607 research outputs found
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
Theoretical vs. empirical classification and prediction of congested traffic states
Starting from the instability diagram of a traffic flow model, we derive conditions for the occurrence of congested traffic states, their appearance, their spreading in space and time, and the related increase in travel times. We discuss the terminology of traffic phases and give empirical evidence for the existence of a phase diagram of traffic states. In contrast to previously presented phase diagrams, it is shown that "widening synchronized patterns” are possible, if the maximum flow is located inside of a metastable density regime. Moreover, for various kinds of traffic models with different instability diagrams it is discussed, how the related phase diagrams are expected to approximately look like. Apart from this, it is pointed out that combinations of on- and off-ramps create different patterns than a single, isolated on-ram
Equilibrium distributions in thermodynamical traffic gas
We derive the exact formula for thermal-equilibrium spacing distribution of
one-dimensional particle gas with repulsive potential V(r)=r^(-a) (a>0)
depending on the distance r between the neighboring particles. The calculated
distribution (for a=1) is successfully compared with the highway-traffic
clearance distributions, which provides a detailed view of changes in
microscopical structure of traffic sample depending on traffic density. In
addition to that, the observed correspondence is a strong support of studies
applying the equilibrium statistical physics to traffic modelling.Comment: 5 pages, 6 figures, changed content, added reference
Quantum dynamics of the avian compass
The ability of migratory birds to orient relative to the Earth's magnetic
field is believed to involve a coherent superposition of two spin states of a
radical electron pair. However, the mechanism by which this coherence can be
maintained in the face of strong interactions with the cellular environment has
remained unclear. This Letter addresses the problem of decoherence between two
electron spins due to hyperfine interaction with a bath of spin 1/2 nuclei.
Dynamics of the radical pair density matrix are derived and shown to yield a
simple mechanism for sensing magnetic field orientation. Rates of dephasing and
decoherence are calculated ab initio and found to yield millisecond coherence
times, consistent with behavioral experiments
Calibrating Car-Following Models using Trajectory Data: Methodological Study
The car-following behavior of individual drivers in real city traffic is
studied on the basis of (publicly available) trajectory datasets recorded by a
vehicle equipped with an radar sensor. By means of a nonlinear optimization
procedure based on a genetic algorithm, we calibrate the Intelligent Driver
Model and the Velocity Difference Model by minimizing the deviations between
the observed driving dynamics and the simulated trajectory when following the
same leading vehicle. The reliability and robustness of the nonlinear fits are
assessed by applying different optimization criteria, i.e., different measures
for the deviations between two trajectories. The obtained errors are in the
range between~11% and~29% which is consistent with typical error ranges
obtained in previous studies. In addition, we found that the calibrated
parameter values of the Velocity Difference Model strongly depend on the
optimization criterion, while the Intelligent Driver Model is more robust in
this respect. By applying an explicit delay to the model input, we investigated
the influence of a reaction time. Remarkably, we found a negligible influence
of the reaction time indicating that drivers compensate for their reaction time
by anticipation. Furthermore, the parameter sets calibrated to a certain
trajectory are applied to the other trajectories allowing for model validation.
The results indicate that ``intra-driver variability'' rather than
``inter-driver variability'' accounts for a large part of the calibration
errors. The results are used to suggest some criteria towards a benchmarking of
car-following models
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
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
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
Life events and hemodynamic stress reactivity in the middle-aged and elderly
Recent versions of the reactivity hypothesis, which consider it to be the product of stress exposure and exaggerated haemodynamic reactions to stress that confers cardiovascular disease risk, assume that reactivity is independent of the experience of stressful life events. This assumption was tested in two substantial cohorts, one middle-aged and one elderly. Participants had to indicate from a list of major stressful life events up to six they had experienced in the previous two years. They were also asked to rate how disruptive and stressful they were, at the time of occurrence and now. Blood pressure and pulse rate were measured at rest and in response to acute mental stress. Those who rated the events as highly disruptive at the time of exposure and currently exhibited blunted systolic blood pressure reactions to acute stress. The present results suggest that acute stress reactivity may not be independent of stressful life events experience
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