2,313 research outputs found
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
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
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
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
Determination of Interaction Potentials in Freeway Traffic from Steady-State Statistics
Many-particle simulations of vehicle interactions have been quite successful
in the qualitative reproduction of observed traffic patterns. However, the
assumed interactions could not be measured, as human interactions are hard to
quantify compared to interactions in physical and chemical systems. We show
that progress can be made by generalizing a method from equilibrium statistical
physics we learned from random matrix theory. It allows one to determine the
interaction potential via distributions of the netto distances s of vehicles.
Assuming power-law interactions, we find that driver behavior can be
approximated by a forwardly directed 1/s potential in congested traffic, while
interactions in free traffic are characterized by an exponent of approximately
4. This is relevant for traffic simulations and the assessment of telematic
systems.Comment: For related work see http://www.helbing.or
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
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
From social data mining to forecasting socio-economic crises
Abstract.: The purpose of this White Paper of the EU Support Action "Visioneer”(see www.visioneer.ethz.ch) is to address the following goals: 1. Develop strategies to quickly increase the objective knowledge about social and economic systems. 2. Describe requirements for efficient large-scale scientific data mining of anonymized social and economic data. 3. Formulate strategies how to collect stylized facts extracted from large data set. 4. Sketch ways how to successfully build up centers for computational social science. 5. Propose plans how to create centers for risk analysis and crisis forecasting. 6. Elaborate ethical standards regarding the storage, processing, evaluation, and publication of social and economic dat
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