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Original Authors: Willians R. Mertz Villa, HOB Consultores SA.
Edited by Cyth Systems
The Challenge
Improving the process of surveying information to assess the degree of deterioration of the road infrastructure—which is currently performed manually and disrupts traffic during the day, has a high risk of accidents, and yields little (10 km per work crew per day)—and recording the information in formats that are not subject to manipulation and can be verified with consistent results.
The Solution
Developing a mobile platform with a continuously geo-referenced, real-time video system specifically designed to collect virtual images of the condition of deterioration and maintenance of the pavement and engineering structures (up to 80 km/h) efficiently and securely.
Surveying Road Conditions Using the ROAS Equipment
Road infrastructure helps local markets develop and provides integration with spatial economic centers to generate positive effects that influence businesses’ and households' production and consumption decisions. The lack of a route affects the standard of living and the productivity of the people in the area. Additionally, road deterioration increases operating costs, travel time, and investment. User satisfaction is reflected in the quality of the pavement. We must know when to intervene and how to measure deterioration, a process subject to methodologies of surveying information that are now performed manually, which makes results inconsistent.
Application Description
The road analyzer and survey (ROAS) vehicle mobile platform is oriented to technological innovation for the management and maintenance of roads. The ROAS performs automatic measurements of geo-referenced data and provides service survey information to assess service levels and surface conditions of the road using national and international standards such as ASTM Standard D6433-11 from the Roads and Parking Lots Pavement Condition Index Surveys (Figure 1). We developed a data acquisition and pre-processing system, and two software modules to generate specialized reports.
Left: Road Inspection Platform Graphical User Interface, Right: Software Module for Inspection and Reporting With Images of the Pavement (MESP)
The Data Acquisition and Pre-Processing System
This module is composed of data acquisition hardware using the NI PXI Platform and the control module, which we developed using NI LabVIEW software and the NI LabVIEW Real-Time Module (Figure 2).
The hardware synchronizes and acquires digital image data of the road and pavement, GPS, turning, and other devices. We synchronized this data with a distance measuring instrument (DMI) through a sensor encoder connected to the vehicle axis wheels. Figure 3 shows the parts of the DAQ system mounted on the mobile platform.
Software Modules to Generate Specialized Reports
We generate reports based on the type of information collected by the ROAS system. We could perform many inspections and operations with the route images acquired through the route surface evaluation module (MESR), which we developed using LabVIEW (Figure 4), including:
Road safety
Asset inventory (traffic signs, traffic lights)
Current road conditions with simulations of tours through the track at different speeds
Measurements of the images, such as lane width and projection GPS
We can perform in-cabinet visual inspections of the condition of the paved roads, get a maintenance history, identify the type of failures and determine severity (crocodile cracking or longitudinal and transverse cracks), and perform reporting. We can do all of this through the pavement surface evaluation module (MESP), which we developed using LabVIEW (Figure 5).
General Properties of the System
The system includes:
Data acquisition rates of up to 80 km/h
Panoramic digital images of up to 120° of route
Digital images of all the pavement in a lane (up to 4 m wide)
Virtual measurements on images
Virtual tours of tracks at different speeds and geo-positioning
Large storage capacity for internal and external information
Report generation and data exporting to different file formats such as Excel, Word, KML, (Google Earth, JPG, and AVI
Artificial lighting using xenon strobe lights to capture images of the pavement
Geo-referenced data (GPS or DGPS)
DMI with an error rate less than 0.1 percent
Conclusion
We developed the appropriate methodology for surveying. Our system provides reliable information and consistent results with a high production rate (200 km/day) and is safe. It works on unpaved, paved, and urban roads during the day or at night. Users can adjust report generation to their own requirements. Data is verifiable, reproducible, and exportable to other platforms. The system has GPS or DGPS information and can import images from Google Maps. It also has improved information quality to input into the pavement management system, provides better and timelier intervention decisions for the road, and can integrate other sensors and/or measurement equipment into the platform.
Original Authors:
Willians R. Mertz Villa, HOB Consultants SA.
Edited by Cyth Systems