Identifying unrepresentative road traffic condition data obtained from mobile data sources

• US 20070208493A1
• Filed: 05/11/2006
• Published: 09/06/2007
• Est. Priority Date: 03/03/2006
• Status: Abandoned Application

• Current Assignee: Inrix Incorporated
• Original Assignee: Inrix Incorporated
• Inventors: Cahn, Robert, Hersch, Jesse, Chapman, Craig, Downs, Oliver
• Application Number:
  US11/431,980
• Publication Number:
  US 20070208493A1
• Time in Patent Office: Days
• US Class Current: 701/117
• CPC Class Codes: G08G 1/0104 Measuring and analyzing of parameters relative to traffic conditions

Abstract

Techniques are described for assessing road traffic conditions in various ways based on obtained traffic-related data, such as data samples from vehicles and other mobile data sources traveling on the roads, as well as in some situations data from one or more other sources (such as physical sensors near to or embedded in the roads). The assessment of road traffic conditions based on obtained data samples may include various filtering and/or conditioning of the data samples, and various inferences and probabilistic determinations of traffic-related characteristics of interest from the data samples. In some situations, the filtering of the data samples includes identifying data samples that are inaccurate or otherwise unrepresentative of actual traffic condition characteristics of interest, such as by identifying data samples that are statistical outliers with respect to other data samples.

Claims

1. A computer-implemented method for assessing data samples reported by vehicles traveling on roads, the data samples including information regarding the travel of the vehicles, the method comprising:

receiving indications of multiple road segments of one or more roads;

receiving information related to current traffic conditions of the multiple road segments, the received information including a plurality of data samples that each are reported from one of multiple vehicles and reflect a reported speed of the one vehicle at a reported location related to one of the road segments at a reported time; and

for each of the multiple road segments, assessing traffic conditions for the road segment based on data samples identified to represent travel on the road segment by,

identifying a group of multiple data samples from the plurality of data samples such that the data samples of the group have reported locations that correspond to travel on the road segment;

for each of the data samples in the group, determining an average speed and standard deviation for all other data samples of the group based on the reported speeds for those data samples, and determining whether the data sample is a statistical outlier relative to the other data samples of the group based on how a difference in the reported speed of the data sample and the determined average speed compares to the determined standard deviation;

excluding from the group the data samples determined to be statistical outliers; and

after the excluding, using the data samples remaining in the group to infer traffic conditions for all vehicles traveling on the road segment, so that the inferred traffic conditions based on the data samples are available for use in facilitating travel on the road segment.

2. The method of claim 1 wherein the assessing of the traffic conditions for each of the multiple road segments is performed for each of multiple distinct periods of time, and wherein the identifying of the group of data samples for a road segment for a period of time is further performed such that the identified data samples of the group have reported times that correspond to the period of time.

3. The method of claim 1 wherein, for each of at least one of the multiple road segments, one of the data samples of the identified group for the one road segment that is determined to be a statistical outlier is a data sample that is from a vehicle traveling on another road segment and that is incorrectly associated with the one road segment.

4. The method of claim 1 wherein, for each of at least one of the multiple road segments, one of the data samples of the identified group for the one road segment that is determined to be a statistical outlier is a data sample from a vehicle that is parked on or by the one road segment.

5. The method of claim 1 wherein the assessing of the traffic conditions for each of the multiple road segments includes determining an average speed and a standard deviation for all of the data samples of the identified group for the road segment, and using the determined average speed and standard deviation for all of the data samples as part of the determining, for each of the data samples of the identified group, of the average speed and standard deviation for all the other data samples of the group.

6. The method of claim 5 wherein the determining of whether a data sample of a group is a statistical outlier relative to the other data samples of the group includes determining whether the difference in the reported speed of the data sample and the determined average speed of the other data samples of the group exceeds a threshold based on the determined standard deviation for the other data samples of the group.

7. The method of claim 1 wherein data samples related to current traffic conditions of the multiple road segments are repeatedly received to reflect changing traffic conditions, and wherein the assessing of the traffic conditions for each of the multiple road segments is performed for recently received data samples in a realtime manner.

8. The method of claim 7 wherein the using of data samples remaining in a group to infer traffic conditions for all vehicles traveling on a road segment includes determining an average speed for the remaining data samples, inferring an average speed for all vehicles traveling on the road segment based on the determined average speed, and providing information about the inferred average speed to one or more people considering upcoming travel on the road segment.

