System and method for controlling vehicle components based on camera-obtained image information

• US 9,676,386 B2
• Filed: 06/03/2015
• Issued: 06/13/2017
• Est. Priority Date: 06/03/2015
• Status: Active Grant

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Inventors: Shutko, John, Neubecker, Cynthia M, Remillard, Jeffrey Thomas
• Primary Examiner(s): Troost, Aaron L
• Assistant Examiner(s): WEEKS, MARTIN A
• Application Number:
  US14/730,080
• Publication Number:
  US 20160355182A1
• Time in Patent Office: 741 Days
• CPC Class Codes: B60Q 9/00 Arrangement or adaptation of signal devices not provided for in one of main groups B60Q1/00 - B60Q7/00 , e.g. haptic signalling
• CPC Class Codes: B60W 2050/143 Alarm means
• CPC Class Codes: B60W 2420/403 Image sensing, e.g. optical camera
• CPC Class Codes: B60W 2554/00 Input parameters relating to objects
• CPC Class Codes: B60W 2555/60 Traffic rules, e.g. speed limits or right of way
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 30/14 Adaptive cruise control
• CPC Class Codes: B60W 30/143 Speed control B60W30/16 takes precedence
• CPC Class Codes: B60W 50/14 Means for informing the driver, warning the driver or prompting a driver intervention
• CPC Class Codes: G01C 21/3415 Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents
• CPC Class Codes: G01C 21/3602 Input other than that of destination using image analysis, e.g. detection of road signs, lanes, buildings, real preceding vehicles using a camera
• CPC Class Codes: G01C 21/3697 Output of additional, non-guidance related information, e.g. low fuel level G01C21/3679 takes precedence

Abstract

Various embodiments of the present disclosure provide systems and methods for provide monitoring a vehicle'"'"'s surroundings, predicting when a navigation route will pass through a closed road, preemptively modifying the navigation route to avoid the closed road, identifying changes in speed limit, and identifying dangerous debris in the roadway. One embodiment of the camera-based vehicle control system includes a camera configured to obtain image information and a processor configured to: analyze the image information; if a reroute condition is satisfied based on the image information, implement an alternate navigation route; if a threat condition is satisfied based on the image information, cause an output device to output a threat alert; and if a speed condition is satisfied based on the image information, modify a vehicle speed setting.

Claims

1. A control system, for a vehicle, comprising:

vehicle camera(s) that capture image(s);

processor(s) configured to;

parse the image(s) for road closure signs and associated closure lengths;

generate and display a navigational route based on parsed road closure signs and parsed associated closure lengths;

determine that one of the images yields a parsed road closure sign, but not a parsed associated closure length, and, in response;

query a traffic information server to determine the associated closure length.

2. The control system of claim 1, wherein the processor(s) are configured to:

parse the image(s) for the road closure signs and the associated closure lengths via image-processing software, wherein the vehicle camera(s) are directly mounted to the vehicle, and wherein the vehicle includes (i) a motor configured to provide mechanical power to wheel(s) and (ii) batterie(s).

3. The control system of claim 1, wherein the processor(s) are configured to:

parse the image(s) for the road closure signs at least partially by comparing the image(s) to prestored images of a plurality of different road closure signs.

4. The control system of claim 1, wherein the processor(s) are configured to:

generate the navigational route based on parsed road closure signs and parsed associated closure lengths such that the navigational route avoids closed roads for their associated closure lengths.

5. A control system, for a vehicle, comprising:

vehicle camera(s) that capture image(s);

processor(s) configured to;

parse the image(s) for (i) road closure signs and (ii) associated closure lengths;

generate and display a navigational route based on parsed road closure signs and parsed associated closure lengths;

begin parsing the image(s) for detour signs upon detecting a parsed road closure sign;

determine that one of the images yields a parsed road closure sign, but not a parsed associated closure length, and, in response;

query a traffic information server to determine the associated closure length.

