VEHICLE BEHAVIOR ANALYSIS

• US 20150178578A1
• Filed: 12/19/2013
• Published: 06/25/2015
• Est. Priority Date: 12/19/2013
• Status: Active Grant

• Current Assignee: Harman International Industries Incorporated (Samsung Electronics Co. Ltd.)
• Original Assignee: Harman International Industries Incorporated (Samsung Electronics Co. Ltd.)
• Inventors: Hampiholi, Vallabha
• Granted Patent: US 10,318,828 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06V 20/584 of vehicle lights or traffic lights
• CPC Class Codes: G08G 1/052 with provision for determining speed or overspeed speed measuring in general G01P
• CPC Class Codes: G08G 1/091 Traffic information broadcasting broadcasting communication H04H
• CPC Class Codes: G08G 1/166 for active traffic, e.g. moving vehicles, pedestrians, bikes
• CPC Class Codes: G08G 1/167 Driving aids for lane monitoring, lane changing, e.g. blind spot detection
• CPC Class Codes: G08G 1/205 Indicating the location of the monitored vehicles as destination, e.g. accidents, stolen, rental

Abstract

Embodiments are disclosed for identifying potentially erratic vehicles travelling near a vehicle including an in-vehicle computing system. In some embodiments, an in-vehicle computing system for a vehicle includes a processor, a sensor subsystem communicatively coupleable to a camera mounted on the vehicle, and an external device interface communicatively coupleable to an extra-vehicle server. The in-vehicle computing system may also include a storage device storing instructions executable by the processor to monitor neighboring vehicles within a field of view of the camera, identify a potential erratic vehicle, and transmit vehicle information to the extra-vehicle server.

Claims

1. An in-vehicle computing system for a vehicle, comprising:

a processor;

a sensor subsystem communicatively coupleable to a camera mounted on the vehicle;

an external device interface communicatively coupleable to an extra-vehicle device; and

a storage device storing instructions executable by the processor to;

monitor neighboring vehicles within a field of view of the camera;

identify a potential erratic vehicle; and

transmit vehicle information to the extra-vehicle device.

2. The in-vehicle computing system of claim 1, wherein monitoring neighboring vehicles within the field of view of the camera includes capturing image data including a number plate of each neighboring vehicle within the field of view of the camera to identify each neighboring vehicle and, for each identified neighboring vehicle, capturing a stream of image data imaging the identified neighboring vehicle over time.

3. The in-vehicle computing system of claim 1, wherein identifying the potential erratic vehicle includes determining one or more driving characteristics of each neighboring vehicle including speed, acceleration, braking, and driving patterns of each neighboring vehicle.

4. The in-vehicle computing system of claim 1, wherein identifying a potential erratic vehicle further includes sending image data from the camera to an external device located remotely from the in-vehicle computing system, the external device running an application configured to analyze the image data and identify a potential erratic vehicle based on the image data.

5. The in-vehicle computing system of claim 1, wherein the extra-vehicle device is an extra-vehicle server, and wherein the instructions are further executable by the processor to receive an alert confirming that the potential erratic vehicle is verified as an erratic vehicle.

6. The in-vehicle computing system of claim 1, wherein the extra-vehicle device is a mobile device, and wherein the instructions are further executable by the processor receive an alert identifying an erratic vehicle identified by another neighboring vehicle.

7. The in-vehicle computing system of claim 1, wherein the camera includes a camera system comprising a rear-facing camera and at least one additional camera.

8. The in-vehicle computing system of claim 1, wherein identifying the potential erratic vehicle includes identifying a vehicle condition of each of the neighboring vehicles.

9. The in-vehicle computing system of claim 1, further comprising a Controller Area Network (CAN) stack communicatively connected to an electronic control unit for the camera via a CAN bus of the vehicle, the CAN stack configured to provide instructions to control operation of the camera.

10. The in-vehicle computing system of claim 1, wherein the vehicle information includes a vehicle identifier for the potential erratic vehicle and/or a vehicle status of the potential erratic vehicle.

11. The in-vehicle computing system of claim 1, wherein the vehicle identifier includes one or more of a plate number, a make of the potential erratic vehicle, a model of the potential erratic vehicle, and a color of the potential erratic vehicle.

12. The in-vehicle computing system of claim 1, wherein the vehicle status includes one or more of a location, speed, condition, and identified erratic behavior of the potential erratic vehicle.

13. An in-vehicle computing system for a vehicle, comprising:

a processor;

a sensor subsystem communicatively coupleable to a camera mounted on the vehicle;

an external device interface communicatively coupleable to an extra-vehicle server; and

a storage device storing instructions executable by the processor to;

for each neighboring vehicle within a field of view of the camera, capture at least one frame of image data including a license plate of the neighboring vehicle;

capture a stream of image data indicating one or more driving behaviors of each neighboring vehicle within the field of view of the camera;

compare the one or more driving behaviors to driving behaviors of the vehicle and/or one or more other neighboring vehicles;

identify a potential erratic vehicle of the neighboring vehicles based on the stream of image data and one or more driving behaviors; and

transmit vehicle information corresponding to the potential erratic vehicle to the extra-vehicle server, the vehicle information including an identifier presented on the license plate of the potential erratic vehicle.

14. The in-vehicle computing system of claim 13, further comprising a frame grabber communicatively connected to the camera and configured to receive the stream of image data from the camera and separate the stream of image data into individual frames.

15. The in-vehicle computing system of claim 13, wherein the one or more driving behaviors includes frequent lane changes and identifying a potential erratic vehicle further comprises determining that a number of times the potential erratic vehicle changed lanes exceeded a threshold above an average number of times each of the neighboring vehicles changed lanes.

16. A method of identifying a potential erratic vehicle within a field of view of a camera of a vehicle, the method comprising:

capturing image data including an identifier of each neighboring vehicle within a field of view of the camera;

monitoring each neighboring vehicle within the field of view of the camera;

identifying, with an in-vehicle computing system of the vehicle, erratic behavior exhibited by a potential erratic vehicle of the neighboring vehicles; and

transmitting vehicle information for the potential erratic vehicle to a server.

17. The method of claim 16, further comprising receiving an alert from the extra-vehicle server regarding an erratic vehicle not identified as a potential erratic vehicle by the vehicle.

18. The method of claim 16, wherein transmitting the vehicle information for the potential erratic vehicle to the server includes transmitting the vehicle information when a threshold number of erratic behaviors are identified by the vehicle.

19. The method of claim 16, further comprising receiving an alert confirming that the potential erratic vehicle is verified as an erratic vehicle.

20. The method of claim 18, wherein the potential erratic vehicle is verified as an erratic vehicle when a threshold number of observing vehicles identify the erratic vehicle as a potential erratic vehicle.