9. A computer-implemented method for assessing data samples representing vehicles traveling on roads, the method comprising:

receiving indications of one or more segments of one or more roads, each road segment having multiple associated data samples that each reflect a reported speed of a vehicle on the road segment; and

for each of at least one of the road segments,

automatically analyzing the multiple associated data samples for the road segment so as to determine one or more of those data samples that are unrepresentative of actual vehicle travel on the road segment, at least one of the determined data samples being a statistical outlier with respect to other of the multiple associated data samples; and

providing one or more indications to exclude the determined data samples from later use so that the other data samples are available for use in facilitating travel on the road segment.

10. The method of claim 9 wherein, for one or more of the at least one road segments, the providing of the indications to exclude the determined data samples from later use includes analyzing the associated data samples for the road segment other than the determined data samples in order to determine an average speed of vehicles traveling on the road segment, and includes indicating the determined average speed for use in facilitating travel of other vehicles on the road segment.

11. The method of claim 9 wherein, for one or more of the at least one road segments, the providing of the indications to exclude the determined data samples from later use includes analyzing the associated data samples for the road segment other than the determined data samples in order to determine traffic flow of vehicles traveling on the road segment, and includes indicating the determined traffic flow for use in facilitating travel of other vehicles on the road segment.

12. The method of claim 9 wherein, for one or more of the at least one road segments, the determining of the one or more data samples for the road segment that are unrepresentative of actual vehicle travel on the road segment includes determining that each of those data samples is a statistical outlier with respect to other of the multiple data samples associated with the road segment.

13. The method of claim 12 wherein the determining that a data sample associated with a road segment is a statistical outlier with respect to other of the multiple data samples associated with the road segment is performed using leave-one-out outlier analysis.

14. The method of claim 12 wherein the determining that a data sample associated with a road segment is a statistical outlier with respect to other of the multiple data samples associated with the road segment is based at least in part on the reported speeds reflected by each of the data samples.

15. The method of claim 12 wherein the determining that each of the one or more data samples for a road segment is a statistical outlier with respect to other of the multiple data samples associated with the road segment includes:

determining an average speed and a standard deviation for all of the multiple data samples for the road segment; and

for each of the one or more data samples for the road segment,

determining an average speed and a standard deviation for all other of the multiple data samples for the road segment based on the determined average speed and standard deviation for all of the multiple data samples for the road segment;

determining a difference between the reported speed for the data sample and the determined average speed for all other of the multiple data samples for the road segment;

determining a threshold based at least in part on the determined standard deviation for all other of the multiple data samples for the road segment; and

when the determined difference exceeds the determined threshold, identifying the data sample as a statistical outlier.

16. The method of claim 12 wherein, for each of the one or more road segments, the determining that each of the one or more data samples for the road segment is a statistical outlier with respect to other of the multiple data samples associated with the road segment is performed in a substantially realtime manner.

17. The method of claim 9 wherein, for one or more of the at least one road segments, the determining of the one or more data samples for the road segment that are unrepresentative of actual vehicle travel on the road segment includes assessing an activity of each vehicle whose reported speed is reflected by at least one of the determined data samples and determining that the assessed activity of each of the vehicles does not correspond to actual vehicle travel on the road segment.

18. The method of claim 17 wherein the assessed activity of at least one of the vehicles corresponds to a parked vehicle.

19. The method of claim 17 wherein the assessed activity of at least one of the vehicles based on one or more determined data samples corresponds to travel on a road segment other than a road segment with which the one or more determined data samples are associated.

20. The method of claim 9 wherein, for one or more of the at least one road segments, the determining of one or more data samples for the road segment that are unrepresentative of actual vehicle travel on the road segment includes identifying multiple data samples that are reported by a single vehicle traveling on the road segment, determining an activity of the single vehicle over time based on the identified data samples, and determining that the identified data samples are unrepresentative of actual vehicle travel on the road segment based on the determined activity.

21. The method of claim 9 wherein, for one or more of the at least one road segments, the determining of one or more data samples for the road segment that are unrepresentative of actual vehicle travel on the road segment includes identifying expected values for the multiple data samples associated with the road segment and determining that the determined data samples do not fit the identified expected values.

22. The method of claim 9 wherein, for one or more of the at least one road segments, the determining of one or more data samples for the road segment that are unrepresentative of actual vehicle travel on the road segment includes determining a statistical distribution for the multiple data samples associated with the road segment and determining that the determined data samples do not fit the determined statistical distribution.

23. The method of claim 9 wherein, for one or more of the at least one road segments, the determining of one or more data samples for the road segment that are unrepresentative of actual vehicle travel on the road segment includes identifying multiple distinct data curves for the road segment, each of the data curves reflecting a distinct subset of vehicle travel on at least a portion of the road segment, and wherein the determined data samples fit at least one of the data curves that reflects a subset of vehicle travel that is not of interest.

