PAVEMENT CONDITION ANALYSIS FROM MODELING IMPACT OF TRAFFIC CHARACTERISTICS, WEATHER DATA AND ROAD CONDITIONS ON SEGMENTS OF A TRANSPORTATION NETWORK INFRASTRUCTURE

• US 20140122045A1
• Filed: 01/07/2014
• Published: 05/01/2014
• Est. Priority Date: 08/08/2013
• Status: Active Grant

• Current Assignee: DTN, LLC (TBG AG)
• Original Assignee: Iteris Incorporated
• Inventors: MEWES, JOHN J., OSBORNE, LEON F.
• Granted Patent: US 8,744,822 B2
• Time in Patent Office: Days
• US Class Current: 703/6
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30
• CPC Class Codes: Y02T 10/82 Elements for improving aerodynamics

Abstract

A pavement condition analysis system and method models a state of a roadway by processing at least traffic and weather data to simulate the impact of traffic and weather conditions on a particular section of a transportation infrastructure. Traffic data is ingested from a plurality of different external sources to incorporate various approaches estimating traffic characteristics such as speed, flow, and incidents, into a road condition model to analyze traffic conditions on the roadway in order to improve road condition assessments and/or prediction. A road condition model applies these traffic characteristics, weather data, and other input data relevant to road conditions, accounting for heat and moisture exchanges between the road, the atmosphere, and pavement substrate(s) in a pavement'"'"'s composition, as further influenced by traffic and road maintenance activities, to generate accurate and reliable simulations and predictions of pavement condition states for motorists, communication to vehicles, use by industry and public entities, and other end uses such as media distribution.

Claims

1. A method of integrating traffic, weather and road condition data for modeling pavement conditions in a transportation infrastructure network, comprising:

ingesting, as a first set of input data, weather data collected from one or more of weather sensors, satellite networks, vehicle-based systems, and numerical weather prediction models, and developing a meteorological profile representing weather conditions on a roadway segment of a transportation infrastructure for which pavement conditions are to be modeled;

ingesting, as a second set of input data, traffic data, and developing a traffic profile representing traffic conditions on the roadway segment for which pavement conditions are to be modeled;

ingesting, as a third set of input data, road condition data collected from one or more of road sensors, mobile sensors, and vehicle-based systems, and developing standardized road condition reports representing roadway conditions on the roadway segment for which pavement conditions are to be modeled;

assimilating, in a computing environment comprised of hardware and software components that include at least one processor configured to analyze the meteorological profiles, the traffic profiles, and the standardized road condition reports in a road condition model that simulates and iteratively adjusts pavement condition states from behavior of a pavement response to one or more of

     1) changes in states of moisture resulting from heat and moisture exchanges between a pavement surface, the atmosphere, and one or more pavement substrates in a pavement'"'"'s composition

     2) traffic flow characteristics that include deviations from a normal traffic state at a specified period of time indicated in the traffic profile, and

     3) experienced roadway conditions from the standardized road condition reports, and predicts pavement condition states over the specified period of time; and

generating one or more of a plurality of output pavement conditions from the simulated and predicted pavement condition states to output data modules configured to develop spatial, trip, and time-series content in one or more related application programming interfaces, and interpretations of the simulated and predicted pavement condition states for distribution to output data modules configured to develop enhanced commercial content in one or more related application programming interfaces.

2. The method of claim 1, wherein at least one of the weather data, traffic data, and road condition data further includes data collected from crowd-sourced observations.

3. The method of claim 1, wherein the weather sensors are comprised of at least one of radar systems, surface networks, and image-based systems.

4. The method of claim 1, wherein the traffic data is representative of actual traffic conditions that include traffic speed data, traffic flow data, and incident data, from one or both of analyzed traffic characteristics that include traffic information generated by a traffic state estimation platform, and predicted traffic characteristics that include predicted traffic speed and predicted traffic volume generated by a traffic prediction platform.

