RESUMO
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.
Assuntos
Dinâmica não Linear , Meios de Transporte , Algoritmos , Comportamento , Cidades , Simulação por Computador , Humanos , Modelos Estatísticos , Veículos Automotores , Tempo de ReaçãoRESUMO
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.
Assuntos
Biofísica/métodos , Algoritmos , Automação , Automóveis , Análise por Conglomerados , Humanos , Modelos Estatísticos , Modelos Teóricos , Meios de TransporteRESUMO
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.