Traffic volume estimation

• US 9,582,999 B2
• Filed: 10/30/2014
• Issued: 02/28/2017
• Est. Priority Date: 10/31/2013
• Status: Active Grant

• Current Assignee: HERE Global B.V. (Nokia Corporation)
• Original Assignee: HERE Global B.V. (Nokia Corporation)
• Inventors: Lewis, Andrew Philip
• Primary Examiner(s): Nguyen, Bao Long T
• Application Number:
  US14/528,855
• Publication Number:
  US 20150120174A1
• Time in Patent Office: 852 Days
• Field of Search: 700117-119
• US Class Current: 1/1
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data

Abstract

Method, systems, and devices are described for determining traffic volume of one or more path segments. A computing device may receive probe data associated with a road segment from one or more sources. The computing device selects either a free flow algorithm or a congestion algorithm for the probe data, and calculates an estimated probe quantity from historical data using either the free flow algorithm or the congestion algorithm. A traffic volume may be estimated from the estimate probe quantity.

Claims

1. A method comprising:

receiving probe data from one or more mobile devices and generated by position circuitry, the probe data associated with a road segment;

selecting between a free flow algorithm and a congestion algorithm based on one or more values from the probe data generated by the position circuitry;

calculating an estimated probe quantity from historical data using either the free flow algorithm or the congestion algorithm;

querying a free flow lookup table with a time epoch from the probe data, when the free flow algorithm is selected;

receiving a traffic density from the free flow lookup table, when the free flow algorithm is selected; and

estimating traffic volume from the traffic density.

2. The method of claim 1, further comprising:

generating the free flow algorithm and the congestion algorithm based on historical density levels for the road segment according to time epoch.

3. The method of claim 2, wherein the historical density levels are calculated from probe data received from one or more sources.

4. The method of claim 3, wherein receiving probe data comprises:

receiving probe data from a first source from one or more mobile devices; and

receiving probe data from a second source from one or more mobile devices.

5. The method of claim 4, the method further comprising:

assigning a first coefficient to the probe data from the first source; and

assigning a second coefficient to the probe data from the second source,

wherein the estimated probe quantity is calculated as a function of the first coefficient and the second coefficient, or

wherein the traffic volume is estimated from the first coefficient and the second coefficient.

6. A method comprising:

receiving probe data from one or more mobile devices and generated by position circuitry, the probe data associated with a road segment;

selecting between a free flow algorithm and a congestion algorithm based on one or more values from the probe data generated by the position circuitry;

calculating an estimated probe quantity from historical data using either the free flow algorithm or the congestion algorithm;

when the congestion algorithm is selected,

identifying a velocity derived from the probe data;

when the congestion algorithm is selected, identifying a time epoch from the probe data;

accessing a threshold velocity based on the time epoch;

comparing the threshold velocity to the velocity derived from the probe data; and

estimating traffic volume from the comparison of the threshold velocity to the velocity derived from the probe data.

7. The method of claim 6, further comprising:

when the velocity from the probe data exceeds the threshold velocity, reverting to the free flow algorithm.

8. The method of claim 7, further comprising:

when the velocity from the probe data is less than the threshold velocity, accessing a congestion density lookup table.

9. An apparatus comprising:

at least one processor; and

at least one memory including computer program code for one or more programs;

the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least;

receive probe data from one or more position sensors, the probe data associated with a road segment;

select a free flow algorithm when one or more values from the probe data are at a first level and a congestion algorithm when one or more values from the probe data are at a second level;

calculate an estimated probe quantity from historical data using either the free flow algorithm or the congestion algorithm; and

calculate traffic volume for the road segment from the estimated probe quantity,

wherein the free flow algorithm includes a free flow lookup table that associates a time epoch derived from the probe data to a traffic density, or wherein the congestion algorithm includes a congestion lookup table that associate a velocity derived from the probe data to a traffic density.

10. The apparatus of claim 9, wherein the congestion algorithm includes instructions to:

identify a time epoch from the probe data;

access a threshold velocity based on the time epoch; and

compare the threshold velocity to the velocity derived from the probe data.

11. The apparatus of claim 10 wherein when the velocity from the probe data exceeds the threshold velocity, the congestion algorithm reverts to the free flow algorithm.

12. The apparatus of claim 9, wherein the one or more position sensors include a first sensor from one or more mobile devices and a second sensor from one or more mobile devices.

13. The apparatus of claim 12, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least:

assign a first coefficient to the probe data from the first sensor; and

assign a second coefficient to the probe data from the second sensor,

wherein the estimated probe quantity is calculated as a function of the first coefficient and the second coefficient, or

wherein the traffic volume is estimated from the first coefficient and the second coefficient.

14. A method comprising:

receiving first probe data for a road segment from a first mobile device source of a first vehicle;

receiving second probe data for the road segment from a second mobile device source of a second vehicle;

assigning a first coefficient to the first probe data from the first mobile device source;

assigning a second coefficient to the second probe data from the second mobile device source;

selecting a free flow algorithm or a congestion algorithm based on one or more values from the first probe data and the second probe data;

calculating an estimated probe quantity from historical data using either the free flow algorithm or the congestion algorithm, wherein the estimated probe quantity is calculated as a function of the first coefficient and the second coefficient;

calculating an estimated traffic volume from the estimated probe quantity, and when the free flow algorithm is selected;

querying a free flow lookup table with a time epoch from the first probe data or the second probe data; and

receiving a traffic density from the free flow lookup table.

15. A method comprising:

receiving first probe data for a road segment from a first mobile device source of a first vehicle;

receiving second probe data for the road segment from a second mobile device source of a second vehicle;

assigning a first coefficient to the first probe data from the first mobile device source;

assigning a second coefficient to the second probe data from the second mobile device source;

selecting a free flow algorithm or a congestion algorithm based on one or more values from the first probe data and the second probe data;

calculating an estimated probe quantity from historical data using either the free flow algorithm or the congestion algorithm, wherein the estimated probe quantity is calculated as a function of the first coefficient and the second coefficient;

calculating an estimated traffic volume from the estimated probe quantity, and when the congestion algorithm is selected;

identifying a velocity derived from the first probe data or the second probe data;

identifying a time epoch from the first probe data or the second probe data;

accessing a threshold velocity based on the time epoch; and

comparing the threshold velocity to the velocity derived from the first probe data or the second probe data.