Simulating the city traffic complexity induced by traffic light periods.

We revisited the global traffic light optimization problem through a cellular automata model, which allows us to address the relationship between the traffic lights and car routing. We conclude that both aspects are not separable. Our results show that a good routing strategy weakens the importance of the traffic light period for mid-densities, thus limiting the parameter space where such optimization is relevant. This is confirmed by analyzing the travel time normalized by the shortest path between the origin and destination. As an unforeseen result, we report what seems to be a power-law distribution for such quantities, indicating that the travel time distribution slowly decreases for long travel times. The power-law exponent depends on the density, traffic light period, and routing strategy, which in this case is parametrized by the tendency of agents to abandon a route if it becomes stagnant. These results could have relevant consequences on how to improve the overall traffic efficiency in a particular city, thus providing insight into useful measurements, which are often counter-intuitive, which may be valuable to traffic controllers that operate through traffic light periods and phases.

Does following optimized routes for single cars improve car routing?

We study the impact of deserting a pre-established path, determined by a navigation software, on the overall city traffic. To do so, we consider a cellular automaton model for vehicular traffic, where the cars travel between two randomly assigned points in the city following three different navigation strategies based on the minimization of the individual paths or travel times. We found, in general, that, above a critical car density, the transport improves in all strategies if we decrease the time that the vehicles persist in trying to follow a particular strategy when a route is blocked, namely, the mean flux increases, the individual travel times decrease, and the fluctuations of density in the streets decrease; consequently, deserting helps prevent traffic jams.

Growth of Ni nanoclusters on irradiated graphene: a molecular dynamics study.

We studied the soft landing of Ni atoms on a previously damaged graphene sheet by means of molecular dynamics simulations. We found a monotonic decrease of the cluster frequency as a function of its size, but few big clusters comprise an appreciable fraction of the total number of Ni atoms. The aggregation of Ni atoms is also modeled by means of a simple phenomenological model. The results are in clear contrast with the case of hard or energetic landing of metal atoms, where there is a tendency to form mono-disperse metal clusters. This behavior is attributed to the high diffusion of unattached Ni atoms, together with vacancies acting as capture centers. The findings of this work show that a simple study of the energetics of the system is not enough in the soft landing regime, where it is unavoidable to also consider the growth process of metal clusters.

Characterization of the nontrivial and chaotic behavior that occurs in a simple city traffic model.

We explore in detail the nontrivial and chaotic behavior of the traffic model proposed by Toledo et al. [Phys. Rev. E 70, 016107 (2004)] due to the richness of behavior present in the model, in spite of the fact that it is a minimalistic representation of basic city traffic dynamics. The chaotic behavior, previously shown for a given lower bound in acceleration/brake ratio, is examined more carefully and the region in parameter space for which we observe this nontrivial behavior is found. This parameter region may be related to the high sensitivity of traffic flow that eventually leads to traffic jams. Approximate scaling laws are proposed.

Resonance, criticality, and emergence in city traffic investigated in cellular automaton models.

The complex behavior that occurs when traffic lights are synchronized is studied for a row of interacting cars. The system is modeled through a cellular automaton. Two strategies are considered: all lights in phase and a "green wave" with a propagating green signal. It is found that the mean velocity near the resonant condition follows a critical scaling law. For the green wave, it is shown that the mean velocity scaling law holds even for random separation between traffic lights and is not dependent on the density. This independence on car density is broken when random perturbations are considered in the car velocity. Random velocity perturbations also have the effect of leading the system to an emergent state, where cars move in clusters, but with an average velocity which is independent of traffic light switching for large injection rates.

Optimal control in a noisy system.

We describe a simple method to control a known unstable periodic orbit (UPO) in the presence of noise. The strategy is based on regarding the control method as an optimization problem, which allows us to calculate a control matrix A. We illustrate the idea with the Rossler system, the Lorenz system, and a hyperchaotic system that has two exponents with positive real parts. Initially, a UPO and the corresponding control matrix are found in the absence of noise in these systems. It is shown that the strategy is useful even if noise is added as control is applied. For low noise, it is enough to find a control matrix such that the maximum Lyapunov exponent lambda(max)<0, and with a single non-null entry. If noise is increased, however, this is not the case, and the full control matrix A may be required to keep the UPO under control. Besides the Lyapunov spectrum, a characterization of the control strategies is given in terms of the average distance to the UPO and the control effort required to keep the orbit under control. Finally, particular attention is given to the problem of handling noise, which can affect considerably the estimation of the UPO itself and its exponents, and a cleaning strategy based on singular value decomposition was developed. This strategy gives a consistent manner to approach noisy systems, and may be easily adapted as a parametric control strategy, and to experimental situations, where noise is unavoidable.

Universal and nonuniversal features in a model of city traffic.

The complex behavior that occurs when traffic lights are synchronized is studied. Two strategies are considered: all lights in phase, and a "green wave" with a propagating green signal. It is found that traffic variables such as traveling time, velocity, and fuel consumption, near resonance, follow critical scaling laws. For the green wave, it is shown that time and velocity scaling laws hold even for random separation between traffic lights. These results suggest the concept of transient resonances, which can be induced by adaptively changing the phase of traffic lights. This may be important to consider when designing strategies for traffic control in cities, where short trajectories, and thus transient solutions, are likely to be relevant.

Modeling traffic through a sequence of traffic lights.

We introduce a microscopic traffic model, based on kinematic behavior, which consists of a single vehicle traveling through a sequence of traffic lights that turn on and off with a specific frequency. The reconstructed function that maps the state of the vehicle from light to light displays complex behavior for certain conditions. This chaotic behavior, which arises by the discontinuous nature of the map, displays an essential ingredient in traffic patterns and could be of relevance in studying traffic situations.