Worlds Collide: Using Fluid Dynamics to Solve Urban Traffic Woes

Imagine being stuck in your car—60 miles from your destination—moving just a few miles per day, for 11 days. In August 2010, this nightmare became a reality for thousands of Chinese motorists who were attempting to travel into the nation’s capital and found themselves stranded in gridlock on the Beijing-Tibet Expressway. While traffic congestion has long been a major urban issue, the development of large population centers in emerging nations, such as China, has pushed many policymakers to consider new and sometimes controversial infrastructure measures to combat the problem, such as cutting lanes and implementing congestion charges.

However, while researchers have found that there are major opportunity and environmental costs of traffic congestion, many urban planners and policymakers disagree on the best solutions to the problem. Researchers Theodore Tsekeris and Nikolas Geroliminis in their paper for the Journal of Urban Economics titled “City size, network structure and traffic congestion” point to a new way of analyzing traffic in urban areas utilizing fluid dynamics, the science of measuring fluids in flow, that provides policymakers with better insight into this issue.

Using physics to study traffic flow is not a new idea. As early as the 1960s, physicist Robert Herman and chemist Ilya Prigogine were using kinetics to describe traffic congestion. According to Tsekeris and Geroliminis, however, the current predictive diagrams for traffic congestion are incomplete because of the assumptions kinetic diagrams made on entry and exit points in the overall traffic network. Tsekeris and Geroliminis instead suggest that policymakers should use the Macroscopic Fundamental Diagram (MFD) to accurately study the physics of traffic flow.

Instead of graphing traffic flow on a block-by-block basis, the MFD traces traffic flow regionally, which allows shifting congestion from block to block to be observed throughout the day. As a result, the MFD is not only a function of traffic density, vehicle speed, lane size, and time, but also overall city size and network structure. Tsekeris and Geroliminis argue that the MFD, therefore, can more accurately predict hypercongestion–the point in which roads jam—and the overall maximum capacity of a traffic network.

To show the calculative power of the MFD, Tsekeris and Geroliminis construct a model of a theoretical city on which they impose constraints to test their diagram. These theoretical models agree with previous fieldwork done in Yokohama, Japan by Geroliminis with researcher Carlos Daganzo, which demonstrate that the MFD can be used accurately on a large urban area to analyze congestion. Reviewing their models, Tsekeris and Geroliminis suggest that policymakers can use the MFD to determine the control strategies and optimal land use that will best fit a specific city’s overall traffic network without having to guess on adjustments to hypercongestion, which, Tsekeris and Geroliminis argue, other models are unable to take into account.

The global population is moving more and more toward urban centers, with a majority of the world’s population living in cities, according to data from the World Bank. As the world’s cities expand, policymakers will be under increasing pressure to manage these large traffic networks effectively and under tighter budget constraints. By using traffic diagrams, such as the MFD, city leaders will be able create accurate predictive models in order to best manage these vast networks without wasting resources. Otherwise hypercongestion, such as 11 days stuck on the Beijing-Tibet Expressway, may become the norm.

Feature Photo: cc/(Sippanont Samchai)