Roaming Mobile Sensor Platform For Collecting Geo-Referenced Data and Creating Thematic Maps

• US 20130018575A1
• Filed: 03/21/2011
• Published: 01/17/2013
• Est. Priority Date: 03/19/2010
• Status: Active Grant

• Current Assignee: Northeastern University
• Original Assignee: Northeastern University
• Inventors: Birken, Ralf, Rappaport, Carey M., Wang, Ming-Liang, Wadia-Fasceti, Sara, McDaniels, Gregory J.
• Granted Patent: US 9,377,528 B2
• Time in Patent Office: Days
• US Class Current: 701/409
• CPC Class Codes: G01B 11/2513 with several lines being projected in more than one direction, e.g. grids, patterns
• CPC Class Codes: G01S 13/00 Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
• CPC Class Codes: G01S 13/885 for ground probing prospecting or detecting using electromagnetic waves G01V3/12
• CPC Class Codes: G01S 15/89 for mapping or imaging
• CPC Class Codes: G01S 19/14 specially adapted for specific applications
• CPC Class Codes: G01V 3/12 operating with electromagnetic waves operating with millimetre waves G01V8/005

Abstract

A roaming sensor system collects data on the condition of roads and bridge decks and identifies and maps defects, including cracks, potholes, debonding, tracking, delamination, surface ice, surface water, and rebar corrosion. Data are collected by a vehicle or a fleet of vehicles driven at normal traffic speeds. The vehicle is outfitted with sensors that collect data using acoustic surface waves, ground penetrating radar, mm wave surface radar, and/or video images. The data are transmitted to a control center for analysis and distribution.

Claims

1. A roaming sensor system for mapping a condition of a roadway, the system comprising:

a positioning subsystem on a vehicle, wherein the positioning subsystem collects geoposition data of a vehicle as it travels on the roadway;

a sensor subsystem on a vehicle, wherein the sensor subsystem collects roadway condition data as a vehicle travels on the roadway; and

a computer that correlates the geoposition data and roadway condition data and produces a map of the condition on the roadway.

2. The system of claim 1, wherein the sensor subsystem collects said roadway condition data at an ordinary driving speed for the roadway.

3. The system of claim 2, wherein the sensor subsystem collects said roadway condition data at a speed of at least 65 mph.

4. The system of claim 1, wherein the computer is remotely located from the vehicle.

5. The system of claim 4, further comprising a data transmission subsystem that wirelessly transmits the geoposition data and roadway condition data in raw or processed form to the computer.

6. The system of claim 1, further comprising a main controller that accepts road condition data from the sensor subsystem and transmits the data in raw or processed form to the computer.

7. The system of claim 5, further comprising a main controller that accepts road condition data from the sensor subsystem and transmits the data in raw or processed form to the data transmission subsystem.

8. The system of either claim 6 or claim 7, wherein the main controller further accepts geoposition data from the positioning subsystem and correlates the geoposition data with the road condition data before transmitting the road condition data.

9. The system of claim 1, wherein the sensor subsystem comprises one or more sensors selected from the group consisting of acoustic sensors, electromagnetic sensors, and optical sensors.

10. The system of claim 1, wherein the sensor subsystem detects a surface acoustic wave, a surface radar reflection, a subsurface radar reflection, an optical image, or a combination thereof.

11. The system of claim 1, wherein the sensor subsystem comprises an array of directional microphones mounted under the vehicle, the array of microphones forming a tire excited acoustic sensor system (TEAS) and detecting acoustic waves at a roadway surface, said acoustic waves excited by one or more tires of the vehicle.

12. The system of claim 1, wherein the sensor subsystem comprises an air coupled ground penetrating radar (GPR) system.

13. The system of claim 12, wherein the GPR system collects at least 16 channels of data across the width of the roadway.

14. The system of claim 13, wherein the GPR system collects data with a spatial resolution in the range of 1-5 cm along the length of the roadway while the vehicle is driven at a speed of at least 65 mph.

15. The system of claim 1, wherein the sensor subsystem comprises a surface looking millimeter wave radar (SLMR) system.

16. The system of claim 1, wherein the sensor subsystem comprises a video-based surface sensing system, an optical profilometry system, or a differential optical profilometry system.

17. The system of claim 16, wherein the sensor subsystem produces a topography map of the roadway surface with at least 2 mm resolution.

