Detecting anomalous road traffic conditions

• US 7,899,611 B2
• Filed: 11/03/2006
• Issued: 03/01/2011
• Est. Priority Date: 03/03/2006
• Status: Expired due to Fees

• Current Assignee: Inrix Incorporated
• Original Assignee: Inrix Incorporated
• Inventors: Cahn, Robert C., Barker, Alec, Stoppler, Wayne, Downs, Oliver B., Chapman, Craig H.
• Primary Examiner(s): Tran; Khoi
• Assistant Examiner(s): Broadhead; Brian J
• Application Number:
  US11/556,648
• Publication Number:
  US 20070208497A1
• Time in Patent Office: 1,579 Days
• Field of Search: 701/117, 701/119
• US Class Current: 701/117
• CPC Class Codes: G08G 1/0104 Measuring and analyzing of parameters relative to traffic conditions
• CPC Class Codes: G08G 1/0962 having an indicator mounted inside the vehicle, e.g. giving voice messages
• CPC Class Codes: G08G 1/0968 Systems involving transmission of navigation instructions to the vehicle
• CPC Class Codes: G08G 1/0969 having a display in the form of a map

Abstract

Techniques are described for automatically detecting anomalous road traffic conditions and for providing information about the detected anomalies, such as for use in facilitating travel on roads of interest. Anomalous road traffic conditions may be identified using target traffic conditions for a particular road segment at a particular selected time, such as target traffic conditions that reflect actual traffic conditions for a current or past selected time, and/or target traffic conditions that reflect predicted future traffic conditions for a future selected time. Target traffic conditions may be compared to distinct expected road traffic conditions for a road segment at a selected time, with the expected conditions reflecting road traffic conditions that are typical or normal for the road segment at the selected time. Anomalous conditions may be identified based on sufficiently large differences from the expected conditions, and information about the anomalous conditions may be provided in various ways.

Claims

1. A computer-implemented method for automatically identifying abnormal traffic conditions on roads, the method comprising:

receiving information describing a network of roads in a geographic area;

for each of the roads in the network, identifying multiple segments of the road for which traffic conditions are distinctly tracked;

for each of multiple users, receiving a request from the user to be notified of abnormal traffic conditions that occur on one or more indicated road segments, wherein the received request from a first user of the multiple users includes an indication from the first user of a first specified amount of difference between actual and expected average traffic speeds for the first user; and

facilitating navigation of vehicles over the network of roads using information about automatically identified abnormal traffic conditions on the roads, the facilitating of the navigation of the vehicles being performed automatically by one or more programmed computing systems and including, for each of at least some of the road segments,

obtaining information indicating current actual traffic conditions for the road segment, the current actual traffic conditions including an actual average traffic speed of vehicles traveling on the road segment at a current time;

obtaining information indicating expected traffic conditions for the current time for the road segment, the expected traffic conditions reflecting a generated forecast of traffic conditions that includes an expected average traffic speed of vehicles traveling on the road segment at the current time;

automatically identifying whether the current actual traffic conditions for the road segment at the current time are abnormal with respect to the expected traffic conditions for the road segment for the current time, the identifying being based at least in part on generated comparative information for the road segment that indicates a difference between the actual and expected average traffic speeds of vehicles traveling on the road segment, wherein the identifying of whether current actual traffic conditions for a road segment are abnormal based at least in part on generated comparative information for the road segment that indicates a difference between the actual and expected average traffic speeds of vehicles traveling on the road segment includes, for the multiple users other than the first user, determining whether the difference exceeds a predetermined amount and includes, for the first user, determining whether the difference exceeds the first specified amount; and

if the current actual traffic conditions for the road segment are identified as abnormal, and if one or more users has requested to be notified of abnormal traffic conditions on the road segment, providing information about the abnormal current actual traffic conditions to each of the one or more users, wherein the providing of the information about the abnormal current actual traffic conditions to each of the one or more users includes providing a notification to the first user if the difference between the actual and expected average traffic speeds of vehicles traveling on one or more of the at least some road segments exceeds the first specified amount.

