2,693 research outputs found
Accelerating Scientific Discovery by Formulating Grand Scientific Challenges
One important question for science and society is how to best promote
scientific progress. Inspired by the great success of Hilbert's famous set of
problems, the FuturICT project tries to stimulate and focus the efforts of many
scientists by formulating Grand Challenges, i.e. a set of fundamental, relevant
and hardly solvable scientific questions.Comment: To appear in EPJ Special Topics. For related work see
http://www.futurict.eu and http://www.soms.ethz.c
Macroscopic Dynamics of Multi-Lane Traffic
We present a macroscopic model of mixed multi-lane freeway traffic that can
be easily calibrated to empirical traffic data, as is shown for Dutch highway
data. The model is derived from a gas-kinetic level of description, including
effects of vehicular space requirements and velocity correlations between
successive vehicles. We also give a derivation of the lane-changing rates. The
resulting dynamic velocity equations contain non-local and anisotropic
interaction terms which allow a robust and efficient numerical simulation of
multi-lane traffic. As demonstrated by various examples, this facilitates the
investigation of synchronization patterns among lanes and effects of on-ramps,
off-ramps, lane closures, or accidents.Comment: For related work see
http://www.theo2.physik.uni-stuttgart.de/helbing.htm
Fundamentals of Traffic Flow
From single vehicle data a number of new empirical results concerning the
density-dependence of the velocity distribution and its moments as well as the
characteristics of their temporal fluctuations have been determined. These are
utilized for the specification of some fundamental relations of traffic flow
and compared with existing traffic theories.Comment: For related work see
http://www.theo2.physik.uni-stuttgart.de/helbing.htm
Derivation, Properties, and Simulation of a Gas-Kinetic-Based, Non-Local Traffic Model
We derive macroscopic traffic equations from specific gas-kinetic equations,
dropping some of the assumptions and approximations made in previous papers.
The resulting partial differential equations for the vehicle density and
average velocity contain a non-local interaction term which is very favorable
for a fast and robust numerical integration, so that several thousand freeway
kilometers can be simulated in real-time. The model parameters can be easily
calibrated by means of empirical data. They are directly related to the
quantities characterizing individual driver-vehicle behavior, and their optimal
values have the expected order of magnitude. Therefore, they allow to
investigate the influences of varying street and weather conditions or freeway
control measures. Simulation results for realistic model parameters are in good
agreement with the diverse non-linear dynamical phenomena observed in freeway
traffic.Comment: For related work see
http://www.theo2.physik.uni-stuttgart.de/helbing.html and
http://www.theo2.physik.uni-stuttgart.de/treiber.htm
A Modification of the Social Force Model by Foresight
The motion of pedestrian crowds (e.g. for simulation of an evacuation
situation) can be modeled as a multi-body system of self driven particles with
repulsive interaction. We use a few simple situations to determine the simplest
allowed functional form of the force function. More complexity may be necessary
to model more complex situations. There are many unknown parameters to such
models, which have to be adjusted correctly. The parameters can be related to
quantities that can be measured independently, like step length and frequency.
The microscopic behavior is, however, only poorly reproduced in many
situations, a person approaching a standing or slow obstacle will e.g. show
oscillations in position, and the trajectories of two persons meeting in a
corridor in opposite direction will be far from realistic and somewhat erratic.
This is inpart due to the assumption of instantaneous reaction on the momentary
situation. Obviously, persons react with a small time lag, while on the other
hand they will anticipate changing situations for at least a short time. Thus
basing the repulsive interaction on a (linear) extrapolation over a short time
(e.g. 1 s) eliminates the oscillations at slowing down and smoothes the
patterns of giving way to others to a more realistic behavior. A second problem
is the additive combination of binary interactions. It is shown that combining
only a few relevant interactions gives better model performance.Comment: 6 pages, 5 figures, Preprint from PED 2008 (Wuppertal
Memory effects in microscopic traffic models and wide scattering in flow-density data
By means of microscopic simulations we show that non-instantaneous adaptation
of the driving behaviour to the traffic situation together with the
conventional measurement method of flow-density data can explain the observed
inverse- shape and the wide scattering of flow-density data in
``synchronized'' congested traffic. We model a memory effect in the response of
drivers to the traffic situation for a wide class of car-following models by
introducing a new dynamical variable describing the adaptation of drivers to
the surrounding traffic situation during the past few minutes (``subjective
level of service'') and couple this internal state to parameters of the
underlying model that are related to the driving style. % For illustration, we
use the intelligent-driver model (IDM) as underlying model, characterize the
level of service solely by the velocity and couple the internal variable to the
IDM parameter ``netto time gap'', modelling an increase of the time gap in
congested traffic (``frustration effect''), that is supported by single-vehicle
data. % We simulate open systems with a bottleneck and obtain flow-density data
by implementing ``virtual detectors''. Both the shape, relative size and
apparent ``stochasticity'' of the region of the scattered data points agree
nearly quantitatively with empirical data. Wide scattering is even observed for
identical vehicles, although the proposed model is a time-continuous,
deterministic, single-lane car-following model with a unique fundamental
diagram.Comment: 8 pages, submitted to Physical Review
Gas-Kinetic-Based Traffic Model Explaining Observed Hysteretic Phase Transition
Recently, hysteretic transitions to `synchronized traffic' with high values
of both density and traffic flow were observed on German freeways [B. S. Kerner
and H. Rehborn, Phys. Rev. Lett. 79, 4030 (1997)]. We propose a macroscopic
traffic model based on a gas-kinetic approach that can explain this phase
transition. The results suggest a general mechanism for the formation of
probably the most common form of congested traffic.Comment: With corrected formula (3). For related work see
http://www.theo2.physik.uni-stuttgart.de/helbing.htm
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
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
Drift- or Fluctuation-Induced Ordering and Self-Organization in Driven Many-Particle Systems
According to empirical observations, some pattern formation phenomena in
driven many-particle systems are more pronounced in the presence of a certain
noise level. We investigate this phenomenon of fluctuation-driven ordering with
a cellular automaton model of interactive motion in space and find an optimal
noise strength, while order breaks down at high(er) fluctuation levels.
Additionally, we discuss the phenomenon of noise- and drift-induced
self-organization in systems that would show disorder in the absence of
fluctuations. In the future, related studies may have applications to the
control of many-particle systems such as the efficient separation of particles.
The rather general formulation of our model in the spirit of game theory may
allow to shed some light on several different kinds of noise-induced ordering
phenomena observed in physical, chemical, biological, and socio-economic
systems (e.g., attractive and repulsive agglomeration, or segregation).Comment: For related work see http://www.helbing.or
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