. A system, comprising:

a memory adapted to store vehicle characteristics associated with a first vehicle and a statistical model of dangerous situations; and

a processor programmed to;

monitor a driver'"'"'s orientation within the first vehicle;

detect a change in the driver'"'"'s orientation;

detect a change in at least one of an eye position of the driver, a head position of the driver, a body position of the driver, and an activity of the driver;

determine at least one characteristic associated with the first vehicle, the at least one characteristic comprising at least one of a size of the first vehicle, a mirror adjustment associated with the first vehicle, a speed of the first vehicle, a driver'"'"'s seat height, a driver'"'"'s seat position, and a steering angle of the first vehicle;

calculate a change to at least one of a blind spot shape, blind spot dimensions, and a blind spot location of the first vehicle based upon the detected change in the driver'"'"'s orientation and the determined at least one characteristic associated with the first vehicle;

read the statistical model of dangerous situations from the memory;

apply at least one of the detected change in the driver'"'"'s orientation and the calculated change to the blind spot to the statistical model of dangerous situations;

predict a dangerous situation associated with the first vehicle based upon a result of the at least one of the detected change in the driver'"'"'s orientation and the calculated change to the blind spot applied to the statistical model of dangerous situations;

communicate information associated with at least one of the calculated change to the blind spot and the predicted dangerous situation to at least one of the first vehicle and a second vehicle;

update the statistical model of dangerous situations based upon data associated with the predicted dangerous situation; and

store the updated statistical model of dangerous situations to the memory.