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Register a new userAnalytical and simulation studies of pedestrian flow at a crossing with random update rule
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The intersecting pedestrian flow on the 2D lattice with random update rule is studied. Each pedestrian has three moving directions without the back step. Under periodic boundary conditions, an intermediate phase has been found at which some pedestrians could move along the border of jamming stripes. We have performed mean field analysis for the moving and intermediate phase respectively. The analytical results agree with the simulation results well. The empty site moves along the interface of jamming stripes when the system only has one empty site. The average movement of empty site in one Monte Carlo step (MCS) has been analyzed through the master equation. Under open boundary conditions, the system exhibits moving and jamming phases. The critical injection probability $alpha_c$ shows nontrivially against the forward moving probability $q$. The analytical results of average velocity, the density and the flow rate against the injection probability in the moving phase also agree with simulation results well.
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We analyze numerically some macroscopic models of pedestrian motion such as Hughes model [1] and mean field game with nonlinear mobilities [2] modeling fast exit scenarios in pedestrian crowds. A model introduced by Hughes consisting of a non-linear conservation law for the density of pedestrians coupled with an Eikonal equation for a potential modeling the common sense of the task. Mean field game with nonlinear mobilities is obtained by an optimal control approach, where the motion of every pedestrian is determined by minimizing a cost functional, which depends on the position, velocity, exit time and the overall density of people. We consider a parabolic optimal control problem of nonlinear mobility in pedestrian dynamics, which leads to a mean field game structure. We show how optimal control problem related to the Hughes model for pedestrian motion. Furthermore we provide several numerical results which relate both models in one and two dimensions. References [1] Hughes R.L.: A continuum theory for the flow of pedestrians, Transportation Research Part B: Methodological, 36, 507-535 (2000) [2] Burger M., Di Francesco M., Markowich P.A., Wolfram M-T.: Mean field games with nonlinear mobilities in pedestrian dynamics, Discrete and Continuous Dynamical Systems. Series B. A Journal Bridging Mathematics and Sciences, 19, 1311-1333 (2014)
This article focuses on different aspects of pedestrian (crowd) modeling and simulation. The review includes: various modeling criteria, such as granularity, techniques, and factors involved in modeling pedestrian behavior, and different pedestrian simulation methods with a more detailed look at two approaches for simulating pedestrian behavior in traffic scenes. At the end, benefits and drawbacks of different simulation techniques are discussed and recommendations are made for future research.
In addition to the $lambda$ parameter, we have found another parameter which characterize the class III, class II and class IV patterns more quantitatively. It explains why the different classes of patterns coexist at the same $lambda$. With this parameter, the phase diagram for an one dimensional cellular automata is obtained. Our result explains why the edge of chaos(class IV) is scattered rather wide range in $lambda$ around 0.5, and presents an effective way to control the pattern classes. oindent PACS: 89.75.-k Complex Systems
It is shown that for the N-neighbor and K-state cellular automata, the class II, class III and class IV patterns coexist at least in the range $frac{1}{K} le lambda le 1-frac{1}{K} $. The mechanism which determines the difference between the pattern classes at a fixed $lambda$ is found, and it is studied quantitatively by introducing a new parameter $F$. Using the parameter F and $lambda$, the phase diagram of cellular automata is obtained for 5-neighbor and 4-state cellular automata. PACS: 89.75.-k Complex Systems
We critically discuss the concept of ``synchronized flow from a historical, empirical, and theoretical perspective. Problems related to the measurement of vehicle data are highlighted, and questionable interpretations are identified. Moreover, we propose a quantitative and consistent theory of the empirical findings based on a phase diagram of congested traffic states, which is universal for all conventional traffic models having the same instability diagram and a fundamental diagram. New empirical and simulation data supporting this approach are presented as well. We also give a short overview of the various phenomena observed in panicking pedestrian crowds relevant from the point of evacuation of buildings, ships, and stadia. Some of these can be applied to the optimization of production processes, e.g. the ``slower-is-faster effect.
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