10,616 research outputs found

    Fast Low Fidelity Microsimulation of Vehicle Traffic on Supercomputers

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    A set of very simple rules for driving behavior used to simulate roadway traffic gives realistic results. Because of its simplicity, it is easy to implement the model on supercomputers (vectorizing and parallel), where we have achieved real time limits of more than 4~million~kilometers (or more than 53~million vehicle sec/sec). The model can be used for applications where both high simulation speed and individual vehicle resolution are needed. We use the model for extended statistical analysis to gain insight into traffic phenomena near capacity, and we discuss that this model is a good candidate for network routing applications. (Submitted to Transportation Research Board Meeting, Jan. 1994, Washington D.C.)Comment: 11 pages, latex, figs. available upon request, Cologne-WP 93.14

    Life-Times of Simulated Traffic Jams

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    We study a model for freeway traffic which includes strong noise taking into account the fluctuations of individual driving behavior. The model shows emergent traffic jams with a self-similar appearance near the throughput maximum of the traffic. The lifetime distribution of these jams shows a short scaling regime, which gets considerably longer if one reduces the fluctuations for driving at maximum speed but leaves the fluctuations for slowing down or accelerating unchanged. The outflow from a traffic jam self-organizes into this state of maximum throughput.Comment: latex, figs. available upon request, WP-Cologne 93.14

    Detection of non-radial g-mode pulsations in the newly discovered PG1159 star HE 1429-1209

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    We performed time-series photometry of the PG1159-type star HE 1429-1209, which was recently discovered in the ESO SPY survey. We show that the star is a low-amplitude (about 0.05 mag) non-radial g-mode pulsator with a period of 919s. HE 1429-1209 is among the hottest known post-AGB stars (Teff=160000 K) and, together with the known pulsator RX J2117.1+3412, it defines empirically the blue edge of the GW Vir instability strip in the HRD at high luminosities.Comment: 4 pages, 4 figures, to be published in A&

    Traffic at the Edge of Chaos

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    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

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    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

    Using microsimulation feedback for trip adaptation for realistic traffic in Dallas

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    This paper presents a day-to-day re-routing relaxation approach for traffic simulations. Starting from an initial planset for the routes, the route-based microsimulation is executed. The result of the microsimulation is fed into a re-router, which re-routes a certain percentage of all trips. This approach makes the traffic patterns in the microsimulation much more reasonable. Further, it is shown that the method described in this paper can lead to strong oscillations in the solutions.Comment: Accepted by International Journal of Modern Physics C. Complete postscript version including figures in http://www-transims.tsasa.lanl.gov/research_team/papers

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

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    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

    Strain Hardening in Polymer Glasses: Limitations of Network Models

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    Simulations are used to examine the microscopic origins of strain hardening in polymer glasses. While traditional entropic network models can be fit to the total stress, their underlying assumptions are inconsistent with simulation results. There is a substantial energetic contribution to the stress that rises rapidly as segments between entanglements are pulled taut. The thermal component of stress is less sensitive to entanglements, mostly irreversible, and directly related to the rate of local plastic arrangements. Entangled and unentangled chains show the same strain hardening when plotted against the microscopic chain orientation rather than the macroscopic strain.Comment: 4 pages, 3 figure

    Do Wealth Fluctuations Generate Time-varying Risk Aversion? Micro-Evidence on Individuals' Asset Allocation

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    We use data from the PSID to investigate how households' portfolio allocations change in response to wealth fluctuations. Persistent habits, consumption commitments, and subsistence levels can generate time-varying risk aversion with the consequence that when the level of liquid wealth changes, the proportion a household invests in risky assets should also change in the same direction. In contrast, our analysis shows that the share of liquid assets that households invest in risky assets is not affected by wealth changes. Instead, one of the major drivers of households' portfolio allocation seems to be inertia: households rebalance only very slowly following inflows and outflows or capital gains and losses.
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