Research Areas
A Wide Range of Research Areas in Transportation
Research conducted by the members of the Center for Transportation Studies is wide ranging and extensive, covering such areas as intelligent transportation systems, transportation and land use, traffic simulation, highway safety, freight operations, and traffic operations. Our projects include both basic research and practical applications.
Information Technology for Intelligent Transportation Systems
The goal of our intelligent transportation systems initiative is to improve the value of the data collected by transportation information systems. In essence, we are working to help departments of transportation gain a better return on their investment in the communications, sensor, and computer network technologies that monitor transportation in major metropolitan areas.
As part of this effort, the Center for Transportation Studies has undertaken a number of initiatives to enhance the quality of data produced by the existing ITS systems and to develop complementary data sources from other technologies, including cell phones and closed circuit television. We are also a national leader in developing the systems and procedures needed to archive ITS data efficiently. We are undertaking a major redesign of our data warehouse, which will make it the most sophisticated database of its kind in the world, and are augmenting our data archives to include vehicle classification data, weather data, and city signal system data, among other sources. At the same time, we are pioneering ways to make this data more accessible to a wide variety of users, including local transportation departments, police departments, city and county planners, businesses, and others.
Measurement, Simulation, and Forecasting
Gathering ITS data is just a first step. The next is to determine the most relevant data and to convert it to forms that are meaningful for transportation specialists. The center’s researchers are deeply involved in these efforts as well.
One area that Center researchers have focused on is developing and refining effective measures of system performance. Center researchers have approached this problem on both the micro and macro levels, assessing the accuracy of such standards as vehicle mile traveled (VMT) and developing ways to quantify congestion. They have also worked to improve the accuracy of simulations by developing a procedure for simulation modeling calibration and validation for some of the most widely used models used in traffic operations and management analyses.
The Center for Transportation Studies has also been a leader in the application of nonparametric regression forecasting of traffic flow under typical conditions. Center researchers are now extending their studies to abnormal conditions, such as accidents or major sporting and cultural events. The challenge is to find ways to conduct computing-intensive nonparametric analysis rapidly enough to produce useful forecasts in a quickly evolving situation. Utilizing data from Hampton Roads and Northern Virginia that has been archived at the STL, faculty have explored ways to simplify the analysis, making the process quicker and more efficient.
Enhancing Traffic Operations
The ultimate proof of the value of ITS data is its ability to enhance traffic operations. Center researchers are harnessing these data to create improvements on a number of fronts. Center researchers are constantly striving to make the data generated by intelligent transportation systems more easily intelligible and useful to decision-makers. One recent effort involved creating an updated Web-based congestion map for the Northern Virginia Smart Traffic Signal System that includes more understandable system performance measures such as approach delay and the volume-to-capacity ratio.
Optimizing traffic signal timing is among the most cost-effective ways of improving mobility, allaying commuting-related stress and reducing fuel consumption and automobile emissions. Using archived data at the STL and additional field data, Center researchers have calibrated and validated several commercial optimization programs using stochastic and microscoping simulation models, increasing their accuracy. They have also been active in developing a low-cost, easy-to-implement adaptive traffic signal system and used STL’s archived data as a foundation for creating more realistic time-of-day plans.
Finally, center researchers have been particularly active in developing techniques for traffic management that are more responsive to actual situations than existing methods because they are more comprehensive. Members of the center have developed variable speed limit control logic for work zones that incorporates both safety and mobility measures. They are also developing more robust guidelines for left-turn lanes at signalized and unsignalized intersections that are based on more sophisticated gap acceptance model.
Highway Safety and Security
ITS data has the potential to make our roadways safer than ever before. This data can help researchers better analyze the causes of traffic incidents and help us find better ways to prevent them. Members of the center are working to increase the accuracy of crash predictions developing safety surrogate measures that incorporate both speed and headway information. Other faculty are working to augment traditional models for congestion forecasting and management with information about the impact of these strategies on the frequency of crashes. Center researchers have also broadened the scope of accident analysis to include the effect of accidents on travel in the opposite direction
The underlying methods used to understand and improve safety can also be applied to security issues as well. Currently there is no standardized system or set procedure for screening air cargo in the United States. Center researchers are analyzing cargo flow from its entrance onto airport property to its exit, identifying all situations where there is a potential security hazard and propose solutions to minimize the security risk without incurring delay or increased costs.
Freight Operations and Planning
The increase of trucks on our highways and new, more stringent hours of service regulations are placing a burden on both public rest areas and private truck stops in Virginia. When rest areas are full, tired drivers may exceed their hours of service or park on shoulders or ramps and, in the process, contribute to accidents. Faculty members at the center are systematically analyzing this problem in Virginia, assessing the supply of and demand for commercial truck parking, and evaluating the use of variable message signs to alert drivers about the location of available parking spaces.
UVA researchers are also looking at the supply chains that generate truck traffic. Focusing again on Virginia, they have engaged in a multiyear study tracing the truck traffic needed in the production, transportation, warehousing, retailing, and consumption of 15 key commodities. The goal is to identify aspects of the interrelated corporate decisions that impact transportation planning. Such disaggregated data has the potential to dramatically improve forecasting.
Integrated Transportation Planning and Management
The Center for Transportation Studies has been instrumental in breaking down organizational barriers so that transportation data can be better shared among transportation agencies and other stakeholders in our transportation system. For instance, Center researchers are examining ways to integrate data from the Northern Virginia Smart Traffic Center and the Northern Virginia Smart Traffic Signal System and, in particular, to develop better methods to adjust the control of signalized intersections adjacent to freeways so that they can better respond to non-recurring congestion.
The Center is an active participant in developing the Capital Area Wireless Integrated Network (CapWIN), a state-of-the-art wireless integrated mobile data communications network being implemented to support federal, state, and local law enforcement, transportation, and public safety agencies in the Washington, D.C., metropolitan area. Working with the University of Maryland, the STL is leading the CapWIN transportation research effort. Among other initiatives, it is currently developing a prototype visualization tool that will allow systems managers to view, access, and manage information from their own network as well as the CapWIN network from multiple communications platforms.
Transportation and Land Use
The controlled environment of a university campus makes it an excellent environment in which to develop innovative land use strategies and to study how land use planning affects transportation. Center researchers are examining how land use at universities affects the various elements of a comprehensive transportation system that might include ridesharing, parking demand management, transit, bicycling, and walking. They have also made extensive use of geographic information systems in considering the factors that make walking and bicycling attractive strategies for people living in residential areas.
Center researchers are also collaborating with environmental scientists who are trying to gain an overview of carbon monoxide fluxes in the Piedmont of Virginia. Scientists know that some carbon monoxide is a product of biogenic hydrocarbons produced by vegetation. By examining traffic information from the last 20 years, they are determining how much carbon monoxide is generated by vehicles.
| 
