System and method for range measurement of a preceding vehicle

• US 20070031008A1
• Filed: 08/02/2005
• Published: 02/08/2007
• Est. Priority Date: 08/02/2005
• Status: Abandoned Application

• Current Assignee: Visteon Global Technologies Incorporated (Visteon Corporation)
• Original Assignee: Visteon Global Technologies Incorporated (Visteon Corporation)
• Inventors: Miyahara, Shunji
• Application Number:
  US11/195,427
• Publication Number:
  US 20070031008A1
• Time in Patent Office: Days
• US Class Current: 382/106
• CPC Class Codes: B60W 30/095 Predicting travel path or likelihood of collision
• CPC Class Codes: G06T 7/70 Determining position or orientation of objects or cameras camera calibration G06T7/80
• CPC Class Codes: G06V 20/58 Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads

Abstract

A system for determining range and lateral position of a vehicle is provided. The system includes a camera and a processor. The camera is configured to view a region of interest including the vehicle and generate an electrical image of the region. The processor is in electrical communication with the camera to receive the electrical image. The processor analyzes the image by identifying objects and determining a relationship corresponding to the expected pixel values at various locations on the road. The processor calculates a value indicative of the validity that an object is a vehicle by comparing the pixel values of the object with the expected pixel values based on the relationship. A score is determined based on the comparison indicating the likelihood that certain characteristics of the electrical image actually correspond to the vehicle.

Claims

1. A system for determining range of a vehicle, the system comprising:

a camera configured to view a region of interest including the vehicle and generate an electrical image of the region;

a processor in electrical communication with the camera to receive the electrical image, wherein the processor is configured to construct a plurality of objects indicative of potential vehicle locations, calculate a relationship corresponding to an expected road pixel value, and perform a comparison between object pixel values located proximate the objects and the expected road pixel value.

2. The system according to claim 1, wherein the relationship is an equation calculated based on pixel values of a road region.

3. The system according to claim 2, wherein the equation is a linear equation.

4. The system according to claim 1, wherein the processor calculates the relationship based on a regression algorithm.

5. The system according to claim 1, wherein the processor is configured to calculate a deviation between the object pixel values and the expected road pixel value.

6. The system according to claim 1, wherein the processor is configured to calculate a score for the object based on the comparison.

7. The system according to claim 6, wherein the range of the vehicle being determined based on the score of the object.

8. The system according to claim 6, wherein the processor is configured to identify a plurality of windows within the electrical image, each window of the plurality of windows corresponding to a predetermined physical size at a target range from the camera, the processor being further configured to evaluate characteristics of the electrical image in relation to each window to identify the vehicle.

9. The system according to claim 8, wherein the objects are constructed from edge segments generated based on the enhanced edge image.

10. The system according to claim 9, wherein the edge segments are vertical edge segments.

11. The system according to claim 9, wherein the score is based on a height of the edge segments.

12. The system according to claim 9, wherein the score is based on a width of the edge segments.

13. The system according to claim 6, wherein the score is based on a height of the objects.

14. The system according to claim 6, wherein the score is based on a width of the objects.

15. The system according to claim 1, wherein the processor is configured to generate a trinary image based on the edge enhanced image for the determination of the potential vehicle locations.

16. The system according to claim 15, wherein positive edge elements are identified by applying a predefined upper threshold to the edge enhanced image.

17. The system according to claim 15, wherein negative edge elements are identified by applying a predefined lower threshold to the edge enhanced image.

18. The system according to claim 15, wherein the objects are constructed from at least one positive and at least one negative edge segment generated from the trinary image.