Method and apparatus for classifying a traffic jam from probe data

• US 9,965,950 B2
• Filed: 06/03/2016
• Issued: 05/08/2018
• Est. Priority Date: 06/03/2016
• Status: Active Grant

• Current Assignee: HERE Global B.V. (Nokia Corporation)
• Original Assignee: HERE Global B.V. (Nokia Corporation)
• Inventors: Xu, Bo, Barkley, Tiffany, Lewis, Andrew, MacFarlane, Jane, Pietrobon, Davide, Stroila, Matei
• Primary Examiner(s): Heinle, Courtney D
• Application Number:
  US15/172,897
• Publication Number:
  US 20170352262A1
• Time in Patent Office: 704 Days
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0133 for classifying traffic situation

Abstract

An approach is provided for classifying a traffic jam from probe data. The approach involves receiving the probe data that is map-matched to a roadway on which the traffic jam is detected. The probe data is collected from one or more vehicles traveling the roadway. The approach also involves determining a jam area of the roadway based on the probe data. The jam area corresponds to one or more segments of the roadway affected by the traffic jam. The approach further involves determining a set of features indicated by the probe data from a portion of the probe data collected from the jam area. The approach further involves classifying, using a machine learning classifier, the traffic jam as either a recurring traffic jam or a non-recurring traffic jam based on the set of features.

Claims

1. A computer-implemented method for classifying a traffic jam using probe data, comprising:

receiving the probe data that is map-matched to a roadway on which the traffic jam is detected, wherein the probe data is collected from one or more vehicles traveling the roadway;

determining a jam area of the roadway based on the probe data, wherein the jam area corresponds to one or more segments of the roadway affected by the traffic jam;

determining a set of features indicated by the probe data from a portion of the probe data collected from the jam area; and

classifying the traffic jam as either a recurring traffic jam or a non-recurring traffic jam based on the set of features,

wherein the probe data is received from the one or more vehicles on a continuous batch basis,

wherein a batch of the probe data is collected for a predetermined period of time before the batch is processed and a next batch of the probe data is collected for the predetermined period of time,

wherein the batch of the probe data is designated as a jam slice when any traffic jam is determined to occur in the roadway based on the batch of the probe data,

wherein each probe data in each jam slice is a probe point collected from the one or more vehicles at a point in time that records telemetry data for the one or more vehicles for that point in time,

wherein the jam slice is added to a jam group associated with the traffic jam if the jam slice relates to the traffic jam, and

wherein a new jam group including the jam slice is created if the jam slice relates to another traffic jam.

2. The method of claim 1, further comprising:

determining a downstream area of the roadway, wherein the downstream area corresponds to one or more other segments of the roadway downstream from the jam area; and

determining another set of features indicated by the probe data from another portion of the probe data collected from the downstream area,

wherein the classifying of the traffic jam is further based on the another set of features.

3. The method of claim 2, further comprising:

classifying the non-recurring traffic jam as an accident-caused traffic jam based on the set of features, the another set of features, or a combination thereof.

4. The method of claim 2, further comprising:

classifying a severity level of the traffic jam based on the set of features, the another set of features, or a combination thereof.

5. The method of claim 2, wherein the set of features includes a jam normalized speed, a jam speed, a jam probe point density, a density of distinct probe points in the jam area, or a combination thereof;

and wherein the another set of features includes a downstream normalized speed, a downstream speed, a downstream probe point density, a density of distinct probe points in the downstream area, a ratio of the downstream stream speed to a jam speed, a ratio of the downstream point density to a jam probe point density, a ratio of the density of distinct probe points in the downstream area to a density of the distinct probe points in the jam area, a variance of a jam-downstream border, a jam length, or a combination thereof.

6. The method of claim 1, wherein the roadway represents one or more lanes of a multi-lane roadway, and wherein the classifying of the traffic jam indicates on which of the one of the more lanes of the multi-lane roadway the traffic jam is detected.

7. The method of claim 1, wherein the classifying of the traffic jam is performed based on the jam group.

8. The method of claim 7, further comprising:

initiating the classifying of the traffic jam when a count of jam slices in the jam group reaches a candidate size value of at least 3.

9. The method of claim 8, further comprising:

determining the candidate size value based on a target response time for the classifying of the traffic jam.