2. The method of claim 1 wherein at least some of the received requests from the users each indicate road segments of interest by indicating one or more routes on the network of roads, and wherein the at least some road segments include the indicated road segments of interest.

3. The method of claim 2 wherein the at least some received requests each indicate a notification mechanism to use for notifying of abnormal traffic conditions, and wherein the providing of information about abnormal current actual traffic conditions to a user whose request indicates a notification mechanism is performed in a manner so as to use the indicated notification mechanism.

4. The method of claim 3 wherein the at least some received requests each indicate one or more times of interest, and wherein the providing of information about abnormal current actual traffic conditions to a user whose request indicates one or more times of interest is performed only if the current time is one of the indicated times of interest.

5. The method of claim 4 wherein the facilitating of the navigation of vehicles over the network of roads using information about automatically identified abnormal traffic conditions on the roads is performed repeatedly at each of multiple distinct times such that the current time changes for each performance.

6. The method of claim 1 wherein the generated forecast traffic conditions for the at least some road segments are default forecast traffic conditions generated by one or more predictive models using input information related to traffic conditions at the current time, wherein the input information includes information about time-of-day of the current time, about day-of-week of the current time, about school schedules in the geographic area at the current time, and about holiday schedules in the geographic area at the current time, and wherein the input information does not include information about current conditions at a time of generating the forecast traffic conditions, the current conditions including current traffic conditions, current traffic incidents, and current weather conditions.

7. The method of claim 6 wherein at least one of the one or more predictive models uses a Bayesian network to probabilistically generate the forecast traffic conditions.

8. The method of claim 1 wherein the providing of information about abnormal traffic conditions to each of one or more users includes at least one of sending an electronic message to the user with the information about the abnormal traffic conditions and initiating a display to the user of the information about the abnormal traffic conditions.

9. A computer-implemented method for automatically identifying abnormal traffic conditions on roads so as to facilitate travel, the method comprising:

receiving indications of multiple road segments of multiple related roads;

receiving information from a user that identifies traffic conditions that are considered to be normal by the user for one of the multiple road segments;

obtaining information about expected traffic conditions for each of the road segments for a current time, the expected traffic conditions reflecting traffic conditions that are normal for the road segments at the current time, wherein the obtained expected traffic conditions for the one road segment for the current time are based at least in part on the received information from the user;

obtaining information about target traffic conditions for each of the road segments for the current time for comparison to the expected traffic conditions for the road segments, the target traffic conditions reflecting actual traffic conditions on the road segments;

for each of the multiple road segments, comparing the target traffic conditions for the road segment for the current time to the expected traffic conditions for the road segment for the current time to automatically determine whether the target traffic conditions are abnormal with respect to normal traffic conditions for the current time, the automatic determining of whether the target traffic conditions are abnormal with respect to normal traffic conditions for the current time being performed by one or more computing systems, wherein the automatic determining that target traffic conditions for the one road segment are abnormal with respect to normal traffic conditions for the one road segment is performed on behalf of the user; and

providing indications of the road segments whose target traffic conditions are determined to be abnormal for the current time to facilitate travel on the roads, wherein the providing of the indications of the road segments whose target traffic conditions are determined to be abnormal for the current time includes providing notification to the user if the target traffic conditions for the one road segment that reflect the actual traffic conditions on the one road segment differ from the identified traffic conditions that are considered to be normal by the user for the one road segment by more than a determined amount.

10. The method of claim 9 wherein the automatic determining that target traffic conditions for a road segment are abnormal with respect to normal traffic conditions for the road segment includes determining that the target traffic conditions are better than the normal traffic conditions by at least a minimum amount.

11. The method of claim 9 wherein the automatic determining that target traffic conditions for a road segment are abnormal with respect to normal traffic conditions for the road segment includes determining that the target traffic conditions are worse than the normal traffic conditions by at least a minimum amount.

12. The method of claim 9 wherein, for each of the multiple road segments, the comparing of the target traffic conditions for the road segment for the current time to the expected traffic conditions for the road segment for the current time includes generating comparative information that includes a numerical difference between the target and expected traffic conditions for the road segment.

