Estimating Acceleration and Lane-Changing Dynamics Based on NGSIM Trajectory Data

The NGSIM trajectory data sets provide longitudinal and lateral positional information for all vehicles in certain spatiotemporal regions. Velocity and acceleration information cannot be extracted directly since the noise in the NGSIM positional information is greatly increased by the necessary numerical differentiations. We propose a smoothing algorithm for positions, velocities and accelerations that can also be applied near the boundaries. The smoothing time interval is estimated based on velocity time series and the variance of the processed acceleration time series. The velocity information obtained in this way is then applied to calculate the density function of the two-dimensional distribution of velocity and inverse distance, and the density of the distribution corresponding to the ``microscopic'' fundamental diagram. Furthermore, it is used to calculate the distributions of time gaps and times-to-collision, conditioned to several ranges of velocities and velocity differences. By simulating virtual stationary detectors we show that the probability for critical values of the times-to-collision is greatly underestimated when estimated from single-vehicle data of stationary detectors. Finally, we investigate the lane-changing process and formulate a quantitative criterion for the duration of lane changes that is based on the trajectory density in normalized coordinates. Remarkably, there is a very noisy but significant velocity advantage in favor of the targeted lane that decreases immediately before the change due to anticipatory accelerations

Probing complex RNA structures by mechanical force

RNA secondary structures of increasing complexity are probed combining single molecule stretching experiments and stochastic unfolding/refolding simulations. We find that force-induced unfolding pathways cannot usually be interpretated by solely invoking successive openings of native helices. Indeed, typical force-extension responses of complex RNA molecules are largely shaped by stretching-induced, long-lived intermediates including non-native helices. This is first shown for a set of generic structural motifs found in larger RNA structures, and then for Escherichia coli's 1540-base long 16S ribosomal RNA, which exhibits a surprisingly well-structured and reproducible unfolding pathway under mechanical stretching. Using out-of-equilibrium stochastic simulations, we demonstrate that these experimental results reflect the slow relaxation of RNA structural rearrangements. Hence, micromanipulations of single RNA molecules probe both their native structures and long-lived intermediates, so-called "kinetic traps", thereby capturing -at the single molecular level- the hallmark of RNA folding/unfolding dynamics.Comment: 9 pages, 9 figure

Interpreting the Wide Scattering of Synchronized Traffic Data by Time Gap Statistics

Based on the statistical evaluation of experimental single-vehicle data, we propose a quantitative interpretation of the erratic scattering of flow-density data in synchronized traffic flows. A correlation analysis suggests that the dynamical flow-density data are well compatible with the so-called jam line characterizing fully developed traffic jams, if one takes into account the variation of their propagation speed due to the large variation of the netto time gaps (the inhomogeneity of traffic flow). The form of the time gap distribution depends not only on the density, but also on the measurement cross section: The most probable netto time gap in congested traffic flow upstream of a bottleneck is significantly increased compared to uncongested freeway sections. Moreover, we identify different power-law scaling laws for the relative variance of netto time gaps as a function of the sampling size. While the exponent is -1 in free traffic corresponding to statistically independent time gaps, the exponent is about -2/3 in congested traffic flow because of correlations between queued vehicles.Comment: For related publications see http://www.helbing.or

Prediction and statistics of pseudoknots in RNA structures using exactly clustered stochastic simulations

Ab initio RNA secondary structure predictions have long dismissed helices interior to loops, so-called pseudoknots, despite their structural importance. Here, we report that many pseudoknots can be predicted through long time scales RNA folding simulations, which follow the stochastic closing and opening of individual RNA helices. The numerical efficacy of these stochastic simulations relies on an O(n^2) clustering algorithm which computes time averages over a continously updated set of n reference structures. Applying this exact stochastic clustering approach, we typically obtain a 5- to 100-fold simulation speed-up for RNA sequences up to 400 bases, while the effective acceleration can be as high as 100,000-fold for short multistable molecules (<150 bases). We performed extensive folding statistics on random and natural RNA sequences, and found that pseudoknots are unevenly distributed amongst RNAstructures and account for up to 30% of base pairs in G+C rich RNA sequences (Online RNA folding kinetics server including pseudoknots : http://kinefold.u-strasbg.fr/ ).Comment: 6 pages, 5 figure

Temporal Modulation of the Control Parameter in Electroconvection in the Nematic Liquid Crystal I52

I report on the effects of a periodic modulation of the control parameter on electroconvection in the nematic liquid crystal I52. Without modulation, the primary bifurcation from the uniform state is a direct transition to a state of spatiotemporal chaos. This state is the result of the interaction of four, degenerate traveling modes: right and left zig and zag rolls. Periodic modulations of the driving voltage at approximately twice the traveling frequency are used. For a large enough modulation amplitude, standing waves that consist of only zig or zag rolls are stabilized. The standing waves exhibit regular behavior in space and time. Therefore, modulation of the control parameter represents a method of eliminating spatiotemporal chaos. As the modulation frequency is varied away from twice the traveling frequency, standing waves that are a superposition of zig and zag rolls, i.e. standing rectangles, are observed. These results are compared with existing predictions based on coupled complex Ginzburg-Landau equations

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

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

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 $h$ and $a$ that are due to the many-particle effects of the vehicle interaction. The parameter $h$ describes the multilane correlations in the vehicle motion. Together with the car density it determines directly the mean velocity. The parameter $a$, in contrast, controls the evolution of $h$ only. The model assumes that $a$ 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 $a$ 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