5. The method of claim 1, wherein the road condition model simulates and iteratively adjusts pavement condition states from behavior of a pavement in response to experienced roadway conditions from the standardized road condition reports for a specified period of time.

6. The method of claim 1, wherein the road condition data comprises maintenance data relative to treatments provided to a roadway surface, the vehicle-based systems including systems coupled to winter maintenance vehicles.

7. The method of claim 1, further comprising associating the traffic profiles, meteorological profiles, and standardized road condition reports with representative road segment metadata maintained in at least one road segment database.

8. The method of claim 1, wherein the generating interpretations of the simulated and predicted pavement condition states for distribution to output data modules configured to develop enhanced commercial content further comprises developing at least one of output data packaged for traffic flow models to improve traffic prediction, quantitative metrics of travel difficulty along a specific roadway segment that include one or more of textual, visual and numerical summarizations of pavement condition states in an area including one or more roadway segments, and one or more of textual, visual, and numerical summarizations of pavement condition states for a user-defined trip.

9. The method of claim 1, wherein the generating one or more of a plurality of output pavement conditions from the simulated and predicted pavement condition states to output data modules further comprises developing at least one of map tiles and vectorized roadway condition data for a mapping function, developing pavement conditions for a set of locations or times in a trip, and developing pavement conditions at a fixed location over time for a time-series display.

10. The method of claim 1, wherein the generating one or more of a plurality of output pavement conditions from the simulated and predicted pavement conditions states to output data models further comprises displaying cross-sectional animations of a pavement condition on a graphical user interface.

11. The method of claim 1, wherein the generating one or more of a plurality of output pavement conditions from the simulated and predicted pavement conditions states to output data models further comprises generating a display of a pavement condition state in a broadcast media presentation tool configured to provide one or more of visual, textual, an audial content to a broadcast audience.

12. The method of claim 1, further comprising ingesting image data received from one or more video cameras configured to collect images of the roadway to be modeled, and adjusting, based on one or more visual characteristics within the image data, an existing state of the roadway in the road condition model for consistency with road, traffic and weather conditions indicated in image data.

13. The method of claim 1, wherein predictions of pavement condition states at least include forecasts of at least one of pavement surface temperatures and pavement conditions.

14. A system comprising:

a computer processor; and

at least one computer-readable storage medium operably coupled to the computer processor and having program instructions stored therein, the computer processor being operable to execute the program instructions to operate a road condition model in a plurality of data processing modules, the plurality of data processing modules including;

a data ingest module configured to receive, as input data, weather data representing meteorological conditions experienced on segments of roadway a transportation infrastructure, and traffic data representing traffic conditions experienced on segments of roadway in a transportation infrastructure, and road condition data representing factors relating to experienced road conditions on segments of a transportation infrastructure;

a pavement analysis module configured to simulate and iteratively adjust pavement condition states from behavior of a pavement in response to one or more of

     1) changes in states of moisture resulting from heat and moisture exchanges between the road surface, the atmosphere, and one or more pavement substrates in a pavement'"'"'s composition,

     2) traffic flow characteristics that include deviations from a normal traffic state at a specified period of time, and

     3) experienced road conditions, and a forecast module configured to generate predictions of pavement condition states over the specified period of time.

15. The system of claim 14, further comprising at least one module configured to generate content representative of the simulations and predictions of pavement condition states, the content configured for delivery in at least one of indicia for visual display on a graphical user interface, textual information, or audio, for use by motorists, for communication to vehicles, for use by industry and public entities, and as content for distribution to one or more media outlets.

16. The system of claim 15, wherein the content further includes the simulations and predictions of pavement condition states interpreted for at least one of a traffic model application programming interface, a mobility application programming interface, an area summary application programming interface, and trip summary application programming interface.