13. The method of claim 12 wherein, for each of one or more of the multiple road segments, the target traffic conditions are determined to be abnormal with respect to normal traffic conditions if the numerical difference between the target and expected traffic conditions for the road segment exceeds a predetermined quantity.

14. The method of claim 12 wherein the providing of the indications of the road segments whose target traffic conditions are determined to be abnormal includes providing indications of the generated comparative information for at least some of the multiple road segments.

15. The method of claim 9 wherein, for each of the multiple road segments, the comparing of the target traffic conditions for the road segment for the current time to the expected traffic conditions for the road segment for the current time includes using one or more statistical measures to determine whether the target traffic conditions for the road segment are abnormal.

16. The method of claim 15 wherein the target and expected traffic conditions for the current time for the multiple road segments are each represented as a distribution of traffic speeds of vehicles traveling on the road segment at the current time, and wherein the one or more statistical measures include at least one statistical difference measure to determine an amount of difference between the target and expected traffic speed distributions for a road segment.

17. The method of claim 15 wherein the target and expected traffic conditions for the current time for the multiple road segments each have an associated probability distribution, and wherein the one or more statistical measures used to determine whether the target traffic conditions for a road segment are abnormal are applied at least in part to the associated probability distributions for the target and expected traffic conditions for the road segment.

18. The method of claim 9 wherein, for each of the multiple road segments, the automatic determining of whether the target traffic conditions for the current time for the road segment are abnormal is further based at least in part on information about traffic conditions for one or more other road segments adjoining the road segment.

19. The method of claim 18 wherein the information about traffic conditions for one or more other road segments adjoining a road segment includes information about abnormal traffic conditions for the current time for the one or more other road segments.

20. The method of claim 9 wherein, for each of the multiple road segments, the automatic determining of whether the target traffic conditions for the current time for the road segment are abnormal is further based at least in part on use of an automated classifier, the classifier using at least one of a probabilistic Bayesian network, a decision tree, a neural network, and a support vector machine.

21. The method of claim 9 wherein the obtained information about the target traffic conditions for at least some of the road segments that reflect actual traffic conditions for the at least some road segments includes measurements of actual traffic conditions on the at least some road segments that are taken within a predetermined amount of time from the current time.

22. The method of claim 9 wherein the obtained information about expected traffic conditions for at least some of the road segments includes forecasted traffic conditions information based on use of at least one predictive model whose input information includes information about conditions affecting traffic on the roads.

23. The method of claim 22 wherein the obtaining of the information about the expected traffic conditions for the road segments includes generating the information about the expected traffic conditions based at least in part on use of the at least one predictive models.

24. The method of claim 22 wherein the input information to the at least one predictive model does not include multiple of current traffic conditions, current weather conditions, current traffic incidents, future expected weather conditions, and future events that are scheduled to occur.

25. The method of claim 22 wherein the input information to the at least one predictive model includes multiple of a time-of-day for the current time, a day-of-week for the current time, a month-of-year for the current time, a holiday schedule, and a school schedule.

26. The method of claim 22 wherein the at least one predictive model includes a probabilistic Bayesian network.

27. The method of claim 9 wherein the obtained information about expected traffic conditions for each of at least some of the road segments includes information about historical average traffic conditions based on an aggregation of actual traffic conditions that have been previously observed on the road segment.

28. The method of claim 9 further comprising receiving an indication of a selected future time, comparing predicted traffic conditions on each of one or more road segments at the selected future time to normal traffic conditions on that road segment at that future time so as to automatically determine whether the predicted traffic conditions at that future time on that road segment are abnormal with respect to the normal traffic conditions at that future time on that road segment, and providing indications of the road segments whose predicted traffic conditions at the selected future time are determined to be abnormal.

29. The method of claim 28 wherein the predicted traffic conditions on each of the one or more road segments at the selected future time are predictions that are generated for the road segment for the future time based in part on current conditions at a time of the generating.

