Determining road traffic conditions using data from multiple data sources

• US 8,090,524 B2
• Filed: 03/21/2011
• Issued: 01/03/2012
• Est. Priority Date: 03/03/2006
• Status: Active Grant

• Current Assignee: Inrix Incorporated
• Original Assignee: Inrix Incorporated
• Inventors: Chapman, Craig H., Parikh, Kush G., Downs, Oliver B., Cahn, Robert C., Hersch, Jesse S.
• Primary Examiner(s): Beaulieu, Yonel
• Application Number:
  US13/052,953
• Publication Number:
  US 20110173015A1
• Time in Patent Office: 288 Days
• Field of Search: 701117-119, 701213-215, 701/207
• US Class Current: 701/117
• CPC Class Codes: G01C 21/3691 Retrieval, searching and output of information related to real-time traffic, weather, or environmental conditions arrangements for giving variable traffic instructions G08G1/09
• CPC Class Codes: G08G 1/00 Traffic control systems for road vehicles arrangement of road signs or traffic signals E01F9/00 ; automatic vehicle control B62D
• CPC Class Codes: G08G 1/0104 Measuring and analyzing of parameters relative to traffic conditions
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• 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 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0141 for traffic information dissemination
• CPC Class Codes: G08G 1/0968 Systems involving transmission of navigation instructions to the vehicle

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 and/or from one or more other sources (such as physical sensors near to or embedded in the roads). The road traffic conditions assessment 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 inferences include repeatedly determining current traffic flow characteristics and/or predicted future traffic flow characteristics for road segments of interest during time periods of interest, such as to determine average traffic speed, traffic volume and/or occupancy, and include weighting various data samples in various ways (e.g., based on a latency of the data samples and/or a source of the data samples).

Claims

1. A computer-implemented method for providing information related to vehicle travel on roads, the method comprising:

for each of one or more roads, providing information related to vehicle travel during a period of time on the road, by;

obtaining multiple data samples that are each of one of multiple types and that reflect travel characteristics of vehicles traveling on the road during the period of time, the obtained multiple data samples including multiple road traffic sensor readings that are each generated by one of one or more road traffic sensors associated with the road, the obtained multiple data samples further including multiple mobile data source data samples that are each reported by one of one or more mobile devices moving along the road;

automatically assessing the obtained data samples to identify a group of multiple data samples of multiple types to represent actual vehicle travel on the road during the period of time, the identifying of the group including excluding one or more data samples that are identified as being unrepresentative of actual vehicle travel on the road, the automatic assessing being performed by one or more programmed computing systems;

automatically analyzing the identified group of multiple data samples in order to determine one or more estimated measurements of actual traffic flow during the period of time on the road, the automatic analyzing being performed by the one or more programmed computing systems; and

providing one or more indications of the determined estimated actual traffic flow measurements for use in facilitating travel on the road.

2. The method of claim 1 wherein the providing of information related to vehicle travel during the period of time on a road is performed in at least one of a realtime and a near-realtime manner.

3. The method of claim 2 wherein the period of time is a current period of time, and wherein the providing of the information related to the vehicle travel in the at least one realtime and near-realtime manner includes providing during the current period of time the one or more indications of the determined estimated actual traffic flow measurements.

4. The method of claim 3 wherein the period of time is a period of 15 minutes or less.

5. The method of claim 2 wherein the providing of information related to vehicle travel during a period of time on a road is performed for each of multiple distinct periods of time, so as to repeatedly provide information related to the vehicle travel on the road in the at least one realtime and near-realtime manner.

6. The method of claim 1 wherein the providing of the one or more indications of the determined estimated actual traffic flow measurements includes providing the determined estimated actual traffic flow measurements to each of one or more users for display to the one or more users.

7. The method of claim 6 wherein the providing of information related to vehicle travel during the period of time is performed for each of multiple distinct segments of multiple distinct roads that are part of a network of roads in a geographic area, and wherein the providing of the determined estimated actual traffic flow measurements to each of one or more users for display includes providing to each of the users a graphical representation of the geographic area that includes graphical representations of the multiple roads and that includes graphical representations for each of multiple road segments of corresponding determined estimated actual traffic flow measurements for that road segment.