24. The method of claim 23 wherein at least one of the identified data curves is a Gaussian curve.

25. The method of claim 9 wherein, for one or more of the at least one road segments, the multiple associated data samples for the road segment each further reflect a reported time corresponding to the reported speed of the vehicle for the data sample, the automatic analyzing of the multiple associated data samples for the road segment further corresponding to a predetermined period of time such that the actual vehicle travel on the road segment is travel during the predetermined period of time.

26. The method of claim 25 wherein, for each of the one or more road segments, the determining of the one or more data samples for the road segment that are unrepresentative of actual vehicle travel on the road segment includes identifying that the reported time for each of the determined data samples is not within the predetermined period of time for the road segment.

27. The method of claim 9 further comprising, for each of multiple distinct periods of time, receiving multiple associated data samples for one of the road segments that each reflect a reported speed of a vehicle at a reported time on the one road segment during the period of time, and wherein the automatic analyzing is performed for the one road segment for each of the periods of time based on the data samples whose reported times are during the period of time.

28. The method of claim 9 wherein, for one or more of the at least one road segments, the determining of one or more data samples for the road segment that are unrepresentative of actual vehicle travel on the road segment is performed in a substantially realtime manner.

29. The method of claim 28 wherein at least some of the multiple data samples associated with at least some of the road segments are acquired by and reported from vehicles traveling on those road segments, the reporting of the at least some data samples occurring in a substantially realtime manner after acquisition of one or more of the at least one data samples.

30. A computer-readable medium whose contents enable a computing device to assess data samples representing traveling vehicles, by performing a method comprising:

receiving an indication of multiple data samples that each reflect reported travel characteristics of one of multiple vehicles traveling on a road;

automatically determine one or more of the multiple data samples that are unrepresentative of actual vehicle travel on the road; and

providing one or more indications of the data samples other than the determined data samples so that the indicated data samples are available for use in facilitating travel on the road.

31. The computer-readable medium of claim 30 wherein the reported travel characteristics of each data sample include reported speed of the vehicle to which the data sample corresponds, wherein the determining of at least one of the one or more data samples that are unrepresentative of actual vehicle travel on the road includes determining that the at least one data samples are statistical outliers with respect to other of the data samples, and wherein the providing of the indications of the data samples includes analyzing the data samples to determine average speed of vehicles traveling on the road and indicating the determined average speed for use in facilitating travel of other vehicles on the road.

32. The computer-readable medium of claim 31 wherein the determining that the at least one data samples are statistical outliers with respect to other of the data samples includes performing a leave-one-out outlier analysis in a substantially realtime manner.

33. The computer-readable medium of claim 30 wherein the computer-readable medium is a memory of a computing device.

34. The computer-readable medium of claim 30 wherein the computer-readable medium is a data transmission medium that transmits a generated data signal containing the contents.

35. The computer-readable medium of claim 30 wherein the contents are instructions that when executed cause the computing device to perform the method.

36. A computing system configured to assess data samples representing traveling vehicles, comprising:

a first component that is configured to, for each of multiple roads, receive an indication of multiple data samples for the road that each reflect a reported speed of a vehicle traveling on the road; and

a data sample outlier eliminator component that is configured to, for each of the multiple roads,

automatically determine one or more of the multiple data samples for the road that are statistical outliers with respect to other of the multiple data samples for the road; and

provide one or more indications of the multiple data samples for the road other than the determined data samples so that the indicated data samples are available for use in facilitating travel on the road.

37. The computing system of claim 36 wherein, for each of at least one of the multiple roads, the determining of the data samples for the road that are statistical outliers with respect to other of the data samples for the road includes performing a leave-one-out outlier analysis in a substantially realtime manner, and wherein the providing of the indications of the data samples for the road includes analyzing the data samples to determine average speed of vehicles traveling on the road and indicating the determined average speed for use in facilitating travel of other vehicles on the road.

38. The computing system of claim 36 wherein the first component and the data sample outlier eliminator component each include software instructions for execution in memory of the computing system.

39. The computing system of claim 36 wherein the first component consists of a means for, for each of multiple roads, receiving an indication of multiple data samples for the road that each reflect a reported speed of a vehicle traveling on the road, and wherein the data sample outlier eliminator component consists of a means for, for each of the multiple roads, automatically determining one or more of the multiple data samples for the road that are statistical outliers with respect to other of the multiple data samples for the road, and providing one or more indications of the multiple data samples for the road other than the determined data samples so that the indicated data samples are available for use in facilitating travel on the road.