30. The method of claim 28 wherein the normal traffic conditions on each of the one or more road segments at the selected future time are forecasts that are generated for the road segment for the future time without using current traffic conditions at a time of the generating.

31. The method of claim 9 wherein the expected traffic conditions for each of the road segments include expected average traffic speed for the road segment, and wherein the target traffic conditions for each of the road segments include actual average traffic speed for the road segment.

32. The method of claim 9 wherein the expected traffic conditions for each of the road segments include expected traffic volume for the road segment during a period of time, and wherein the target traffic conditions for each of the road segments include actual traffic volume for the road segment during the period of time.

33. The method of claim 9 wherein the expected traffic conditions for each of the road segments include expected traffic occupancy percentage for at least one location of the road segment during a period of time, and wherein the target traffic conditions for each of the road segments include actual traffic occupancy percentage for at least one location of the road segment during the period of time.

34. The method of claim 9 wherein one or more users have each requested notification of abnormal traffic conditions for at least one selected road segment, and wherein the providing of the indications of the road segments whose target traffic conditions are determined to be abnormal includes sending one or more electronic messages to each of the one or more users who have selected at least one of the road segments whose target traffic conditions are determined to be abnormal.

35. The method of claim 9 wherein the providing of the indications of one or more of the road segments whose target traffic conditions are determined to be abnormal includes initiating display to each of one or more users of a map that includes representations of the one or more road segments, the map indicating for each of the one or more road segments a numerical difference between the target traffic conditions for the road segment and the expected traffic conditions for the road segment.

36. The method of claim 9 further comprising, after automatically determining that the target traffic conditions for one or more of the road segments are abnormal, automatically inferring an occurrence of a traffic incident based at least in part on the determination of the abnormality of the target traffic conditions for the one or more road segments.

37. A computer-implemented method for automatically identifying abnormal traffic conditions on roads so as to facilitate travel, the method comprising:

receiving indications of multiple road segments of multiple related roads;

obtaining information about expected traffic conditions for each of the road segments for a current time, the expected traffic conditions reflecting traffic conditions that are normal for the road segments at the current time;

obtaining information about target traffic conditions for each of the road segments for the current time for comparison to the expected traffic conditions for the road segments, the target traffic conditions reflecting actual traffic conditions on the road segments;

for each of the multiple road segments, comparing the target traffic conditions for the road segment for the current time to the expected traffic conditions for the road segment for the current time to automatically determine whether the target traffic conditions are abnormal with respect to normal traffic conditions for the current time, the automatic determining of whether the target traffic conditions are abnormal with respect to normal traffic conditions for the current time being performed by one or more computing systems;

providing indications of the road segments whose target traffic conditions are determined to be abnormal for the current time to facilitate travel on the roads; and

receiving an indication of a selected past time, comparing actual traffic conditions on each of one or more road segments at the selected past time to normal traffic conditions on that road segment at that past time so as to automatically determine whether the actual traffic conditions at that past time on that road segment are abnormal with respect to the normal traffic conditions at that past time on that road segment, and providing indications of the road segments whose actual traffic conditions at the selected past time are determined to be abnormal.

38. A non-transitory computer-readable storage medium whose stored contents configure a computing device to automatically identify abnormal traffic conditions on roads so as to facilitate travel, by performing a method comprising:

receiving indications of multiple road segments;

obtaining information about expected traffic conditions for each of the road segments for a current time, the expected traffic conditions reflecting traffic conditions that are normal for the road segments at the current time, the traffic conditions that are normal for the road segments at the current time including information specific to a first user that indicates traffic conditions for at least one of the road segments that are normal for the first user for the at least one road segments at the current time;

obtaining information about target traffic conditions for each of the road segments for the current time for comparison to the expected traffic conditions for the road segments, the target traffic conditions reflecting actual traffic conditions on the road segments;

for each of the multiple road segments, comparing the target traffic conditions for the road segment for the current time to the expected traffic conditions for the road segment for the current time to automatically determine whether the target traffic conditions are abnormal with respect to normal traffic conditions for the current time, the automatic determining of whether the target traffic conditions are abnormal with respect to normal traffic conditions for the current time including determining whether the indicated traffic conditions for the at least one road segments that are normal for the first user differ by at least a determined amount from the target traffic conditions for the at least one road segments for the current time; and

providing indications of the road segments whose target traffic conditions are determined to be abnormal, the providing of the indications including notifying the first user if the target traffic conditions for one or more of the at least one road segments for the current time are determined to differ by at least the determined amount from the indicated traffic conditions for the at least one road segments that are normal for the first user.