8. The method of claim 1 further comprising, for each of at least one of the one or more roads, automatically generating one or more predicted measurements of future traffic flow during each of one or more future periods of times on the road, and providing one or more indications of the generated predicted future traffic flow measurements for use in facilitating future travel on the at least one roads.

9. The method of claim 8 wherein the period of time for which the estimated actual traffic flow measurements are determined is a current period of time, and wherein the predicted future traffic flow measurements for the one or more future periods of times are generated during the current period of time and are based in part on the determined estimated actual traffic flow measurements for the current period of time.

10. The method of claim 9 wherein the predicted future traffic flow measurements for a road for the one or more future periods of times are further based in part on current conditions that include multiple of current weather, current events that are scheduled to occur, current school sessions that are scheduled to occur, current traffic accidents on the road, and current construction activities on the road.

11. The method of claim 1 wherein the period of time is a future period of time, and wherein the determining of the one or more estimated measurements of actual traffic flow on a road during the period of time includes predicting the one or more estimated actual traffic flow measurements so as to reflect actual traffic that will occur on the road during the future period of time.

12. The method of claim 1 wherein the automatic assessing of the obtained data samples for a road includes analyzing the mobile data source data samples of the obtained data samples to determine information about at least one of speed and direction of movement of the one or more mobile devices moving along the road.

13. The method of claim 1 wherein the one or more road traffic sensors associated with each of the one or more roads each include at least one of an embedded loop sensor, a camera, a radar ranging device, a motion sensor, and an RFID-based sensor to detect RFID-based tags in vehicles.

14. The method of claim 1 wherein the one or more mobile devices moving along the one or more roads each include at least one of a device with GPS capabilities and of a device with cellular telephone transmission capabilities.

15. The method of claim 1 wherein the one or more road traffic sensors associated with each of the one or more roads include one or more embedded loop sensors, one or more cameras, one or more radar ranging devices, one or more motion sensors, and one or more RFID-based sensors to detect RFID-based tags in vehicles.

16. The method of claim 15 wherein the one or more mobile devices moving along the one or more roads include one or more devices with GPS capabilities and one or more devices with cellular telephone transmission capabilities.

17. The method of claim 1 wherein the one or more mobile devices moving along the one or more roads each include at least one of a device with GPS capabilities and of a device with cellular telephone transmission capabilities.

18. The method of claim 1 wherein the determined estimated actual traffic flow measurements for a road during the period of time include one or more estimates of speeds of vehicles traveling on the road during the period of time.

19. The method of claim 18 wherein the determined estimated actual traffic flow measurements for a road during the period of time further include multiple of one or more estimates of a traffic arrival rate volume for the road during the period of time, of one or more estimates of traffic density for the road during the period of time, and of one or more estimates of percentage traffic occupancy of at least one point on the road during the period of time.

20. The method of claim 1 wherein the providing of the information related to vehicle travel during the period of time on a road is performed by an automated traffic information system as part of a fee-based service.

21. A non-transitory computer-readable medium whose contents configure a computing device to provide information related to vehicle travel on a road, by performing a method comprising:

receiving an indication of multiple data samples of multiple types that reflect travel characteristics of vehicles traveling on a road, the multiple data samples being based on at least one of data readings that are each generated by a traffic sensor associated with the road to indicate one or more measurements of traffic conditions on the road at an associated time and of information reported by one or more mobile devices moving along the road at one or more times;

automatically analyzing the multiple data samples of the multiple types in order to determine one or more estimated measurements of traffic conditions on the road during a period of time, the automatic analyzing being performed by the configured computing device; and

providing one or more indications of the determined estimated traffic conditions measurements.

22. The computer-readable medium of claim 21 wherein the multiple types include multiple types of traffic sensors associated with the road.

23. The computer-readable medium of claim 22 wherein the multiple types of traffic sensors include multiple of embedded loop sensors, cameras, radar ranging devices, motion sensors, and RFID-based sensors.

24. The computer-readable medium of claim 21 wherein the multiple types include multiple types of mobile devices moving along the road.

25. The computer-readable medium of claim 24 wherein the multiple types of mobile devices include devices with GPS capabilities and devices with cellular telephone transmission capabilities.

26. The computer-readable medium of claim 24 wherein the multiple types of mobile devices include multiple types of devices with GPS capabilities.

27. The computer-readable medium of claim 21 wherein the multiple types include one or more embedded loop sensors, one or more devices with GPS capabilities, and one or more devices with cellular telephone transmission capabilities.

