Traffic at the Edge of Chaos

We use a very simple description of human driving behavior to simulate traffic. The regime of maximum vehicle flow in a closed system shows near-critical behavior, and as a result a sharp decrease of the predictability of travel time. Since Advanced Traffic Management Systems (ATMSs) tend to drive larger parts of the transportation system towards this regime of maximum flow, we argue that in consequence the traffic system as a whole will be driven closer to criticality, thus making predictions much harder. A simulation of a simplified transportation network supports our argument.Comment: Postscript version including most of the figures available from http://studguppy.tsasa.lanl.gov/research_team/. Paper has been published in Brooks RA, Maes P, Artifical Life IV: ..., MIT Press, 199

A Simplified Cellular Automaton Model for City Traffic

We systematically investigate the effect of blockage sites in a cellular automaton model for traffic flow. Different scheduling schemes for the blockage sites are considered. None of them returns a linear relationship between the fraction of ``green'' time and the throughput. We use this information for a fast implementation of traffic in Dallas.Comment: 12 pages, 18 figures. submitted to Phys Rev

Experiences with a simplified microsimulation for the Dallas/Fort Worth area

We describe a simple framework for micro simulation of city traffic. A medium sized excerpt of Dallas was used to examine different levels of simulation fidelity of a cellular automaton method for the traffic flow simulation and a simple intersection model. We point out problems arising with the granular structure of the underlying rules of motion.Comment: accepted by Int.J.Mod.Phys.C, 20 pages, 14 figure

Non-concave fundamental diagrams and phase transitions in a stochastic traffic cellular automaton

Within the class of stochastic cellular automata models of traffic flows, we look at the velocity dependent randomization variant (VDR-TCA) whose parameters take on a specific set of extreme values. These initial conditions lead us to the discovery of the emergence of four distinct phases. Studying the transitions between these phases, allows us to establish a rigorous classification based on their tempo-spatial behavioral characteristics. As a result from the system's complex dynamics, its flow-density relation exhibits a non-concave region in which forward propagating density waves are encountered. All four phases furthermore share the common property that moving vehicles can never increase their speed once the system has settled into an equilibrium

Patterns in Illinois Educational School Data

We examine Illinois educational data from standardized exams and analyze primary factors affecting the achievement of public school students. We focus on the simplest possible models: representation of data through visualizations and regressions on single variables. Exam scores are shown to depend on school type, location, and poverty concentration. For most schools in Illinois, student test scores decline linearly with poverty concentration. However Chicago must be treated separately. Selective schools in Chicago, as well as some traditional and charter schools, deviate from this pattern based on poverty. For any poverty level, Chicago schools perform better than those in the rest of Illinois. Selective programs for gifted students show high performance at each grade level, most notably at the high school level, when compared to other Illinois school types. The case of Chicago charter schools is more complex. In the last six years, their students' scores overtook those of students in traditional Chicago high schools.Comment: 9 pages, 6 figure

Modeling Two Dimensional Magnetic Domain Patterns

Two-dimensional magnetic garnets exhibit complex and fascinating magnetic domain structures, like stripes, labyrinths, cells and mixed states of stripes and cells. These patterns do change in a reversible way when the intensity of an externally applied magnetic field is varied. The main objective of this contribution is to present the results of a model that yields a rich pattern structure that closely resembles what is observed experimentally. Our model is a generalized two-dimensional Ising-like spin-one Hamiltonian with long-range interactions, which also incorporates anisotropy and Zeeman terms. The model is studied numerically, by means of Monte Carlo simulations. Changing the model parameters stripes, labyrinth and/or cellular domain structures are generated. For a variety of cases we display the patterns, determine the average size of the domains, the ordering transition temperature, specific heat, magnetic susceptibility and hysteresis cycle. Finally, we examine the reversibility of the pattern evolution under variations of the applied magnetic field. The results we obtain are in good qualitative agreement with experiment.Comment: 8 pages, 12 figures, submitted to Phys. Rev.

Incipient failure in sandpile models

Elastoplastic and constitutive equation theories are two approaches based on very different assumptions for creating a continuum theory for the stress distributions in a static sandpile. Both models produce the same surprising prediction that in a two dimensional granular pile constructed at its angle of repose, the outside wedge will be on the verge of failure. We show how these predictions can be tested experimentally.Comment: 5 pages, 1 figur

Two-dimensional cellular automaton model of traffic flow with open boundaries

A two-dimensional cellular automaton model of traffic flow with open boundaries are investigated by computer simulations. The outflow of cars from the system and the average velocity are investigated. The time sequences of the outflow and average velocity have flicker noises in a jamming phase. The low density behavior are discussed with simple jam-free approximation.Comment: 14 pages, Phys. Rev. E in press, PostScript figures available at ftp://hirose.ai.is.saga-u.ac.jp/pub/documents/papers/1996/2DTR/ OpenBoundaries/Figs.tar.g