Moscow’s Traffic Control Center and the performative mythology of congestion management reveals cultural narratives of the city as a real-time digital model, and calls for alternative literacies of model-making and urban simulation.
Michael Batty, Bartlett Professor of Planning at University College London
Post-Soviet Moscow is one of the most congested cities in the world. Over the past thirty years, it has seen exponential growth in the number of vehicles on the streets—every day there are over 3.6 million cars driving in the city, with 200,000 new cars registered every year. This is happening despite the success of Moscow’s extensive underground rapid transit system—one of the world’s most reliable and efficient—among other means of available transportation. The growth of car ownership is often attributed to an intense desire for personal freedom and a market economy that flourished after the fall of the USSR, along with a need for a protective bubble in an overstimulating city. Coupled with the specificities of Moscow’s spatial conditions, high mobility has become a definitive quality of the city.
There was a need to reverse the negative tendencies and prevent an imminent “traffic collapse.” In 1999, the Moscow Traffic Control Center was established to develop solutions for the growing intensity of road network use and traffic management issues in the city. The Center was entrusted with a broad mandate of planning, preparing, and organizing the road network within the borders of Moscow, along with traffic research and control over its operations. Initially designed to employ only five people, the Center now has staff resources for 24/7 monitoring of traffic conditions, accompanying a mega dashboard—similar ones exist anywhere from Rio de Janeiro to Dublin—that displays real-time data from numerous sensors, traffic lights, and news outlets. The analysts on-site are able to “disperse congestion in one click” by visually identifying issues on the road as they appear.
The Center is a landmark project for Moscow’s city administration and a matter of pride—it is regularly visited by both high officials and children on school trips. The spatial organization of the control room itself and the way the dashboard is positioned are clues to the significance of this giant screen. While the bulk of the job is done by a manual override of the analysts themselves, the dashboard symbolizes possibilities of control. Although the Center confirms its effectiveness (reduced number of accidents, injuries, and traffic collisions) and declares that “progress is evident,” arguably, the larger function of the traffic dashboard is purely performative.
The dashboard acts as a public face and communication apparatus, while computation and modeling are run separately behind the scenes. The dashboard provides evidence that the present and the future can be simulated and controlled, contributing to the mythology of traffic management. Research finds that humans have difficulty conceptualizing relations and complex systems. For that purpose, graphical representation is more effective, as it does not bear the limitations of the discursivity of language. As in the case of Moscow, more often than not only a fraction of a rather complex urban model is provided as a final visual outcome, offering limited or no methodology. It reveals a certain governing culture in its center—city as a system to be monitored and controlled. What does this disposition mean for the issues of congestion? Are there cultures that produce alternative models?
Philosopher Michel Foucault, one of the key theorists on institutionalized patterns of knowledge, found that there can be a number of discourses circulating in a society at any point in time, with some of them prevailing. From this perspective, analysis of the dominating practices of city simulation allows to identify their inherent cultural properties—arguably, congestion being one of them. Hence, a demystified—but not oversimplified—modeling is crucial in order to grasp the underlying principles and narratives behind models presented to the public in Moscow and worldwide.
According to Bill Hillier, a pioneer of the “space syntax” theory that provided insights into the mutually constructive relations between society and space, the presence of narratives, social institutions, and cultures is implicit in space-time events but not seen in them. These space-time appearances are not the discourse itself, only its “momentary and fragmentary realizations.” On the other hand, a particular configuration of space—and its intrinsic qualities—reflects and enforces the intentions of existing power structures. In turn, it can be argued that models of urban space are designed depending on the nature of the dominant culture, considering top-down and bottom-up dynamics in various proportions.
To explain the viability and urgency to study the built environment in an attempt to delineate ideology and political process, architect and historian Manfredo Tafuri defined architecture as pure ideology, an expression of hidden consciousness of the dominant social structure. Following Tafuri, architect Pier Vittorio Aureli in his work considers a city to be a result of political intention, manifesting itself in distinct architectural designs. A city is shaped by material forces, as well as cultural visions; it is constructed from the continuous interaction between ideas and spatial conditions.
Some underlying principles of neoliberal design are outlined by architectural theorist Douglas Spencer: systematic response to changes in the variables of the environment, spontaneous orders, and self-organization. The power in this kind of social system is not applied as vertical external force upon a human, but through horizontal relations and constant self-adjustment. This line of thought is echoed in space syntax studies: it has been argued that spatial concepts change and evolve over time, through values ingrained in particular social and institutional contexts. In view of this, the Moscow Traffic Control dashboard represents and reinforces the culture of a city that is manageable and adjustable in real-time.
