Complexes

Traffic signals are ubiquitous devices that first appeared in 1868. Recent advances in information and communications technology (ICT) have led to unprecedented improvements in such areas as mobile handheld devices (i.e., smartphones), the electric power industry (i.e., smart grids), transportation infrastructure, and vehicle area networks. Given the trend towards interconnectivity, it is only a matter of time before vehicles communicate with one another and with infrastructure. In fact, several pilots of such vehicle-to-vehicle and vehicle-to-infrastructure (e.g. traffic lights and parking spaces) communication systems are already operational. This survey of autonomous and self-organized traffic signaling control has been undertaken with these potential developments in mind. Our research results indicate that, while many sophisticated techniques have attempted to improve the scheduling of traffic signal control, either real-time sensing of traffic patterns or a priori knowledge of tra...

Self-organizing traffic lights have shown considerable improvements compared to traditional methods in computer simulations. Self-organizing methods, however, use sophisticated sensors, increasing their cost and limiting their deployment. We propose a novel approach using simple sensors to achieve self-organizing traffic light coordination. The proposed approach involves placing a computer and a presence sensor at the beginning of each block; each such sensor detects a single vehicle. Each computer builds a virtual environment simulating vehicle movement to predict arrivals and departures at the downstream intersection. At each intersection, a computer receives information across a data network from the computers of the neighboring blocks and runs a self-organizing method to control traffic lights. Our simulations showed a superior performance for our approach compared with a traditional method (a green wave) and a similar performance (close to optimal) compared with a self-organizing ...

We apply game theory to a vehicular traffic model to study the effect of driver strategies on traffic flow. The resulting model inherits the realistic dynamics achieved by a two-lane traffic model and aims to incorporate phenomena caused by driver-driver interactions. To achieve this goal, a game-theoretic description of driver interaction was developed. This game-theoretic formalization allows one to model different lane-changing behaviors and to keep track of mobility performance. We simulate the evolution of cooperation, traffic flow, and mobility performance for different modeled behaviors. The analysis of these results indicates a mobility optimization process achieved by drivers’ interactions. Cortés-Berrueco LE, Gershenson C, Stephens CR (2016) Traffic Games: Modeling Freeway Traffic with Game Theory. PLoS ONE 11 (11): e0165381. doi: 10.1371/journal.pone.0165381

Cities are changing constantly. All urban systems face different conditions from day to day. Even when averaged regularities can be found, urban systems will be more efficient if they can adapt to changes at the same speeds at which these occur. Technology can assist humans in achieving this adaptation. Inspired by cybernetics, we propose a description of cities as adaptive systems. We identify three main components: information, algorithms, and agents, which we illustrate with current and future examples. The implications of adaptive cities are manifold, with direct impacts on mobility, sustainability, resilience, governance, and society. Still, the potential of adaptive cities will not depend so much on technology as on how we use it. Adaptive Cities: A Cybernetic Perspective on Urban Systems Carlos Gershenson, Paolo Santi, Carlo Ratti http://arxiv.org/abs/1609.02000

Urban mobility systems are composed multiple elements with strong interactions, i.e. their future is co-determined by the state of other elements. Thus, studying components in isolation, i.e. using a reductionist approach, is inappropriate. I propose five recommendations to improve urban mobility based on insights from the scientific study of complex systems: use adaptation over prediction, regulate interactions to avoid friction, use sensors to recover real time information, develop adaptive algorithms to exploit that information, and deploy agents to act on the urban environment. Improving Urban Mobility by Understanding its Complexity Carlos Gershenson http://arxiv.org/abs/1603.04267

The slower is faster (SIF) effect occurs when a system performs worse when its components try to be better. Thus, a moderate individual efficiency actually leads to a better systemic performance. The SIF effect takes place in a variety of phenomena. We review studies and examples of the SIF effect in pedestrian dynamics, vehicle traffic, traffic light control, logistics, public transport, social dynamics, ecological systems, and adaptation. Drawing on these examples we generalize common features of the SIF effect and suggest possible future lines of research. When slower is faster Carlos Gershenson, Dirk Helbing http://arxiv.org/abs/1506.06796 Update : paper was published in Complexity : http://onlinelibrary.wiley.com/doi/10.1002/cplx.21736/abstract

