Automatic driver modeling for integration of human-controlled vehicles into an autonomous vehicle network

1. A computer-implemented method, comprising:

identifying, with a processing device, a driver of a human-controlled vehicle based on behavior patterns of the driver measured by one or more sensors of an autonomous vehicle, wherein the human-controlled vehicle is not an autonomous vehicle, and wherein the driver identification comprises:

interrogating the human-controlled vehicle for the driver identification data;

receiving the driver identification data in response,

analyzing registration information of the human-controlled vehicle, and

identifying the driver using a pattern matching algorithm;

generating a model of the driver of the human-controlled vehicle by the autonomous vehicle based on the behavior patterns of the driver;

retrieving previously stored behavior patterns of the driver to augment the model of the driver; and

transmitting the model of the driver of the human-controlled vehicle by the autonomous vehicle to other nearby autonomous vehicles.

2. The computer-implemented method of claim 1 , wherein an autonomous vehicle probes a nearby vehicle on a roadway for the presence of autonomous interfaces, the autonomous interfaces communicating vehicle parameters comprising a vehicle's location, a vehicle's speed, and a subsequent action of the vehicle.

3. The computer-implemented method of claim 1 , wherein the autonomous vehicles are configured to anticipate actions of the driver of the human-controlled vehicle based on the model of the driver.

4. The computer-implemented method of claim 1 , wherein the retrieving of previously stored behavior patterns of the driver further comprises:

accessing a remote server using a unique identifier of the driver; and

uploading recently measured behavior patterns of the driver to the remote server.

5. The computer-implemented method of claim 4 , wherein the model of the driver is generated using a processing device onboard the human-controlled vehicle or a processing device of the remote server.

6. The computer-implemented method of claim 1 , wherein the model of the driver, which includes previously stored behavior patterns of the driver, is further augmented with present measurements of driver behavior patterns.

7. The computer-implemented method of claim 1 , wherein the one or more sensors comprise optical sensors and audio sensors for identifying the behavior patterns of the driver, the behavior patterns including a vehicle measurement selected from a group comprising a speed, an acceleration, a directional change, a movement, a brake frequency, and a variation in speed over a predetermined time.

8. The computer-implemented method of claim 1 , wherein the transmitting of the model of the driver from the human-controlled vehicle to the autonomous vehicles is implemented through a wireless antenna onboard the human-controlled vehicle.

9. The computer-implemented method of claim 4 , wherein the accessing of the remote server is implemented through a cellular antenna onboard the human-controlled vehicle.

10. The computer-implemented method of claim 4 , wherein behavior patterns of the driver stored in the remote server is accessible via the Internet.

11. A method comprising:

equipping autonomous vehicle with an onboard processor, the onboard processor executing a computer-implemented method comprising:

identifying, with the onboard processor, a driver of a human-controlled vehicle based on behavior patterns of the driver measured by one or more sensors coupled to the onboard processor of the autonomous vehicle, wherein the human-controlled vehicle is not an autonomous vehicle, and wherein the driver is identified using a pattern matching algorithm by:

interrogating the human-controlled vehicle for driver identification wherein the driver identification comprises:

receiving driver identification data, and

analyzing registration information of the human-controlled vehicle;

generating a dynamically updated model of the driver using the behavior patterns measured by the one or more sensors; and

transmitting an identification of the driver and the model of the driver of the human-controlled vehicle to other nearby vehicles with autonomous interfaces and to a remote server to store the generated model.

12. The method of claim 11 , wherein the onboard processor of the autonomous vehicle receives information from a second onboard processor installed on the human-controlled vehicle, and wherein the installation of the second onboard processor grants special driving privileges on roadways to the driver of the human-controlled vehicle.