18. The system of claim 1, further comprising one or more auxiliary sensors selected from the group consisting of a temperature sensor, a humidity sensor, a laser profilometer, and an accelerometer.

19. The system of claim 1, wherein the sensor subsystem comprises at least two different types of sensors.

20. The system of claim 19, comprising at least two sensor types selected from the group consisting of TEAS, GPR, SLMR, and an optical sensor.

21. The system of claim 20, comprising TEAS, GPR, SLMR, and an optical sensor.

22. The system of claim 1, comprising a plurality of said vehicles, each vehicle comprising a said positioning subsystem and a said sensor subsystem, wherein data from each of the positioning subsystems and sensor subsystems are transmitted to one or more computers at a single control center.

23. The system of claim 21, comprising at least ten said vehicles.

24. The system of claim 1 that produces a GIS map of roadway condition having two or more layers.

25. The system of claim 1, wherein the system is capable of identifying a roadway condition selected from the group consisting of cracks, potholes, debonding, tracking, delamination, the presence of surface ice, the presence of surface water, and rebar corrosion.

26. A method of mapping a condition of a roadway, the method comprising the steps of:

providing a roaming sensor system according to claim 1;

driving the vehicle along the roadway while collecting geoposition data and data on the roadway condition;

correlating the geoposition data with the roadway condition data to produce a map of the roadway condition.

27. The method of claim 26, wherein the vehicle is driven at an ordinary driving speed for the roadway while roadway condition data are collected.

28. The method of claim 26, wherein the system comprises a data transfer subsystem and the geoposition data and the roadway condition data in raw or processed form are transmitted by the data transfer subsystem to the computer at a location remote from the vehicle.

29. The method of claim 28, wherein the data are transmitted wirelessly.

30. The method of claim 28, wherein the data are transmitted by cable.

31. The method of claim 28, wherein the data are transmitted on a storage medium.

32. The method of claim 26, wherein the system comprises a main controller that collects the roadway condition data from the sensor subsystem and then transmits the processed data to the computer at a location remote from the vehicle.

33. The method of claim 32, wherein the main controller processes the data prior to transmitting it to the computer at a remote location.

34. The method of claim 26, wherein the roadway condition data are obtained by at least two sensor systems selected from the group consisting of TEAS, GPR, SLMR, and an optical sensor system.

35. The method of claim 34, wherein the roadway condition data are obtained by TEAS, GPR, SLMR, and an optical sensor system.

36. The method of claim 26, wherein the roadway condition data are processed by an algorithm that converts the data into a signal or an image indicative of a roadway condition.

37. The method of claim 36, wherein the condition is selected from the group consisting of cracks, potholes, debonding, tracking, delamination, the presence of surface ice, the presence of surface water, and rebar corrosion.

38. The method of claim 26, further comprising the step of analyzing the correlated data to add interpretive information to the map of the condition on the roadway.

39. The method of claim 26, further comprising the step of collecting data from one or more auxiliary sensors and modifying the roadway condition data using the auxiliary sensor data.

40. The method of claim 26, wherein a plurality of vehicles are driven over roadways in different regions of a geographical area, and the roadway condition maps from individual vehicles are combined to produce a roadway condition map of the geographical area.

41. The method of claim 40, wherein 10 or more vehicles are used.

42. The method of claim 26 which is repeated after a selected time interval and the roadway condition data are analyzed for changes in the roadway condition.

43. The method of claim 26, wherein the vehicle is driven along a route selected for a purpose other than collecting roadway condition data.

44. The method of claim 26, wherein the vehicle is driven along a route selected for the purpose of collecting roadway condition data.

45. The method of claim 26, wherein the roadway is a bridge deck.

46. The method of claim 26, wherein the roadway is a surface road.

47. The method of claim 26, wherein an operator or a program transmits an instruction from a remote location to the vehicle, and the route of the vehicle or a mode of sensor operation, data collection, or data processing is altered in response to the instruction.

48. A roaming sensor system for mapping a condition of a roadway, the system comprising:

a control system comprising;

a receiver for receiving geoposition data from a positioning subsystem and roadway condition data from a sensor subsystem on a vehicle collected as the vehicle travels on a roadway; and

a computer that correlates the geoposition data and roadway condition data and produces a map of the condition on the roadway.