On November 10th, a day after the 25th anniversary of the fall of the Berlin wall , our team Living Mobilities from Mexico City was declared winner of the third edition of the Audi Urban Future Award . Together with José Castillo (team leader, watch the video from his final presentation ) from Arquitectura 911 and Gabriella Gómez-Mont from the Laboratorio para la Ciudad , we were proud and delighted to be declared winners by an international jury , considering the great proposals presented by the teams from Berlin, Boston, and Seoul. Audi Urban Future Award 2014 - Data collectors from Mexico City win the Award 2014 from THE AUDI URBAN FUTURE INITIATIVE on Vimeo . Our project proposes to create a new social contract, assisted by technology, to improve mobility not only in terms of efficiency, but also in terms of quality of life. This focusses on Mexico City, but has the potential to be extended to other megacities in Latin America, Asia, and Africa. We have a big city wi...

We apply measures of complexity, emergence, and self-organization to an urban traffic model for comparing a traditional traffic-light coordination method with a self-organizing method in two scenarios: cyclic boundaries and non-orientable boundaries. We show that the measures are useful to identify and characterize different dynamical phases. It becomes clear that different operation regimes are required for different traffic demands. Thus, not only is traffic a non-stationary problem, requiring controllers to adapt constantly; controllers must also change drastically the complexity of their behavior depending on the demand. Based on our measures and extending Ashby’s law of requisite variety, we can say that the self-organizing method achieves an adaptability level comparable to that of a living system. Zubillaga, Darío; Cruz, Geovany; Aguilar, Luis D.; Zapotécatl, Jorge; Fernández, Nelson; Aguilar, José; Rosenblueth, David A.; Gershenson, Carlos. 2014. "Measuring the Complexit...

We apply measures of complexity, emergence and self-organization to an abstract city traffic model for comparing a traditional traffic coordination method with a self-organizing method in two scenarios: cyclic boundaries and non-orientable boundaries. We show that the measures are useful to identify and characterize different dynamical phases. It becomes clear that different operation regimes are required for different traffic demands. Thus, not only traffic is a non-stationary problem, which requires controllers to adapt constantly. Controllers must also change drastically the complexity of their behavior depending on the demand. Based on our measures, we can say that the self-organizing method achieves an adaptability level comparable to a living system. Measuring the Complexity of Self-organizing Traffic Lights Dario Zubillaga, Geovany Cruz, Luis Daniel Aguilar, Jorge Zapotecatl, Nelson Fernandez, Jose Aguilar, David A. Rosenblueth, Carlos Gershenson http://arxiv.org/abs/1402.01...

This article presents an overview of current and potential applications of living technology to some urban problems. Living technology can be described as technology that exhibits the core features of living systems. These features can be useful to solve dynamic problems. In particular, urban problems concerning mobility, logistics, telecommunications, governance, safety, sustainability, and society and culture are presented, and solutions involving living technology are reviewed. A methodology for developing living technology is mentioned, and supraoptimal public transportation systems are used as a case study to illustrate the benefits of urban living technology. Finally, the usefulness of describing cities as living systems is discussed. Gershenson, C. (2013). Living in living cities. Artificial Life , 19  (3 & 4): 401–420. http://www.mitpressjournals.org/doi/abs/10.1162/ARTL_a_00112   Free Access Related to this  TED@SãoPaulo talk . Check the rest of the...

