System and method for assessing road quality using data collected from a mobile device

• US 9,448,073 B2
• Filed: 06/10/2013
• Issued: 09/20/2016
• Est. Priority Date: 06/10/2013
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Stracke, John Richard Jr.
• Primary Examiner(s): Le, John H
• Application Number:
  US13/913,736
• Publication Number:
  US 20150184348A1
• Time in Patent Office: 1,198 Days
• Field of Search: 702/34, 702/75, 702/93, 702/94, 702/96, 702/141, 702/142, 702/149, 702/150, 455/550.1, 701/31.4, 701/123
• US Class Current: 1/1
• CPC Class Codes: G01C 21/20 Instruments for performing navigational calculations G01C21/24, G01C21/26 take precedence
• CPC Class Codes: G01C 21/28 with correlation of data from several navigational instruments
• CPC Class Codes: G01P 15/00 Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration

Abstract

A computer implemented method for assessing road quality using data collected from a mobile device is disclosed. The method may include obtaining travel data associated with a mobile device traversal. The travel data may include acceleration data associated with the mobile device during the mobile device traversal. The method may also include analyzing the travel data according to one or more heuristics. Each heuristic may provide a heuristic metric indicative of whether the mobile device traversal is a human-carried mobile device traversal. In addition, the method may include determining a confidence score for the travel data based on the heuristic metric provided by each of the one or more heuristics and processing the travel data based at least in part on the confidence score, wherein the processed travel data is configured to be used to assess road quality.

Claims

1. A computer implemented method for assessing road quality using data collected form a mobile device, the method comprising:

obtaining, by one or more processors, travel data collected by the mobile device during a mobile device traversal, the travel data including acceleration data associated with the mobile device during the mobile device traversal;

analyzing, by the one or more processors, the travel data according to one or more heuristics, each heuristic providing a heuristic metric indicative of whether the mobile device traversal is a human-carried mobile device traversal;

determining, by the one or more processors, a confidence score for the travel data based on the heuristic metric provided by each of the one or more heuristics;

processing, by the one or more processors, the travel data to assess road quality for a section of a road based at least in part on the confidence score, including discarding the travel data when the confidence score does not exceed a confidence threshold; and

providing, by the one or more processors, an indication of road quality for the section of the road to a user approaching the road segment.

2. The method of claim 1, wherein the travel data further includes position data associated with the mobile device during the mobile device traversal.

3. The method of claim 1, wherein analyzing the travel data according to one or more heuristics comprises analyzing the travel data according to a speed heuristic.

4. The method of claim 3, further comprising:

determining a speed of the mobile device during the mobile device traversal based the travel data; and

determining the heuristic metric based on the speed of the mobile device.

5. The method of claim 1, wherein analyzing the travel data according to one or more heuristics comprises analyzing the travel data according to an endurance heuristic.

6. The method of claim 5, further comprising:

determining a speed of the mobile device during the mobile device traversal based on the travel data;

identifying a time period across which the speed is maintained during the mobile device traversal; and

determining the heuristic metric based on the time period.

7. The method of claim 1, wherein analyzing the travel data according to one or more heuristics comprises analyzing the travel data according to a frequency heuristic.

8. The method of claim 7, further comprising:

analyzing the acceleration data to identify a plurality of acceleration transients;

determining a frequency of the acceleration transients; and

generating the heuristic metric based on the frequency.

9. The method of claim 1, wherein analyzing the travel data according to one or more heuristics comprises analyzing the travel data according to an acceleration heuristic.

10. The method of claim 1, further comprising:

determining an acceleration of the mobile device during the mobile device traversal based on the acceleration data; and

determining the heuristic metric based on the acceleration of the mobile device.

11. The method of claim 1, wherein the heuristic metric is generated based on a monotonically increasing function.

12. The method of claim 1, wherein the confidence score is determined based on the heuristic metric provided by each of the one or more heuristics using fuzzy logic.

13. The method of claim 1, wherein processing the travel data to assess the road quality includes identifying at least one surface anomaly.

14. The method of claim 1, further comprising obtaining further travel data collected by a plurality of mobile devices to identify road surface anomalies using a crowdsourcing methodology.

15. A system for assessing road quality using data collected form a mobile device, the system comprising:

a computing device including a processor and memory, the memory storing instructions that, when executed by the processor, configure the computing device to;

obtain travel data collected by the mobile device during a mobile device traversal, the travel data including acceleration data associated with the mobile device during the mobile device traversal;

analyze the travel data according to one or more heuristics, each heuristic providing a heuristic metric indicative of whether the mobile device traversal is a human-carried mobile device traversal;

determine a confidence score for the travel data based on the heuristic metric provided by each of the one or more heuristics;

process the travel data to assess road quality based at least in part on the confidence score, including discard the travel data when the confidence score does not exceed a confidence threshold; and

using the assessed road quality, generate a driving route with a least amount of road surface anomalies to a user-selected travel destination.

16. The system of claim 15, wherein the travel data further includes position data associated with the mobile device during the mobile device traversal.

17. The system of claim 15, wherein the computing device is configured to analyze the travel data according to at least one of a speed heuristic, an endurance heuristic, or a frequency heuristic.

18. The system of claim 15, wherein the heuristic metric is generated based on a monotonically increasing function.

19. The system of claim 15, wherein the confidence score is determined based on the heuristic metric provided by each of the one or more heuristics using fuzzy logic.

20. The system of claim 15, wherein the computing device is configured to analyze the acceleration data to identify a plurality of acceleration transients associated with the road surface anomalies.