Systems and methods for identifying intersections and controlling vehicles at intersections

1 . A vehicle comprising:

a plurality of sensors including at least one first sensor and at least one second sensor; and

a vehicle controller programmed to:

collect first sensor information from at least the at least one first sensor during operation of a vehicle;

execute an intersection classification AI model based upon the first sensor information to determine a type of intersection that the vehicle is approaching;

collect second sensor information from at least the at least one second sensor during vehicle operation;

execute an intersection specific AI model based upon the second sensor information to determine at least one course of action for the vehicle to execute, wherein the intersection specific model is associated with the type of intersection determined by the intersection classification model; and

control the vehicle according to the at least one course of action determined by the intersection specific AI model.

2 . The vehicle of claim 1 , wherein the vehicle controller is further programmed to:

train the intersection classification model using a plurality of historic intersection records for historic intersections associated with a type of intersection, wherein each historic intersection record includes i) an identification of the type of intersection of the historic intersection, and ii) historic sensor data associated with the historic intersection.

3 . The vehicle of claim 1 , wherein the vehicle controller is further programmed to:

train one or more intersection specific models using a subset of a plurality of historic vehicle records for historic intersections having identical intersection types, wherein each historic vehicle record includes i) historic courses of action of the vehicle, and ii) historic sensor data of a historic intersection associated with the same intersection type.

4 . The vehicle of claim 2 , wherein the second sensor includes at least one of a radar, a LIDAR, a proximity sensor, an ultrasonic sensor, an electromagnetic sensor, a wide RADAR, a long-distance RADAR, a Global Positioning System (GPS), a video device, an imaging device, a camera, an audio recorder, and a computer vision.

5 . The vehicle of claim 1 , wherein the vehicle controller is further programmed to:

apply the first sensor information to the intersection classification model to determine the type of intersection, wherein the intersection type includes at least one intersection designation including: a) a four-way; b) a Y-intersection; c) a T-intersection; d) a traffic circle; e) a fork; f) a designated turning lane; g) no turning lane; h) a controlled intersection; i) an uncontrolled intersection; j) a pedestrian crosswalk; and/or k) no pedestrian crosswalk.

6 . The vehicle of claim 2 , wherein the vehicle controller is further programmed to:

apply the second sensor information to the intersection specific model to determine at least one course of action for the vehicle including at least one of i) braking, ii) accelerating, and iii) maneuvering controls.

7 . A system for controlling a vehicle, wherein the system comprises:

a computer device comprising:

at least one memory; and

at least one processor in communication with the at least one memory, the at least one processor programmed to:

collect first sensor information from at least one first sensor during operation of a vehicle;

execute an intersection classification AI model based upon the first sensor information to determine a type of intersection that the vehicle is approaching;

collect second sensor information from at least one second sensor during vehicle operation;

execute an intersection specific AI model based upon the second sensor information to determine at least one course of action for the vehicle to execute, wherein the intersection specific model is associated with the type of intersection determined by the intersection classification model; and

control the vehicle according to the at least one course of action determined by the intersection specific AI model.

8 . The system of claim 7 , the at least one processor further programmed to:

train the intersection classification model using a plurality of historic intersection records for historic intersections associated with a type of intersection, wherein each historic intersection record includes i) an identification of the type of intersection of the historic intersection, and ii) historic sensor data associated with the historic intersection.

9 . The system of claim 7 , the at least one processor further programmed to:

train one or more intersection specific models using a subset of a plurality of historic vehicle records for historic intersections having identical intersection types, wherein each historic vehicle record includes i) historic courses of action of the vehicle, and ii) historic sensor data of a historic intersection associated with the same intersection type.

10 . The system of claim 7 , wherein the second sensor includes at least one of a radar, a LIDAR, a proximity sensor, an ultrasonic sensor, an electromagnetic sensor, a wide RADAR, a long-distance RADAR, a Global Positioning System (GPS), a video device, an imaging device, a camera, an audio recorder, and a computer vision.

11 . The system of claim 7 , the at least one processor further programmed to:

apply the first sensor information to the intersection classification model to determine the type of intersection, wherein the intersection type includes at least one intersection classification including: a) a four-way; b) a Y-intersection; c) a T-intersection; d) a traffic circle; e) a fork; f) a designated turning lane; g) no turning lane; h) a controlled intersection; i) an uncontrolled intersection; j) a pedestrian crosswalk; and/or k) no pedestrian crosswalk.

12 . The system of claim 7 , the at least one processor further programmed to:

apply the second sensor information to the intersection specific model to determine at least one course of action for the vehicle including at least one of i) braking, ii) accelerating, and iii) maneuvering controls.

13 . A method for controlling a vehicle using a vehicle controller associated with the vehicle, the method comprising:

collecting first sensor information from at least one first sensor during operation of a vehicle;

executing an intersection classification AI model based upon the first sensor information to determine a type of intersection that the vehicle is approaching;

collecting second sensor information from at least one second sensor during vehicle operation;

executing an intersection specific AI model based upon the second sensor information to determine at least one course of action for the vehicle to execute, wherein the intersection specific model is associated with the type of intersection type determined by the intersection classification model; and

controlling the vehicle according to the at least one course of action determined by the intersection specific AI model.

14 . The method of claim 13 , wherein the method further includes at least one of:

training the intersection classification model using a plurality of historic intersection records for historic intersections associated with a type of intersection, wherein each historic intersection record includes i) an identification of the type of intersection of the historic intersection, and ii) historic sensor data associated with the historic intersection and

updating the intersection classification model using a plurality of historic intersection records associated with a type of intersection.

15 . The method of claim 13 , wherein the method further includes at least one of:

training at least one intersection specific model using a subset of a plurality of historic vehicle records for historic intersections having identical intersection types, wherein each historic vehicle record includes i) historic courses of action of the vehicle, and ii) historic sensor data of a historic intersection associated with the same intersection type; and updating at least one intersection specific model associated with an intersection type using a plurality of historic vehicle records associated with vehicle interactions at the type of intersection.

16 . The method of claim 13 , wherein the second sensor includes at least one of a radar, a LIDAR, a proximity sensor, an ultrasonic sensor, an electromagnetic sensor, a wide RADAR, a long-distance RADAR, a Global Positioning System (GPS), a video device, an imaging device, a camera, an audio recorder, and a computer vision.

17 . The method of claim 13 , wherein the method further includes:

applying the first sensor information to the intersection classification model to determine the type of intersection, wherein the intersection type includes at least one intersection classification including: a) a four-way; b) a Y-intersection; c) a T-intersection; d) a traffic circle; e) a fork; f) a designated turning lane; g) no turning lane; h) a controlled intersection; i) an uncontrolled intersection; j) a pedestrian crosswalk; and/or k) no pedestrian crosswalk.