The  MIT Center for Collective Intelligence  has developed a collaborative platform, the Climate CoLab , where thousands of people seek collectively solutions for problems related to climate change. The CoLab is running 18 contests  for different categories. We are finalists in the Transportation Efficiency contest with the project " Self-organizing traffic lights ". Being this a collective platform, people have to vote on the projects they prefer. Teams with the most votes for each contest will be invited to present at the  Crowds and Climate Conference at MIT in November. Key implementers will be there. If you would like traffic lights to work better, please share and  vote for our proposal, " Self-organizing traffic lights " (quick registration required). Summary The optimal coordination of traffic lights is an extremely complex problem. Moreover, traffic situations change constantly, demanding everchanging solutions. Most traffic lights ar...

Large cities benefit from public transport. It is simply more efficient to transport hundreds or thousands of people together (trans, trams, buses) than each of them individually (cars, taxis). However, public transportation systems have to match the passenger demand. If there are relatively too few passengers for the public transport capacity, there will be idling and waste of resources. If there are relatively too many passengers, the system will be saturated and become inefficient. This balance between public transport capacity and demand is very tricky, since many cities change their transportation demands much faster than their public transport infrastructure. There is also a clear correlation between the cost, building time, and capacity of transportation systems. Trains and metros are high cost, high capacity, making them unsuitable for cities of roughtly less than a million inhabitants. Trams and bus rapid transit (BRT) are intermediate: they have less capacity, but they...

Earlier this month I gave a seminar back at the VUB, one of my alma maters. Here is a video recording, more details here  or below. Application of living technology to urban problems   Carlos Gershenson  (Universidad Nacional  Autónoma de México)  Abstract: I will present an overview of current and potential applications of living technology to urban problems. Living technology can be described as technology that exhibits the core features of living systems. These features can be useful to solve dynamic problems. In particular, urban problems concerning mobility, logistics, telecommunications, governance, safety, sustainability, and society and culture are presented, while solutions involving living technology are reviewed. A methodology for developing living technology is mentioned, while supraoptimal public transportation systems are used as a case study to illustrate the benefits of urban living technology. Finally, the usefulness of de...

Last November I had the honor of participating in TEDxDF with a talk on self-organizing traffic lights. You can watch the video (in Spanish) at: http://tedxtalks.ted.com/video/TEDxDF-Carlos-Gershenson-Semfor  or  http://www.youtube.com/watch?v=QohrFmeNnVw Mejorar el transporte público de la Ciudad de México es una idea que a todos se nos ocurre, pero pocos hacemos algo al respecto. Este no es el caso de Carlos, un apasionado del estudio científico de la complejidad: ¿Cómo podemos diseñar componentes de un sistema para que, por medio de sus interacciones, realicen una función deseada a nivel del sistema? Con su ponencia Carlos responderá esta pregunta y expondrá ideas aplicables al DF para mejorar diversos medios de transporte, afectando positivamente la calidad de vida de la población.

This paper presents and overview of current and potential applications of living technology to urban problems. Living technology can be described as technology that exhibits the core features of living systems. These features can be useful to solve dynamic problems. In particular, urban problems concerning mobility, logistics, telecommunications, governance, safety, sustainability, and society and culture are presented, while solutions involving living technology are reviewed. Finally, the usefulness of describing cities as living systems is discussed. Gershenson, C. (2011). Living in Living Cities. C3 Report 2011.09.  http://arxiv.org/abs/1111.3659

Gershenson, C. & D. A. Rosenblueth (2011). Self-organizing traffic lights at multiple-street intersections . C3 Report 2011.02 Summary : Traffic light coordination is a complex problem. In this paper, we extend previous work on an abstract model of city traffic to allow for multiple street intersections. We test a self-organizing method in our model, showing that it is close to theoretical optima and superior to a traditional method of traffic light coordination.    Abstract : The elementary cellular automaton following rule 184 can mimic particles flowing in one direction at a constant speed. This automaton can therefore model highway traffic. In a recent paper, we have incorporated intersections regulated by traffic lights to this model using exclusively elementary cellular automata. In such a paper, however, we only explored a rectangular grid. We now extend our model to more complex scenarios employing an hexagonal grid. This extension shows first that our model can ...