39. The non-transitory computer-readable storage medium of claim 38 wherein, for each of at least one of the multiple road segments, the comparing of the target traffic conditions for the road segment for the current time to the expected traffic conditions for the road segment for the current time includes generating comparative information that includes a numerical difference between the target and expected traffic conditions for the road segment, and wherein the providing of the indications of the road segments whose target traffic conditions are determined to be abnormal includes providing indications of the generated comparative information for one or more of the at least one road segments.

40. The non-transitory computer-readable storage medium of claim 38 wherein the obtained information about the target traffic conditions for at least some of the road segments includes measurements of actual traffic conditions on the at least some road segments that are taken within a predetermined amount of time from the current time, and wherein the obtained information about expected traffic conditions for the at least some road segments includes forecasted traffic conditions information based on use of at least one predictive model whose input information includes information about conditions affecting traffic on the roads.

41. The non-transitory computer-readable storage medium of claim 38 wherein the method further comprises receiving an indication of a selected past time, comparing actual traffic conditions on each of one or more road segments at the selected past time to normal traffic conditions on that road segment at that past time so as to automatically determine whether the actual traffic conditions at that past time on that road segment are abnormal with respect to the normal traffic conditions at that past time on that road segment, and providing indications of the road segments whose actual traffic conditions at the selected past time are determined to be abnormal.

42. The non-transitory computer-readable storage medium of claim 38 wherein the method further comprises receiving an indication of a selected future time, comparing predicted traffic conditions on each of one or more road segments at the selected future time to normal traffic conditions on that road segment at that future time so as to automatically determine whether the predicted traffic conditions at that future time on that road segment are abnormal with respect to the normal traffic conditions at that future time on that road segment, and providing indications of the road segments whose predicted traffic conditions at the selected future time are determined to be abnormal.

43. The non-transitory computer-readable storage medium of claim 38 wherein the providing of the indications of one or more of the road segments whose target traffic conditions are determined to be abnormal includes initiating display to each of one or more users that include the first user of a map that includes representations of the one or more road segments, the map indicating for each of the one or more road segments a numerical difference between the target traffic conditions for the road segment and the expected traffic conditions for the road segment.

44. The non-transitory computer-readable storage medium of claim 38 wherein the computer-readable medium is a memory of the computing device, and wherein the contents are instructions that when executed cause the computing device to perform the method.

45. A computing device configured to automatically identify abnormal traffic conditions on roads so as to facilitate travel, comprising:

one or more processors; and

a first component configured to, when executed by at least one of the one or more processors, and for each of multiple indicated road segments;

receive information from a user that identifies traffic conditions that are considered to be normal by the user for the road segment;

obtain information about expected traffic conditions for the road segment for a current time, the expected traffic conditions reflecting traffic conditions that are normal for the road segment at the current time and being based at least in part on the received information from the user;

obtain information about target traffic conditions for the road segment for the current time for comparison to the expected traffic conditions for the road segment, the target traffic conditions reflecting actual traffic conditions on the road segment;

compare the target traffic conditions for the road segment for the current time to the expected traffic conditions for the road segment for the current time to automatically determine that the target traffic conditions are abnormal with respect to normal traffic conditions for the current time, the automatic determining that the target traffic conditions are abnormal being performed on behalf of the user; and

provide an indication of the road segment having target traffic conditions that are determined to be abnormal, wherein the providing of the indication includes providing notification to the user if the target traffic conditions differ from the expected traffic conditions by more than a determined amount.

46. The computing device of claim 45 wherein the first component includes software instructions for execution by the at least one processors of the computing device.