58 research outputs found
A power law for the duration of high-flow states and its interpretation from a heterogeneous traffic flow perspective
We study the duration of "high-flow states” in freeway traffic, defined as the time periods for which traffic flows exceed a given flow threshold. Our empirical data are surprisingly well represented by a power law. Moreover, the power law exponent for a two-lane freeway seems to be independent of the chosen flow threshold. In order to interpret this discovery, we investigate a simple theoretical model of heterogeneous traffic with overtaking maneuvers, which is able to reproduce both, the empirical power law and its exponen
Analysis of the runoff response of an Alpine catchment at different scales
International audienceTo understand how hydrological processes are related across different spatial scales, 201 rainfall runoff events were examined in three nested catchments of the upper river Saalach in the Austrian Alps. The Saalach basin is a nested catchment covering different spatial scales, from the micro-scale (Limberg, 0.07 km2), to the small-catchment scale (Rammern, 15.5 km2), and the meso-scale (Viehhofen, 150 km2). At these three scales two different event types could clearly be identified, depending on rainfall characteristics and initial baseflow level: (1) a unimodal event type with a quick rising and falling hydrograph, responding to short duration rainfall, and (2) a bimodal event type with a double peak hydrograph at the micro-scale and substantially increased flow values at the larger basins Rammern and Viehhofen, responding to long duration rainfall events. In all cases where a bimodal event was identified at the microscale, the hydrographs at the larger scales exhibited significantly attenuated recession behavior, quantified by recession constants. At all scales, the bimodal events are associated with considerably higher runoff volumes than the unimodal events. From the investigations at the headwater Limberg we came to the conclusion that the higher amount of runoff of bimodal events is due to the mobilization of subsurface flow processes. The analysis shows that the occurrence of the two event types is consistent over three orders of magnitude in area. This link between the scales means that the runoff behavior of the headwater may be used as an indicator of the runoff behavior of much larger areas
Analysis of the runoff response of an alpine catchment at different scales
International audienceTo understand how hydrological processes are related across different spatial scales, 201 rainfall runoff events were examined in three nested catchments of the upper river Saalach in the Austrian Alps. The Saalach basin is a nested catchment covering different spatial scales, from the micro-scale (Limberg, 0.07 km²), to the small-catchment scale (Rammern, 15.5 km²), and the meso-scale (Viehhofen, 150 km²). At these three scales two different event types could clearly be identified, depending on rainfall characteristics and initial baseflow level: (1) a unimodal event type with a quick rising and falling hydrograph, responding to short duration rainfall, and (2) a bimodal event type with a double peak hydrograph at the micro-scale and substantially increased flow values at the larger basins Rammern and Viehhofen, responding to long duration rainfall events. In all cases where a bimodal event was identified at the microscale, the hydrographs at the larger scales exhibited significantly attenuated recession behavior, quantified by recession constants. At all scales, the bimodal events are associated with considerably higher runoff volumes than the unimodal events. From the investigations at the headwater Limberg we came to the conclusion that the higher amount of runoff of bimodal events is due to the mobilization of subsurface flow processes. The analysis shows that the occurrence of the two event types is consistent over three orders of magnitude in area. This link between the scales means that the runoff behavior of the headwater may be used as an indicator of the runoff behavior of much larger areas
An empirical test for cellular automaton models of traffic flow
Based on a detailed microscopic test scenario motivated by recent empirical
studies of single-vehicle data, several cellular automaton models for traffic
flow are compared. We find three levels of agreement with the empirical data:
1) models that do not reproduce even qualitatively the most important empirical
observations,
2) models that are on a macroscopic level in reasonable agreement with the
empirics, and 3) models that reproduce the empirical data on a microscopic
level as well.
Our results are not only relevant for applications, but also shed new light
on the relevant interactions in traffic flow.Comment: 28 pages, 36 figures, accepted for publication in PR
Statistical Mechanics of Canonical-Dissipative Systems and Applications to Swarm Dynamics
We develop the theory of canonical-dissipative systems, based on the
assumption that both the conservative and the dissipative elements of the
dynamics are determined by invariants of motion. In this case, known solutions
for conservative systems can be used for an extension of the dynamics, which
also includes elements such as the take-up/dissipation of energy. This way, a
rather complex dynamics can be mapped to an analytically tractable model, while
still covering important features of non-equilibrium systems. In our paper,
this approach is used to derive a rather general swarm model that considers (a)
the energetic conditions of swarming, i.e. for active motion, (b) interactions
between the particles based on global couplings. We derive analytical
expressions for the non-equilibrium velocity distribution and the mean squared
displacement of the swarm. Further, we investigate the influence of different
global couplings on the overall behavior of the swarm by means of
particle-based computer simulations and compare them with the analytical
estimations.Comment: 14 pages incl. 13 figures. v2: misprints in Eq. (40) corrected, ref.