Today advanced urban models are built in consideration of the intrinsic spatiality of human activity, relatedness of space, and an appreciation that neither individual parts nor related space-time events convey an understanding of city behavior in its totality. That entails configurational or complex network modeling, rather than an analysis of a singular urban event or a subset of those. For urban congestion infrastructure, that means models that go beyond “road situation” analysis of cars, drivers, and traffic lights and equally do not focus exclusively on traffic. It is a kind of model that shifts the attention from actors—such as human error of breaking a traffic rule—to strategic network modeling and design.
Possibilities of chaos and volatility
In complexity theory for urban analysis and design, developed by urban planner, geographer, and spatial data scientist Michael Batty, scaling allows to model urban growth through self-similarity and pertains to how elements—as well as the entire city in question—change in shape and size as their elements and their wholes grow, and describes the basic relations involved. Scaling provides focus for forms of simulation and visualization, where models are consistent with an understanding that both bottom-up and top-down processes need to be understood. Apparently uncoordinated action (but not random or chaotic) leads to an order of patterns, whose structure emerges from those actions.
Scaling laws help formulate universal rules, but coming from statistical physics, they tend to be generalizations of specific properties detectable within the field. When management and planning are involved, these laws can be challenged—but invariably reassert themselves in the aftermath. Chaos and volatility are thought to be absorbed in the city “organism” and although they have a tendency to impact physical form, they do not alter or affect the macro scaling laws, dominating through the invariant aspects of human behavior—peculiarities of moving and seeing space and the indispensable configurations of the built environment, among other things.
If cities are becoming more complex over time, then the dominant narrative would embrace that degree of change in order to evolve. One of the key concepts in complexity theory—emergence—underpins the idea that multiple decisions made by actors in the system often give rise to unexpected, innovative, and surprising behaviors. Complexity in cities means continual change. Urban simulation models initially implying a possibility to forecast at a cross section in time were the first to adopt and deal with such dynamics.
Cities were first formally considered to have characteristics of a system and to be treated as such. This gave rise to the definition of a city as a specific collection of communicating entities, striving for an equilibrium, but with separate and clear functionalities that allow for their control, planning, and management. In order for this approach to work, cities had to be treated as distinct from social and political processes, which were assumed largely benign and having little impact. The model was found false, as urban space does not exist in a benign environment, but in fact is an intrinsic part of human activity. Cities were found to be ever-changing and nowhere close to a controlled equilibrium.
The approach that treated cities as organized to a point of equilibrium from the top-down has shifted to the idea that cities “organically” evolve from the bottom up. This switch in thinking is best pictured in the transition from thinking of “cities as machines” to “cities as organisms.” The notion of system equilibrium has been replaced with possibilities and considerations of chaos, catastrophes, and bifurcations. Urban processes give rise to morphologies that illustrate fractal patterns and self-similarity. As networks and interactions sustain cities through movement, mobility, and transportation, these processes give rise to the diffusion and segregation of different spatial activities.
A practice of distributed model-making
As argued by Michael Batty, the deep structure of cities is characterized by uncertainty. In fact, most simulation models enable one to make “what if” arguments. As absolute predictions of the future are intrinsically impossible, these are conditional predictions. Their outcomes are not likely to occur, and they are often highly limited by research scope, and useful primarily for exploring the solution space of the problem—identifying many probable scenarios for debate and discussion. It is never possible to say that a prediction has or has not been borne out because the future is unknowable—a city can never be perfectly simulated.
Facilitated by easy access to tools, the number of models created daily is growing exponentially—many of them claim to provide increased “efficiency,” “smartness,” and convenience for city residents. In human systems, things often appear possible because we feel that we can have control over our own destiny. In reality, modeling itself is just about getting a grasp of what the future might be like. Even if this will never be correct, it is a way of exploring what might lie ahead. A different way of thinking should be factored into the way simulation is applied in urban design practice—not only to model futures, but to explore and understand the guiding narratives ingrained in our urban imaginary and the kind of cultures they enable.
The Moscow real-time traffic dashboard reveals an ever-changing city in constant need of supervision and correction. Congestion is created and dispersed momentarily and has become an adjustable feature of the traffic management culture, rather than an issue to be solved. In the current state of things, arguably, the survival of congestion plays into the discourse of traffic management and the possibility of a “smart” city, controlled through an impeccable “digital twin.” The fact that despite all efforts Moscow is still in the top of the most congested cities list signals a need for a change in culture—of both modeling and design—for one that does not harbor a need for a congested city in order to validate its managerial functions. The city needs not one mega-model, but many different models created within a renewed distributed practice of model-making through advanced literacy in urban simulation.
Images: mos.ru (Official site of the Mayor of Moscow).
The essay is part of the Cultures of Congestion special project by Strelka and ArtRebels.