10. The method of claim 1, further comprising:

presenting a result of the classifying of the traffic jam in a map user interface depicting the roadway.

11. An apparatus comprising:

a processor; and

a memory including computer program code for a program,

the memory and the computer program code configured to, with the processor, cause the apparatus to perform at least the following,

receive probe data that is map-matched to a roadway on which a traffic jam is detected, wherein the probe data is collected from one or more vehicles traveling the roadway;

determine a jam area of the roadway based on the probe data, wherein the jam area corresponds to one or more segments of the roadway affected by the traffic jam;

determine a set of features indicated by the probe data from a portion of the probe data collected from the jam area; and

classify the traffic jam as either a recurring traffic jam or a non-recurring traffic jam based on the set of features,

wherein the probe data is received from the one or more vehicles on a continuous batch basis,

wherein a batch of the probe data is collected for a predetermined period of time before the batch is processed and a next batch of the probe data is collected for the predetermined period of time,

wherein the batch of the probe data is designated as a jam slice when any traffic jam is determined to occur in the roadway based on the batch of the probe data,

wherein each probe data in each jam slice is a probe point collected from the one or more vehicles at a point in time that records telemetry data for the one or more vehicles for that point in time,

wherein the jam slice is added to a jam group associated with the traffic jam if the jam slice relates to the traffic jam, and

wherein a new jam group including the jam slice is created if the jam slice relates to another traffic jam.

12. The apparatus of claim 11, wherein the apparatus is further caused to:

determine a downstream area of the roadway, wherein the downstream area corresponds to one or more other segments of the roadway downstream from the jam area; and

determine another set of features indicated by the probe data from another portion of the probe data collected from the downstream area,

wherein the classifying of the traffic jam is further based on the another set of features.

13. The apparatus of claim 12, wherein the apparatus is further caused to:

classify the non-recurring traffic jam as an accident-caused traffic jam based on the set of features, the another set of features, or a combination thereof.

14. The apparatus of claim 12, wherein the apparatus is further caused to:

classify a severity level of the traffic jam based on the set of features, the another set of features, or a combination thereof.

15. The apparatus of claim 11, wherein the roadway represents one or more lanes of a multi-lane roadway, and wherein the classifying of the traffic jam indicates on which of the one of the more lanes of the multi-lane roadway the traffic jam is detected.

16. The apparatus of claim 11, wherein the classifying of the traffic jam is performed based on the jam group.

17. The apparatus of claim 16, wherein the apparatus is further caused to:

initiate the classifying of the traffic jam when a count of jam slices in the jam group reaches a candidate size of at least 3.

18. A non-transitory computer-readable storage medium carrying one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to at least perform the following steps:

receiving probe data that is map-matched to a roadway on which a traffic jam is detected, wherein the probe data is collected from one or more vehicles traveling the roadway;

determining a jam area of the roadway based on the probe data, wherein the jam area corresponds to one or more segments of the roadway affected by the traffic jam;

determining a set of features indicated by the probe data from a portion of the probe data collected from the jam area; and

classifying the traffic jam as either a recurring traffic jam or a non-recurring traffic jam based on the set of features,

wherein the probe data is received from the one or more vehicles on a continuous batch basis,

wherein a batch of the probe data is collected for a predetermined period of time before the batch is processed and a next batch of the probe data is collected for the predetermined period of time,

wherein the batch of the probe data is designated as a jam slice when any traffic jam is determined to occur in the roadway based on the batch of the probe data,

wherein each probe data in each jam slice is a probe point collected from the one or more vehicles at a point in time that records telemetry data for the one or more vehicles for that point in time,

wherein the jam slice is added to a jam group associated with the traffic jam if the jam slice relates to the traffic jam, and

wherein a new jam group including the jam slice is created if the jam slice relates to another traffic jam.

19. The computer-readable storage medium of claim 18, wherein the apparatus is further caused to perform:

determining a downstream area of the roadway, wherein the downstream area corresponds to one or more other segments of the roadway downstream from the jam area; and

determining another set of features indicated by the probe data from another portion of the probe data collected from the downstream area,

wherein the classifying of the traffic jam is further based on the another set of features.

20. The computer-readable storage medium of claim 19, wherein the apparatus is further caused to perform:

classifying the non-recurring traffic jam as an accident-caused traffic jam based on the set of features, the another set of features, or a combination thereof.