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Publication Number:  FHWA-HRT-12-002    Date:  January/February 2012
Publication Number: FHWA-HRT-12-002
Issue No: Vol. 75 No. 4
Date: January/February 2012


Transportation Operations Laboratory: Article III - The DRT Start

by Gene McHale

FHWA's Data Resources testbed is up and running -- collecting, managing, storing, and visualizing data generated by the agency's new Transportation Operations Laboratory.

Growing traffic congestion like this has focused attention on the need to develop and test new strategies to operate the Nation‘s roadways efficiently. To meet this need, FHWA has opened the new Saxton Transportation Operations Laboratory, which includes a Data Resources testbed.
Growing traffic congestion like this has focused attention on the need to develop and test new strategies to operate the Nation's roadways efficiently. To meet this need, FHWA has opened the new Saxton Transportation Operations Laboratory, which includes a Data Resources testbed.

Congestion on U.S. roads continues to be an issue for the traveling public. According to the Texas Transportation Institute's 2011 Urban Mobility Report, an automobile commuter in one of the Nation's 15 largest metropolitan areas experiences 52 hours of delay on average and wastes 25 gallons of fuel, which costs the motorist $1,083 each year due to congestion. For the Chicago and Washington, DC, metropolitan areas, the numbers are over 70 hours of delay and more than 35 gallons of wasted fuel.

At its most basic, congestion can be explained through supply and demand. There is simply not enough supply, or roadway capacity, to handle the demand for travel. To those stuck in traffic, it is of little consolation that many view the high demand for travel as a sign of an active economy. The limited roadway capacity is largely due to the high cost of building new roads or expanding the capacity of existing roads.

"Growing travel demand and limited ability to build new capacity make efficient management and operation of the Nation's roads extremely critical," says Federal Highway Administration (FHWA) Associate Administrator for Operations Jeff Lindley. "In recent years, the importance of transportation operations has grown tremendously due to increasing demands and limited resources for building new road capacity."

Practitioners in the field of transportation operations are constantly looking for new strategies and approaches to better manage roadways. As in other transportation disciplines, researchers typically conceive, analyze, and test new strategies in a laboratory environment prior to field testing and deployment. The mission of the FHWA Office of Operations Research & Development (R&D) is to envision and evaluate new transportation strategies, improve the underlying technologies that facilitate those strategies, and develop and test the new strategies in field settings. To assist in achieving that mission, FHWA has designed and implemented a new Saxton Transportation Operations Laboratory (TOL) located at the Turner-Fairbank Highway Research Center (TFHRC) in McLean, VA.

The Saxton TOL consists of three component testbeds: Concepts and Analysis, Cooperative Vehicle-Highway, and Data Resources. A testbed is an environment where new strategies and technologies can be tested and evaluated prior to real-world deployment. The Concepts and Analysis testbed focuses on identifying and developing concepts for new transportation operations strategies and evaluating their impacts using simulation and other analytical tools. (See "Modeling Transportation Systems: Past, Present, and Future," in the September/October 2011 issue of Public Roads.)

The Cooperative Vehicle-Highway testbed takes the development of new strategies to the next level by testing prototypes in fieldlike settings using the TOL's intelligent intersection, specially equipped vehicles, and other hardware and software components. (See "A Living Outdoor Laboratory" in the November/December 2011 issue.)

The role of the Data Resources testbed includes the capture, management, storage, and visualization needs of data generated by the other two testbeds. It also serves as a data resource for the broader research community.

The Need

Historically, transportation data were hard to come by. Most of the detectors and other equipment for data collection deployed on U.S. roads were installed in fixed locations and served fixed needs. Examples include inductive loop detectors in the pavement at traffic-signalized intersections to detect when vehicles are waiting on side streets at red lights. Other examples include detector count stations installed on freeways to feed information for real-time traffic monitoring and use in annual reporting of highway performance.

