10,613 research outputs found
Fast Low Fidelity Microsimulation of Vehicle Traffic on Supercomputers
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
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
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
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
Using microsimulation feedback for trip adaptation for realistic traffic in Dallas
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
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
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
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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