28. The computer-readable medium of claim 21 wherein the providing of the one or more indications of the determined estimated traffic conditions measurements includes providing information about the determined estimated traffic conditions measurements to one or more users for use in facilitating travel by the one or more users on the road.

29. The computer-readable medium of claim 21 wherein the method further comprises automatically determining to replace the determined estimated traffic condition measurements from the automatic analyzing with other determined estimated traffic condition measurements for the road during the period of time that are based at least in part on historical information about traffic conditions related to the road, and wherein the provided one or more indications are of the other determined estimated traffic condition measurements.

30. The computer-readable medium of claim 29 wherein the historical information is based on at least one of historical traffic sensor readings from one or more traffic sensors associated with the road and of historical mobile data source data samples reported by one or more mobile devices that previously moved along the road.

31. The computer-readable medium of claim 29 wherein the multiple data samples of the multiple types include data samples from one or more types of mobile devices with GPS capabilities, and wherein the multiple data samples are received in a near-realtime manner after generation of those data samples by mobile devices of the one or more types.

32. The computer-readable medium of claim 29 wherein the multiple data samples of the multiple types include data samples from one or more types of devices with cellular telephone capabilities, and wherein the multiple data samples are received in a near-realtime manner after generation of those data samples by mobile devices of the one or more types.

33. The computer-readable medium of claim 21 wherein the method further comprises:

automatically determining estimated traffic condition measurements for the road during a second period of time based at least in part on historical information about prior traffic conditions for the road; and

providing one or more indications of the determined estimated traffic condition measurements for the road during the second period of time.

34. The computer-readable medium of claim 21 wherein the computer-readable medium is a memory of the configured computing device.

35. The computer-readable medium of claim 21 wherein the contents are instructions that when executed program the configured computing device to perform the method.

52. The computer-readable medium of claim 21 wherein the providing of the one or more indications of the determined estimated traffic conditions measurements includes providing to each of one or more users a graphical representation of a geographic area that includes at least some of the road, the provided graphical representation of the geographic area including graphical representations of the at least some of the road and of determined estimated traffic conditions measurements for the at least some of the road.

53. The computer-readable medium of claim 21 wherein the period of time is a future period of time, and wherein the determining of the estimated traffic conditions measurements on the road during the period of time includes predicting future traffic conditions on the road for the future period of time based in part on current traffic conditions on the road.

54. The computer-readable medium of claim 21 wherein the period of time is a current period of time, and wherein the method further comprises automatically generating one or more predicted traffic conditions on the road for a future period of time based in part on the determined estimated traffic conditions measurements for the current period of time.

55. The computer-readable medium of claim 54 wherein the predicted traffic conditions are further based in part on current conditions that include multiple of current weather, current events that are scheduled to occur, current school sessions that are scheduled to occur, current traffic accidents on the road, and current construction activities on the road.

56. The computer-readable medium of claim 21 wherein the period of time is a current period of time, and wherein the method further comprises automatically generating one or more predicted traffic conditions on one or more other roads that are distinct from the road for the current period of time based at least in part on the determined estimated traffic conditions measurements for the current period of time for the road.

57. The computer-readable medium of claim 56 wherein the predicted traffic conditions are further based in part on current conditions that include multiple of current weather, current events that are scheduled to occur, current school sessions that are scheduled to occur, current traffic accidents on the road, and current construction activities on the road.

58. The computer-readable medium of claim 21 wherein the determined estimated traffic conditions measurements for the road during the period of time include one or more estimates of speeds of vehicles traveling on the road during the period of time.

59. The computer-readable medium of claim 21 wherein the determined estimated traffic conditions measurements for the road during the period of time further include at least one of one or more estimates of a traffic arrival rate volume for the road during the period of time, of one or more estimates of traffic density for the road during the period of time, and of one or more estimates of percentage traffic occupancy of at least one point on the road during the period of time.

36. A computing device configured to provide information related to vehicle travel on a road, comprising:

a processor;

a first module configured to, when executed by the processor, and for each of multiple roads and multiple periods of time, automatically analyze multiple data samples that reflect vehicles traveling on the road during the period of time in order to determine one or more estimated measurements of traffic conditions on the road during the period of time, the multiple data samples including at least one data sample based on one or more data readings generated by one or more traffic sensors associated with the road and including at least one other data sample based on information reported by one or more mobile devices moving along the road during the period of time; and

a second module configured to, when executed by the processor, provide one or more indications of at least some of the determined estimated traffic conditions measurements.