In the early 1990s, a renewed focus on transportation operations and the introduction of new intelligent transportation systems (ITS) services with their corresponding data requirements led to an increase in the number and types of equipment for data collection. The new systems employed radar, video image processing, acoustic sensing, infrared, and wireless communications for traffic signal control, freeway operations, incident management, and electronic toll collection. With so much data being collected, however, most of it was not stored, shared, or used for purposes other than those for which it was originally intended. The transportation community and FHWA recognized the need to store useful transportation data from ITS systems and mainstreamed its response in 1999 by adding the Archived Data User Service to version 3.0 of the National ITS Architecture. The National ITS Architecture defines a set of user services and provides a common framework for State and local agencies in the planning, design, and implementation of ITS.

Figure. Three circles formed into a downward-pointing triangle are connected by arrows. The first circle (at the top left of the triangle) is labeled ―Cooperative Vehicle-Highway Testbed (and Technology Testing)‖ and includes a photo of FHWA' s intelligent intersection. The first circle is linked by the first arrow of two two-way arrows labeled "'Real-world' performance characteristics" to the second circle (at the top right of the triangle), which is labeled "Concepts and Analysis Testbed (and 'What-ifs')," and by the second two-way arrow labeled "Simulated network data, e.g., traffic alerts" from that circle back to the first one. The second circle, which shows a photo of a heavily traveled urban highway with high-rise buildings in the background, is connected by two-way arrows labeled "Validation/Calibration Data" and "Data Sets" to the third circle (located at the bottom of the triangle), labeled "Data Resources Testbed (and Data Analysis)." The third circle, which shows flowcharts of data, is connected to the first by two-way arrows labeled "Validation/Calibration Data" and "Test Data." An external box labeled "External Stakeholders, Applications, and Data" is linked by arrows into and out of the central triangle. A second external box labeled "Living Laboratories" with an image of the contiguous United States is linked by arrows into and out of the central triangle.

Today, archived data on transportation operations are fairly common. The ability to share and reuse this data, however, is still hampered by the lack of clear, consistent documentation. Good metadata, or data about data, are critical to enable reuse for purposes beyond those for which the data were originally collected.

Another characteristic of today's widely available data archives is that they typically represent data from a single type of source (for example, data from freeway loop detectors along specific sections of highway). What is less common are data available from a variety of sources and transportation modes, such as freeway loop data combined with traffic data on nearby arterials and data on weather conditions, incidents, transit operations, or freight movements.

This in-pavement loop detector, indicated by the pavement cut, is typical of the sensors used to collect data on roadway use and performance. However, these detectors are limited to the extent that they provide data from only a single point location on a roadway.
This in-pavement loop detector, indicated by the pavement cut, is typical of the sensors used to collect data on roadway use and performance. However, these detectors are limited to the extent that they provide data from only a single point location on a roadway.

Current successful examples of well-documented, integrated data include the U.S. Department of Transportation's (USDOT) Next Generation Simulation (NGSIM) program. The NGSIM program made available a number of well-documented datasets of subsecond vehicle trajectories along roadway sections. The goal was to encourage the research community to develop new algorithms on driver behavior.

Another successful example is California's Performance Measurement System, a source of archived and real-time data from freeway loop detectors across the State. The data often are combined with other relevant data such as scheduled road closures or travel times collected from toll tag readers.

Another success, the Regional Integrated Transportation Information System (RITIS), integrates multisource archived and real-time data from various member jurisdictions of the I-95 Corridor Coalition, a partnership of transportation agencies along the corridor. The RITIS system, developed and operated by the University of Maryland Center for Advanced Transportation Technology (CATT) Laboratory has been extremely innovative in the visualization of integrated transportation data. The CATT Laboratory has applied several advanced techniques such as four-dimensional real-time traffic monitoring (that is, the virtual helicopter), circular dependency graphs that reveal relationships among data elements, and graphical generation of incident timelines to display transportation-related data in ways heretofore unseen in transportation operations.

