TRAFFIC FLOW RATES

• US 20170287327A1
• Filed: 06/19/2017
• Published: 10/05/2017
• Est. Priority Date: 03/03/2014
• Status: Active Grant

• Current Assignee: Inrix Incorporated
• Original Assignee: Inrix Incorporated
• Inventors: SCOFIELD, Christopher L.
• Granted Patent: US 10,319,232 B2
• Time in Patent Office: Days
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• CPC Class Codes: G01C 21/3608 : using speech input, e.g. using speech recognition
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Abstract

One or more techniques and/or systems are provided for determining a scaled flow rate of traffic for a road segment. For example, probe flow rate information is determined based upon locational information from one or more probe vehicles on a road segment (e.g., a flow rate of probe vehicles corresponding to a sum of probe vehicles identified from time stamped global positioning system coordinates provided by the probe vehicles). Satellite imagery of the road segment is analyzed to identify a count of vehicles on the road segment. Scale factor and offset information is estimated based upon the probe flow rate information and the count of vehicles. The scale factor and offset information is used to scale the probe flow rate information to determine a scaled flow rate that may be a relatively accurate flow rate of traffic, which may correspond to an inferred traffic volume along the road segment.

Claims

1. A system for determining a flow rate of traffic for a road segment, comprising:

a traffic modeling component, implemented via a processor, configured to;

determine probe flow rate information based upon locational information from one or more probe vehicles on a road segment;

obtain satellite imagery of the road segment;

analyze the satellite imagery to identify a count of vehicles on the road segment for a unit of time; and

determine a flow rate based upon the probe flow rate information and the count of vehicles for the unit of time.

2. The system of claim 1, the traffic modeling component configured to:

identify a linear feature for identifying the road segment within the satellite imagery.

3. The system of claim 1, the traffic modeling component configured to:

overlay a road network onto the satellite imagery for identifying the road segment within the satellite imagery.

4. The system of claim 1, the traffic modeling component configured to:

identify a parallelogram for identifying a vehicle within the satellite imagery.

5. The system of claim 1, the traffic modeling component configured to:

determine a ground flow rate based upon the count of vehicles; and

determine the flow rate based upon the probe flow rate information and the ground flow rate.

6. The system of claim 1, the traffic modeling component configured to:

determine the flow rate for a second unit of time, different than the unit of time, in real-time based upon the probe flow rate information corresponding to real-time locational information of the one or more probe vehicles.

7. The system of claim 1, the traffic modeling component configured to:

obtain real-time locational information from a set of probe vehicles traveling along the road segment; and

determine a real-time flow rate for the road segment based upon the real-time locational information.

8. The system of claim 1, the locational information corresponding to a timestamp and global positioning system (GPS) coordinates of at least one of a vehicle head unit, a vehicle computing device, or a mobile device located within a vehicle.

9. The system of claim 1, the traffic modeling component configured to:

estimate scale factor and offset information based upon the probe flow rate information and the count of vehicles for the unit of time; and

average the scale factor and offset information based upon at least one of a road type, a day of week, a number of lanes per road, a season, road construction, or a weather condition.

10. The system of claim 1, the traffic modeling component configured to:

utilize vehicle speed information and the probe flow rate information to determine a traffic density.

11. The system of claim 1, the flow rate corresponding to inferred traffic volume along the road segment.

12. The system of claim 1, the traffic modeling component configured to:

utilize an image analysis algorithm to identify the count of vehicles from the satellite imagery.

13. The system of claim 12, the traffic modeling component configured to:

utilize the locational information to identify one or more identified probe vehicles on the road segment; and

adjust the image analysis algorithm based upon the one or more identified probe vehicles.

14. The system of claim 13, the traffic modeling component configured to:

adjust at least one of an edge detection function or a threshold used by the image analysis algorithm based upon the one or more identified probe vehicles.

15. A method for determining a scaled flow rate of traffic for a road segment, comprising:

determining probe flow rate information based upon locational information from one or more probe vehicles on a road segment;

obtaining imagery of the road segment;

analyzing the imagery to identify a count of vehicles on the road segment for a unit of time;

estimating scale factor and offset information based upon the probe flow rate information and the count of vehicles for the unit of time; and

scaling the probe flow rate information based upon the scale factor and offset information to determine a scaled flow rate.

16. The method of claim 15, comprising:

obtaining real-time locational information from a set of probe vehicles traveling along the road segment; and

applying the scale factor and offset information to the real-time locational information to determine a real-time flow rate for the road segment.

17. The method of claim 15, comprising:

utilizing an image analysis algorithm to identify the count of vehicles from the imagery;

utilizing the locational information to identify one or more identified probe vehicles on the road segment; and

adjusting the image analysis algorithm based upon the one or more identified probe vehicles.

18. The method of claim 15, the imagery comprising an image.

19. The method of claim 15, the imagery comprising a video.

20. A non-transitory computer readable medium comprising instructions which when executed perform a method for determining a scaled flow rate of traffic for a road segment, comprising:

determining flow rate information associated with a road segment;

obtaining satellite imagery of a road segment;

analyzing the satellite imagery to identify a count of vehicles on the road segment for a unit of time;

estimating scale factor and offset information based upon the flow rate information and the count of vehicles for the unit of time; and

scaling the flow rate information based upon the scale factor and offset information to determine a scaled flow rate.