37. The computing device of claim 36 wherein at least one of the multiple periods of time is a future period of time, and wherein the determining of the estimated traffic conditions measurements for the roads during each of the at least one future periods of time includes predicting future traffic conditions on the roads for the future period of time based in part on current traffic conditions on the roads.

38. The computing device of claim 36 wherein the first and second modules each include software instructions for execution by the processor.

39. The computing device of claim 36 wherein the providing of the one or more indications of the at least some determined estimated traffic conditions measurements includes providing the at least some determined estimated traffic conditions measurements to each of one or more users for display to the one or more users.

40. The computing device of claim 39 wherein the providing of the at least some determined estimated traffic conditions measurements to each of the one or more users for display includes providing to each of the users a graphical representation of a geographic area that includes at least some of the multiple roads, the provided graphical representation of the geographic area including graphical representations of the at least some roads and including graphical representations of determined estimated traffic condition measurements for one or more of the at least some roads.

41. The computing device of claim 36 wherein at least one of the multiple periods of time is a current period of time, and wherein the computing device further comprises a module configured to automatically generate one or more predicted traffic conditions on one or more of the roads for a future period of time based in part on the determined estimated traffic conditions measurements for the current period of time for at least one of the roads.

42. The computing device of claim 41 wherein the predicted traffic conditions are further based in part on current conditions that include multiple of current weather, current events that are scheduled to occur, current school sessions that are scheduled to occur, current traffic accidents on one or more of the multiple roads, and current construction activities on one or more of the multiple roads.

43. The computing device of claim 36 wherein at least one of the multiple periods of time is a current period of time, and wherein the computing device further comprises a module configured to automatically generate one or more predicted traffic conditions on one or more other roads that are distinct from the multiple roads for the current period of time based at least in part on the determined estimated traffic conditions measurements for the current period of time for at least one of the multiple roads.

44. The computing device of claim 43 wherein the predicted traffic conditions are further based in part on current conditions that include multiple of current weather, current events that are scheduled to occur, current school sessions that are scheduled to occur, current traffic accidents on one or more of the multiple roads, and current construction activities on one or more of the multiple roads.

45. The computing device of claim 36 wherein the one or more traffic sensors associated with each of the multiple roads each includes at least one of an embedded loop sensor, a camera, a radar ranging device, a motion sensor, and an RFID-based sensor to detect RFID-based tags in vehicles.

46. The computing device of claim 36 wherein the one or more mobile devices moving along each of the multiple roads each includes at least one of a device with GPS capabilities and of a device with cellular telephone transmission capabilities.

47. The computing device of claim 36 wherein the determined estimated traffic conditions measurements for one of the multiple roads during one of the multiple periods of time include one or more estimates of speeds of vehicles traveling on the one road during the one period of time.

48. The computing device of claim 36 wherein the determined estimated traffic conditions measurements for one of the multiple roads during one of the multiple periods of time further include at least one of one or more estimates of a traffic arrival rate volume for the one road during the one period of time, of one or more estimates of traffic density for the one road during the one period of time, and of one or more estimates of percentage traffic occupancy of at least one point on the one road during the one period of time.

49. The computing device of claim 36 further comprising a module configured to automatically determine to replace the determined estimated traffic condition measurements for one of the multiple roads and one of the multiple periods of time with alternative determined estimated traffic condition measurements for the one road during the one period of time that are based at least in part on historical information about traffic conditions related to the one road, and wherein the provided one or more indications of the at least some determined estimated traffic conditions measurements include the alternative determined estimated traffic condition measurements.

50. The computing device of claim 49 wherein the historical information is based on at least one of historical traffic sensor readings from one or more traffic sensors associated with the one road and of historical mobile data source data samples reported by one or more mobile devices that previously moved along the one road.

51. The computing device of claim 36 further comprising a module configured to automatically determine estimated traffic condition measurements for one of the multiple roads during a second period of time distinct from the multiple periods of time based at least in part on historical information about prior traffic conditions for the one road, and to provide one or more indications of the determined estimated traffic condition measurements for the one road during the second period of time.