Traffic data simulator

• US 9,495,868 B2
• Filed: 11/01/2013
• Issued: 11/15/2016
• Est. Priority Date: 11/01/2013
• Status: Active Grant

• Current Assignee: HERE Global B.V. (HERE Holding Corporation)
• Original Assignee: HERE Global B.V. (HERE Holding Corporation)
• Inventors: Jang, Dongwook, Arcot, Praveen
• Primary Examiner(s): Jabr, Fadey
• Assistant Examiner(s): Martinez Borrero, Luis A
• Application Number:
  US14/069,664
• Publication Number:
  US 20150127243A1
• Time in Patent Office: 1,110 Days
• Field of Search: 701/117, 701/1, 701/118, 701/119, 701/414, 701/423, 701/412, 701/2, 701/540, 701/100, 701/22, 701/408
• US Class Current: 1/1
• CPC Class Codes: G08G 1/0116 from roadside infrastructure, e.g. beacons
• CPC Class Codes: G08G 1/012 from other sources than vehicle or roadside beacons, e.g. mobile networks
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: G08G 1/0141 for traffic information dissemination

Abstract

In one embodiment, traffic data that originates from sensors, cameras, or observations is analyzed. The traffic data is associated with multiple repeating time epochs or intervals. The traffic data is divided into clusters using a clustering technique. The clustering technique may include clusters of variable sizes. Each of the clusters is analyzed to calculate statistical parameters including but not limited to an average value for one or more clusters and a standard deviation value for one or more clusters. In response to a request for traffic data, simulated traffic data may be generated by providing the average value and the standard deviation value for one or more of the clusters.

Claims

1. 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 perform at least the following;

receive a request for simulated traffic data from a customer device;

identify traffic data associated with time epochs;

divide the traffic data into a plurality of clusters, wherein the plurality of clusters include variable centroids;

calculate a standard deviation value for each of the plurality of clusters;

generate simulated traffic data based on the standard deviations and the variable centroids while cycling through the plurality of clusters,

wherein the simulated traffic data includes multiple points of pseudo traffic data for testing a potential layout for a road network; and

provide the simulated traffic data in response to the request.

2. The apparatus of claim 1, wherein the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following:

select, using a random algorithm, an initial centroid for each of the plurality of clusters;

assign additional traffic data to one of the initial centroids; and

calculate a subsequent centroid based on an average of the additional traffic data and the initial centroid for one of the plurality of clusters.

3. The apparatus of claim 1, wherein the subsequent centroid is recalculated until a threshold is met.

4. The apparatus of claim 3, wherein the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following:

compare a difference in location between the one of the initial centroids and the subsequent centroid to the threshold.

5. The apparatus of claim 3, wherein the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following:

compare a difference in quantity between one of the plurality of clusters and the one of the plurality of clusters after the subsequent centroid is calculated.

6. The apparatus of claim 3, wherein the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following:

compare a difference in an average variance of the one of the plurality of clusters and the one of the plurality of clusters after the subsequent centroid is calculated.

7. The apparatus of claim 3, wherein the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following:

divide the traffic data into the plurality of clusters using a first number of clusters;

divide the traffic data into the plurality of clusters using a second number of clusters;

calculate a first variance using the first number of clusters; and

calculate a second variance using the second number of clusters.

8. The apparatus of claim 1, wherein one of the plurality of clusters for the simulated traffic data is selected based on a random variable.

9. A non-transitory computer readable medium including instructions that when executed are operable to:

receive, from a traffic camera, a traffic sensor, or a mobile device, measured traffic data organized into time intervals;

divide the measured traffic data within the time intervals into a first plurality of data clusters;

calculate a variance of the first plurality of data clusters;

divide the measured traffic data within the time intervals into a second plurality of data clusters;

calculate a variance of the second plurality of data clusters;

perform a comparison of the variance of the first plurality of data clusters to the variance of the second plurality of data clusters;

calculate, based on the comparison, statistical parameters of the measured traffic data within the time intervals;

generate multiple points of simulated traffic data based on the statistical parameters while cycling through the first plurality of data clusters or second plurality of data clusters; and

provide the simulated traffic data in response to a request.

10. The non-transitory computer readable medium of claim 9, the instructions configured to:

select one of the plurality of clusters based a random value.

11. A method comprising:

receiving a request for traffic data;

identifying traffic data collected by sensors, cameras, or mobile devices and associated with multiple repeating time epochs;

dividing the traffic data into a plurality of clusters;

receiving, by a processor, an average value and a standard deviation value for each of the plurality of clusters;

executing a simulation to produce a set of pseudo traffic data for testing a road network based on a random variable, the average value and the standard deviation value for the plurality of clusters; and

providing the pseudo traffic data in response to the request for traffic data.

12. The method of claim 11, wherein the traffic data is divided into the plurality of clusters using a random algorithm.

13. The method of claim 12, wherein the random algorithm includes an initial centroid for each of the plurality of clusters and additional traffic data is assigned to the initial centroids to calculate subsequent centroids based on averages of the additional traffic data and the initial centroids.

14. The method of claim 13, wherein the subsequent centroids are calculated as additional traffic data is added to the plurality of clusters until a threshold is met.

15. The method of claim 14, wherein a difference in location between one of the initial centroids and a corresponding one of the subsequent centroids is compared to the threshold.

16. The method of claim 14, wherein a difference in quantity between one of the plurality of clusters and the one of the plurality of clusters after the subsequent centroids is calculated.

17. The method of claim 14, wherein a difference in an average variance of the one of the plurality of clusters and the one of the plurality of clusters after the subsequent centroids is calculated.

18. The method of claim 14, wherein the random variable designates one of the plurality of clusters.