17. The system of claim 15, wherein the content further includes one or more of animated time-series of cross-sectional profiles of the simulations and predictions of pavement conditions states for a time-series data application programming interface, tiles or vectorized profiles of pavement conditions configured for display of spatial data in an application programming interface for a mapping function, and roadway conditions for a set of locations or times in a trip in an application programming interface for display of trip data.

18. The system of claim 15, wherein the content includes cross-sectional animations of a pavement condition for display on a graphical user interface.

19. The system of claim 15, wherein the content includes a display of a pavement condition state in a broadcast media presentation tool configured to provide one or more of visual, textual, an audial content to a broadcast audience.

20. The system of claim 14, wherein data ingest module is further configured to generate meteorological profiles from the weather data, traffic profiles from the traffic data, and standardized road condition reports from the road condition data.

21. The system of claim 14, wherein the data ingest module is further configured to associate the weather data, the traffic data, and the road condition data with road segment network information.

22. The system of claim 14, wherein the ingested traffic data includes actual traffic conditions that include traffic speed data, traffic flow data, and incident data, from one or both of analyzed traffic characteristics that include traffic information generated by a traffic state estimation platform, and predicted traffic characteristics that include predicted traffic speed and predicted traffic volume generated by a traffic prediction platform.

23. A method of modeling pavement conditions in a transportation infrastructure network, comprising:

developing associations of input data to road segment metadata in a plurality of profiles in at least one processor in a computing environment comprised of hardware and software components to enable a plurality of data processing functions in a road condition model, the plurality of profiles include a meteorological profile representing weather conditions, a traffic profile representing traffic conditions, and standardized road condition reports representing experienced road conditions, for roadway segments of a transportation infrastructure;

simulating and iteratively adjusting pavement condition states from a behavior of a pavement for a roadway segment in response to one or more of

     1) changes in states of moisture resulting from heat and moisture exchanges between the road surface, the atmosphere, and one or more pavement substrates in the pavement'"'"'s composition as a result of impacts on the pavement by weather, traffic, and road conditions experienced on the roadway segment,

     2) traffic flow characteristics that include deviations from a normal traffic state, at a specified period of time, and

     3) the experienced road conditions from the standardized road condition reports; and

predicting pavement condition states over the specified period of time, wherein predictions of pavement condition states at least comprise forecasts of pavement surface temperatures and conditions.

24. The method of claim 23, wherein the input data is comprised of weather data collected from one or more of weather sensors, satellite networks, vehicle-based systems, and numerical weather prediction models, the weather data representative of one or more of atmospheric temperature, humidity, wind speed, and precipitation in an area in which the roadway segments are located.

25. The method of claim 23, wherein the input data is comprised of traffic data representative of actual conditions in one or both of analyzed traffic characteristics and predicted traffic characteristics experienced on the roadway segments, wherein the actual traffic conditions include traffic speed data, traffic flow data, and incident data.

26. The method of claim 25, wherein the analyzed traffic characteristics include traffic information generated by a traffic state estimation platform, and wherein the predicted traffic characteristics include predicted traffic speed and predicted traffic volume generated by a traffic prediction platform.

27. The method of claim 23, wherein the input data is comprised of road condition data collected from one or more of road sensors, mobile sensors, and vehicle-based systems, the road condition data representative of roadway conditions experienced on the roadway segments.

28. The method of claim 23, further comprising generating cross-sectional animations of a pavement condition state on a graphical user interface.

29. The method of claim 23, further comprising generating a display of a pavement condition state in a broadcast media presentation tool configured to provide one or more of visual, textual, an audial content to a broadcast audience.

30. The method of claim 23, further comprising generating output data packaged for traffic flow models to improve traffic prediction, quantitative metrics of travel difficulty along a specific roadway segment that include one or more of textual, visual and numerical summarizations of pavement condition states in an area including one or more roadway segments, one or more of textual, visual, and numerical summarizations of pavement condition states for a user-defined trip, and at least one of map tiles and vectorized roadway condition data for a map of one or more roadway segments.