updated. For related work see also:
http://summa.physik.hu-berlin.de/~frank/active.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
Criterion for traffic phases in single vehicle data and empirical test of a microscopic three-phase traffic theory
A microscopic criterion for distinguishing synchronized flow and wide moving
jam phases in single vehicle data measured at a single freeway location is
presented. Empirical local congested traffic states in single vehicle data
measured on different days are classified into synchronized flow states and
states consisting of synchronized flow and wide moving jam(s). Then empirical
microscopic characteristics for these different local congested traffic states
are studied. Using these characteristics and empirical spatiotemporal
macroscopic traffic phenomena, an empirical test of a microscopic three-phase
traffic flow theory is performed. Simulations show that the microscopic
criterion and macroscopic spatiotemporal objective criteria lead to the same
identification of the synchronized flow and wide moving jam phases in congested
traffic. It is found that microscopic three-phase traffic models can explain
both microscopic and macroscopic empirical congested pattern features. It is
obtained that microscopic distributions for vehicle speed difference as well as
fundamental diagrams and speed correlation functions can depend on the spatial
co-ordinate considerably. It turns out that microscopic optimal velocity (OV)
functions and time headway distributions are not necessarily qualitatively
different, even if local congested traffic states are qualitatively different.
The reason for this is that important spatiotemporal features of congested
traffic patterns are it lost in these as well as in many other macroscopic and
microscopic traffic characteristics, which are widely used as the empirical
basis for a test of traffic flow models, specifically, cellular automata
traffic flow models.Comment: 27 pages, 16 figure
Congested Traffic States in Empirical Observations and Microscopic Simulations
We present data from several German freeways showing different kinds of
congested traffic forming near road inhomogeneities, specifically lane
closings, intersections, or uphill gradients. The states are localized or
extended, homogeneous or oscillating. Combined states are observed as well,
like the coexistence of moving localized clusters and clusters pinned at road
inhomogeneities, or regions of oscillating congested traffic upstream of nearly
homogeneous congested traffic. The experimental findings are consistent with a
recently proposed theoretical phase diagram for traffic near on-ramps [D.
Helbing, A. Hennecke, and M. Treiber, Phys. Rev. Lett. {\bf 82}, 4360 (1999)].
We simulate these situations with a novel continuous microscopic single-lane
model, the ``intelligent driver model'' (IDM), using the empirical boundary
conditions. All observations, including the coexistence of states, are
qualitatively reproduced by describing inhomogeneities with local variations of
one model parameter.
We show that the results of the microscopic model can be understood by
formulating the theoretical phase diagram for bottlenecks in a more general
way. In particular, a local drop of the road capacity induced by parameter
variations has practically the same effect as an on-ramp.Comment: Now published in Phys. Rev. E. Minor changes suggested by a referee
are incorporated; full bibliographic info added. For related work see
http://www.mtreiber.de/ and http://www.helbing.org
Active Brownian Motion Models and Applications to Ratchets
We give an overview over recent studies on the model of Active Brownian
Motion (ABM) coupled to reservoirs providing free energy which may be converted
into kinetic energy of motion. First, we present an introduction to a general
concept of active Brownian particles which are capable to take up energy from
the source and transform part of it in order to perform various activities. In
the second part of our presentation we consider applications of ABM to ratchet
systems with different forms of differentiable potentials. Both analytical and
numerical evaluations are discussed for three cases of sinusoidal,
staircase-like and Mateos ratchet potentials, also with the additional loads
modeled by tilted potential structure. In addition, stochastic character of the
kinetics is investigated by considering perturbation by Gaussian white noise
which is shown to be responsible for driving the directionality of the
asymptotic flux in the ratchet. This \textit{stochastically driven
directionality} effect is visualized as a strong nonmonotonic dependence of the
statistics of the right versus left trajectories of motion leading to a net
current of particles. Possible applications of the ratchet systems to molecular
motors are also briefly discussedComment: 12 pages, 17 figure
Episignature analysis of moderate effects and mosaics
DNA methylation classifiers (episignatures) help to determine the pathogenicity of variants of uncertain significance (VUS). However, their sensitivity is limited due to their training on unambiguous cases with strong-effect variants so that the classification of variants with reduced effect size or in mosaic state may fail. Moreover, episignature evaluation of mosaics as a function of their degree of mosaicism has not been developed so far. We improved episignatures with respect to three categories. Applying (i) minimum-redundancy-maximum-relevance feature selection we reduced their length by up to one order of magnitude without loss of accuracy. Performing (ii) repeated re-training of a support vector machine classifier by step-wise inclusion of cases in the training set that reached probability scores larger than 0.5, we increased the sensitivity of the episignature-classifiers by 30%. In the newly diagnosed patients we confirmed the association between DNA methylation aberration and age at onset of KMT2B-deficient dystonia. Moreover, we found evidence for allelic series, including KMT2B-variants with moderate effects and comparatively mild phenotypes such as late-onset focal dystonia. Retrained classifiers also can detect mosaics that previously remained below the 0.5-threshold, as we showed for KMT2D-associated Kabuki syndrome. Conversely, episignature-classifiers are able to revoke erroneous exome calls of mosaicism, as we demonstrated by (iii) comparing presumed mosaic cases with a distribution of artificial in silico-mosaics that represented all the possible variation in degree of mosaicism, variant read sampling and methylation analysis
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