Despite these advances in transportation data, room for improvement remains. The proliferation of global positioning systems (GPS), cell phones, smartphones, and other wireless mobile devices is creating a data-rich transportation environment that reaches well beyond the previous world of limited data collection at fixed locations along roadways. Mobile devices enable data to be collected in real time across the breadth of the transportation system, in terms of both geographic coverage (that is, all types of roads) and modal coverage (automobiles, transit and freight vehicles, and travelers carrying handheld devices). This wealth of data presents both a challenge and an opportunity to transportation management systems and those that operate them. The potential to assess, in real time, the status of the transportation system across all modes and all types of roads and to use this information to manage the system proactively is the opportunity. The challenge then is how to collect and manage these data in an efficient and effective manner. The Saxton TOL and the Data Resources testbed are poised to address this challenge by conducting and supporting the research needs of the transportation operations community.

Photo. Sample vehicle probe data is shown layered over a photo of a vehicle.
A sample of vehicle probe data transmitted wirelessly from one of the TOL's Cooperative Vehicle-Highway testbed vehicles, shown here. These data include a detailed"snapshot" of information collected from onboard the vehicle, such as vehicle position, speed, acceleration, and the status of a number of vehicle subsystems such as windshield wipers, lights, brakes, and steering.

The Testbed's Internal And External Roles

As mentioned earlier, the role of the Data Resources testbed (DRT) is twofold: one, it serves the data-related needs of FHWA's other two TOL testbeds; and two, it serves as a resource to the broader transportation research community.

As a component of the larger laboratory, the DRT supports the data-related needs of FHWA's Concepts and Analysis testbed by providing a data repository for computer simulation and analysis input files related to transportation operations. Maintaining a well-managed and well-documented file repository promotes the reuse of simulation models as ongoing "analysis testbeds" for new transportation operations strategies. In addition to efficiencies that the Concepts and Analysis testbed researchers gain by not having to create new simulation model inputs from scratch, they can use those analysis testbeds to compare alternative operations strategies under similar simulated conditions and road networks.

The DRT also serves as a repository for the corresponding simulation and analysis output files related to those analysis testbeds and for any corresponding archived data and real-time feeds if the analysis testbeds are based on real-world transportation networks. The DRT researchers are exploring the integration of analytical results with real-world data or other research data and methods to display those combined data visually.

For the Cooperative Vehicle-Highway testbed, the DRT provides data management and visualization services, making the data available for research and analysis. The DRT supports the management and storage of data collected from the Cooperative Vehicle-Highway testbed's full-scale traffic signal-controlled intersection at the TFHRC facility, two specially equipped vehicles, and numerous sensors, detectors, and other equipment that transmit a variety of data both wirelessly and via more traditional wired communications techniques. Part of the data analysis includes visual displays such as plots of GPS-based position data from vehicles traveling around the TFHRC facility. This particular data acquisition functionality is part of the TOL's role as a testbed for USDOT's ITS research program.

Just as important as the DRT's role as an internal resource for the TOL is the testbed's function as an external resource to the broader research community. The intent is to make the data that are collected and managed for TOL research available to the public so the information can be reused in related transportation operations research.

Caption: Data visualization. This data visualization is labeled -I–495, beginning at Exit 27 and ending at VA-123/Chain Bridge Rd/Exit 11. The left half of the graph is labeled -Outer Loop  with downward-pointing arrows, and the right half is labeled -Inner Loop  with upward-pointing arrows. The horizontal axis is divided into 2-hour time segments from 12 a.m. to 10 p.m. The vertical axis is divided into 1-mile segments from 1 mile to 20 miles. A legend and colors indicate heavy congestion on the Outer Loop in the morning along most of the mileage segments and heavy congestion on the Inner Loop in the afternoon along most of the mileage segments. A central section of the graph shows labels for the various exits on this 20-mile section of I-495. Small icons on the figure indicate locations and durations of incidents and work zones.
This data visualization reveals insights into the impact of incidents and work zones on the temporal and spatial severity of traffic congestion on a section of the I-495 Capital Beltway around Washington, DC, during a 24-hour period in March 2009. Creative visualization approaches provide unique insights into data that are otherwise left undiscovered.

