1,697 research outputs found
Generalized Force Model of Traffic Dynamics
Floating car data of car-following behavior in cities were compared to
existing microsimulation models, after their parameters had been calibrated to
the experimental data. With these parameter values, additional simulations have
been carried out, e.g. of a moving car which approaches a stopped car. It
turned out that, in order to manage such kinds of situations without producing
accidents, improved traffic models are needed. Good results have been obtained
with the proposed generalized force model.Comment: For related work see
http://www.theo2.physik.uni-stuttgart.de/helbing.htm
Structure and Instability of High-Density Equations for Traffic Flow
Similar to the treatment of dense gases, fluid-dynamic equations for the
dynamics of congested vehicular traffic are derived from Enskog-like kinetic
equations. These contain additional terms due to the anisotropic vehicle
interactions. The calculations are carried out up to Navier-Stokes order. A
linear instability analysis indicates an additional kind of instability
compared to previous macroscopic traffic models. The relevance for describing
granular flows is outlined.Comment: For related work see
http://www.theo2.physik.uni-stuttgart.de/helbing.htm
Pedestrian, Crowd, and Evacuation Dynamics
This contribution describes efforts to model the behavior of individual
pedestrians and their interactions in crowds, which generate certain kinds of
self-organized patterns of motion. Moreover, this article focusses on the
dynamics of crowds in panic or evacuation situations, methods to optimize
building designs for egress, and factors potentially causing the breakdown of
orderly motion.Comment: This is a review paper. For related work see http://www.soms.ethz.c
Long-lived states in synchronized traffic flow. Empirical prompt and dynamical trap model
The present paper proposes a novel interpretation of the widely scattered
states (called synchronized traffic) stimulated by Kerner's hypotheses about
the existence of a multitude of metastable states in the fundamental diagram.
Using single vehicle data collected at the German highway A1, temporal velocity
patterns have been analyzed to show a collection of certain fragments with
approximately constant velocities and sharp jumps between them. The particular
velocity values in these fragments vary in a wide range. In contrast, the flow
rate is more or less constant because its fluctuations are mainly due to the
discreteness of traffic flow.
Subsequently, we develop a model for synchronized traffic that can explain
these characteristics. Following previous work (I.A.Lubashevsky, R.Mahnke,
Phys. Rev. E v. 62, p. 6082, 2000) the vehicle flow is specified by car
density, mean velocity, and additional order parameters and that are
due to the many-particle effects of the vehicle interaction. The parameter
describes the multilane correlations in the vehicle motion. Together with the
car density it determines directly the mean velocity. The parameter , in
contrast, controls the evolution of only. The model assumes that
fluctuates randomly around the value corresponding to the car configuration
optimal for lane changing. When it deviates from this value the lane change is
depressed for all cars forming a local cluster. Since exactly the overtaking
manoeuvres of these cars cause the order parameter to vary, the evolution
of the car arrangement becomes frozen for a certain time. In other words, the
evolution equations form certain dynamical traps responsible for the long-time
correlations in the synchronized mode.Comment: 16 pages, 10 figures, RevTeX
Cellular Automata Simulating Experimental Properties of Traffic Flows
A model for 1D traffic flow is developed, which is discrete in space and
time. Like the cellular automaton model by Nagel and Schreckenberg [J. Phys. I
France 2, 2221 (1992)], it is simple, fast, and can describe stop-and-go
traffic. Due to its relation to the optimal velocity model by Bando et al.
[Phys. Rev. E 51, 1035 (1995)], its instability mechanism is of deterministic
nature. The model can be easily calibrated to empirical data and displays the
experimental features of traffic data recently reported by Kerner and Rehborn
[Phys. Rev. E 53, R1297 (1996)].Comment: For related work see
http://www.theo2.physik.uni-stuttgart.de/helbing.html and
http://traffic.comphys.uni-duisburg.de/member/home_schreck.htm
An Agent-Based Approach to Self-Organized Production
The chapter describes the modeling of a material handling system with the
production of individual units in a scheduled order. The units represent the
agents in the model and are transported in the system which is abstracted as a
directed graph. Since the hindrances of units on their path to the destination
can lead to inefficiencies in the production, the blockages of units are to be
reduced. Therefore, the units operate in the system by means of local
interactions in the conveying elements and indirect interactions based on a
measure of possible hindrances. If most of the units behave cooperatively
("socially"), the blockings in the system are reduced.
A simulation based on the model shows the collective behavior of the units in
the system. The transport processes in the simulation can be compared with the
processes in a real plant, which gives conclusions about the consequencies for
the production based on the superordinate planning.Comment: For related work see http://www.soms.ethz.c
Modeling and Simulation of Multi-Lane Traffic Flow
A most important aspect in the field of traffic modeling is the simulation of
bottleneck situations. For their realistic description a macroscopic multi-lane
model for uni-directional freeways including acceleration, deceleration,
velocity fluctuations, overtaking and lane-changing maneuvers is systematically
deduced from a gas-kinetic (Boltzmann-like) approach. The resulting equations
contain corrections with respect to previous models. For efficient computer
simulations, a reduced model delineating the coarse-grained temporal behavior
is derived and applied to bottleneck situations.Comment: For related work see
http://www.theo2.physik.uni-stuttgart.de/helbing.htm
Optimal Self-Organization
We present computational and analytical results indicating that systems of
driven entities with repulsive interactions tend to reach an optimal state
associated with minimal interaction and minimal dissipation. Using concepts
from non-equilibrium thermodynamics and game theoretical ideas, we generalize
this finding to an even wider class of self-organizing systems which have the
ability to reach a state of maximal overall ``success''. This principle is
expected to be relevant for driven systems in physics like sheared granular
media, but it is also applicable to biological, social, and economic systems,
for which only a limited number of quantitative principles are available yet.Comment: This is the detailled revised version of a preprint on
``Self-Organised Optimality'' (cond-mat/9903319). For related work see
http://www.theo2.physik.uni-stuttgart.de/helbing.html and
http://angel.elte.hu/~vicsek
Freezing by Heating in a Driven Mesoscopic System
We investigate a simple model corresponding to particles driven in opposite
directions and interacting via a repulsive potential. The particles move
off-lattice on a periodic strip and are subject to random forces as well. We
show that this model - which can be considered as a continuum version of some
driven diffusive systems - exhibits a paradoxial, new kind of transition called
here ``freezing by heating''. One interesting feature of this transition is
that a crystallized state with a higher total energy is obtained from a fluid
state by increasing the amount of fluctuations.Comment: For related work see
http://www.theo2.physik.uni-stuttgart.de/helbing.html and
http://angel.elte.hu/~vicsek
Two-lane traffic rules for cellular automata: A systematic approach
Microscopic modeling of multi-lane traffic is usually done by applying
heuristic lane changing rules, and often with unsatisfying results. Recently, a
cellular automaton model for two-lane traffic was able to overcome some of
these problems and to produce a correct density inversion at densities somewhat
below the maximum flow density. In this paper, we summarize different
approaches to lane changing and their results, and propose a general scheme,
according to which realistic lane changing rules can be developed. We test this
scheme by applying it to several different lane changing rules, which, in spite
of their differences, generate similar and realistic results. We thus conclude
that, for producing realistic results, the logical structure of the lane
changing rules, as proposed here, is at least as important as the microscopic
details of the rules
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