6. The control system of claim 5, wherein the processor(s) are configured to:

parse the image(s) for the road closure signs and the associated closure lengths via image-processing software, wherein the vehicle camera(s) are directly mounted to the vehicle, and wherein the vehicle includes a motor configured to provide mechanical power to wheel(s) and batterie(s).

7. A control system, for a vehicle, comprising:

vehicle camera(s) that capture image(s);

processor(s) configured to;

parse the image(s) for (i) road closure signs and (ii) associated closure lengths;

generate and display a navigational route based on parsed road closure signs and parsed associated closure lengths;

parse the image(s) for objects and road widths;

compare widths of the objects to the road widths;

output threat alerts based on outcomes of the comparisons.

8. The control system of claim 7, wherein the processor(s) are configured to:

output threat alerts by generating graphics on a display.

9. The control system of claim 7, wherein the processor(s) are configured to:

modulate intensities of the output threat alerts based on determined identities of the parsed objects.

10. The control system of claim 7, wherein the processor(s) are configured to:

parse the image(s) for the road closure signs and the associated closure lengths via image-processing software, wherein the vehicle camera(s) are directly mounted to the vehicle, and wherein the vehicle includes (i) a motor configured to provide mechanical power to wheel(s) and (ii) batterie(s).

11. A control system, for a vehicle, comprising:

vehicle camera(s) that capture image(s);

a navigation module that enables user input of a desired navigational route, wherein the navigational route is a readjusted navigational route;

processor(s) configured to;

parse the image(s) for (i) road closure signs and (ii) associated closure lengths;

generate and display a navigational route based on parsed road closure signs and parsed associated closure lengths;

determine an absence of a desired navigational route from the navigation module;

generate and display the readjusted navigational route based on the parsed road closure signs and the parsed associated closure lengths even when a desired navigational route is absent from the navigation module.

12. The control system of claim 11, wherein the processor(s) are configured to:

parse the image(s) for the road closure signs and the associated closure lengths via image-processing software, wherein the vehicle camera(s) are directly mounted to the vehicle, and wherein the vehicle includes (i) a motor configured to provide mechanical power to wheel(s) and (ii) batterie(s).

13. The control system of claim 11, wherein the processor(s) are configured to:

determine that one of the images includes a parsed road closure sign, but not a parsed associated closure length, and, in response;

query a traffic information server to determine the associated closure length.

14. A control method, for a vehicle, comprising, via processor(s) that received captured image(s) from vehicle camera(s):

parsing the image(s) for (i) road closure signs and (ii) associated closure lengths;

generating and displaying a navigational route based on parsed road closure signs and parsed associated closure lengths;

parsing the image(s) for road closure signs and associated closure lengths via image-processing software;

parsing the image(s) for the road closure signs by comparing the image(s) to prestored images of a plurality of different road closure signs;

generating the navigational route based on parsed road closure signs and parsed associated closure lengths such that the navigational route avoids closed roads for their associated closure lengths

determining that one of the images includes a parsed road closure sign, but not a parsed associated closure length, and, in response;

querying a traffic information server to determine the associated closure length.

15. The method of claim 14, further comprising:

beginning to parse the image(s) for detour signs upon detecting a parsed road closure sign.

16. The method of claim 15, further comprising:

parsing the image(s) for objects and road widths;

comparing widths of the objects to the road widths;

outputting threat alerts based on outcomes of the comparisons.

17. The method of claim 16, further comprising:

outputting the threat alerts by generating graphics on a display.

18. The method of claim 16, further comprising:

controlling intensities of the output threat alerts based on determined identities of the parsed objects.

19. The method of claim 18, wherein the navigational route is a readjusted navigational route, and the method further comprises:

determining an absence of a desired navigational route from a navigation module;

generating and displaying the readjusted navigational route based on the parsed road closure signs and the parsed associated closure lengths even when a desired navigational route is absent from the navigation module.