The DRT also can serve as a repository for sample, well-documented, publically available datasets originally collected by others outside of the TOL. In addition to sample datasets, real-time data feeds from select locations and sources may be made publically available through partnerships with State and local transportation agencies, academia, and the private sector. The DRT researchers also will make available demonstrations and examples of interesting and unique data visualizations to inspire creative approaches to data integration and mining, and the presentation of multisource, multimodal data.

Related Research

Researchers with USDOT and the Transportation Research Board (TRB) are actively pursuing many of the DRT concepts. For example, TRB's Strategic Highway Research Program (SHRP 2) Reliability Project L13, Requirements and Feasibility of a System for Archiving and Disseminating Data from SHRP 2 Reliability and Related Studies, recently investigated the feasibility of a research data archive and now is actively pursuing its development. In August 2011, TRB hosted, and FHWA cosponsored, the 6th International Visualization in Transportation Symposium on Data, during which participants exchanged information on current trends and future needs for data visualization.

Perhaps the activity of most relevance to the DRT is USDOT's ITS Real-Time Data Capture and Management program. The role of this research program is to support the development, testing, and demonstration of new and transformative transportation operations services through the provision of multisource, multimodal data. The program is focused on developing and testing data environments to meet the challenges and opportunities of operating transportation systems in a world of pervasive wireless connectivity. As described in "Real-Time Data Capture and Management Program Vision: Objectives, Core Concepts and Projected Outcomes," a data environment is a "well-organized collection of data of specific type and quality, captured and stored at regular intervals from one or more sources, systematically shared in support of one or more applications." The USDOT researchers are developing a research data exchange to serve the ITS research program, and their efforts will be a key feature highlighted within the DRT.

This research data exchange provides both archived datasets and real-time data feeds to support the development of innovative connected-vehicle applications that are designed to better manage U.S. roads and keep congestion at bay. Several archived datasets from the Vehicle Infrastructure Integration (VII) proof-of-concept tests already are available on a prototype data environment. Four new archived datasets also will be available soon, representing Pasadena, CA; San Diego, CA; Portland, OR; and Seattle, WA. The latest information on the USDOT real-time data capture program is available on the ITS Joint Program Office Web site at www.its.dot.gov.

Next Steps

Having just opened in September 2011, the DRT will continue to grow in its role as a resource for both the internal TOL operations and the external research community. The DRT will continue to support USDOT's ITS Real-Time Data Capture and Management program and other data-related research efforts. The development of a data exchange and protocols that support the development and testing of new mobility applications are key ITS research priorities for the DRT in upcoming months.

For the external research community, the DRT will provide open access to new sources and types of data to facilitate research that will build on the paradigm shift from data collection at fixed locations to mobile and multisource data collection across an entire transportation system. The strategy to support internal TOL operations, USDOT research programs, and the external research community allows the DRT to play an important part in supporting the development of new services and applications to operate U.S. roads more efficiently.

Data Environment Conceptual Depiction

Figure. This figure shows two curved arrows, one leading down to a central orange sphere labeled -Data Environment and the other leading down from the sphere. The top of the upper arrow is labeled -Data Capture, and the bottom of the upper arrow as it goes into the Data Environment sphere is labeled -Raw Data. Exiting the
sphere, the top of the lower arrow is labeled -Information, and the bottom of the lower arrow is labeled -Application.
Data environments are well organized systems for the collection, management, and provision of multisource data to support transportation operations strategies. The data environment concept is a key tenant for USDOT's ITS Real-Time Data Capture and Management program.


Gene McHale is the team leader for transportation-enabling technologies in the FHWA Office of Operations R&D. He is the lead for the DRT and is the modal colead for the ITS Real-Time Data Capture and Management program. He has a B.S. and an M.E. in systems engineering from the University of Virginia and a Ph.D. in civil engineering from Virginia Tech. He is a licensed professional engineer in Virginia.

For more information, contact Gene McHale at 202-493-3275 or gene.mchale@dot.gov.




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