arXiv subjects

Andreas Schadschneider

Publications and source records attributed to Andreas Schadschneider.

At least 19 recordsLinked to original sources

arXiv2026

An improved car-oriented mean-field theory for stochastic traffic flow models

We propose an improved mean-field analysis of cellular automata models of single-lane vehicular traffic. By combining aspects of the Car-Oriented-Mean-Field (COMF) theory and the 2-site cluster method, which have been previously successfully applied to similar models, we aim to capture both short- and long-range correlations more accurately. In contrast to classical mean-field theories, the improved method is well suited for models with inhomogeneous stationary states and able to capture the essential properties of phase separation, e.g. in models with slow-to-start rules. The improved accuracy and new physical insights are illustrated through an application to the VDR model with $v_{\text{max}}=1$.

cond-mat.stat-mech↗

arXiv2025

Noise-induced transition to stop-and-go waves in single-file traffic rationalized by an analogy with Kapitza's inverted pendulum

Stop-and-go waves in vehicular traffic are commonly explained as a linear collective instability induced by e.g. response delays. We explore an alternative mechanism that more faithfully mirrors oscillation formation in dense single-file traffic. Stochastic noise plays a key role in this model; as it is increased, the base (uniform) flow abruptly switches to stop-and-go dynamics despite its unconditional linear stability. We elucidate the instability mechanism and rationalize it quantitatively by likening the system to a cyclically driven Kapitza pendulum.

physics.soc-ph↗

arXiv2024

Physics of collective transport and traffic phenomena in biology: progress in 20 years

Enormous progress have been made in the last 20 years since the publication of our review \cite{csk05polrev} in this journal on transport and traffic phenomena in biology. In this brief article we present a glimpse of the major advances during this period. First, we present similarities and differences between collective intracellular transport of a single micron-size cargo by multiple molecular motors and that of a cargo particle by a team of ants on the basis of the common principle of load-sharing. Second, we sketch several models all of which are biologically motivated extensions of the Asymmetric Simple Exclusion Process (ASEP); some of these models represent the traffic of molecular machines, like RNA polymerase (RNAP) and ribosome, that catalyze template-directed polymerization of RNA and proteins, respectively, whereas few other models capture the key features of the traffic of ants on trails. More specifically, using the ASEP-based models we demonstrate the effects of traffic of RNAPs and ribosomes on random and `programmed' errors in gene expression as well as on some other subcellular processes. We recall a puzzling empirical result on the single-lane traffic of predatory ants {\it Leptogenys processionalis} as well as recent attempts to account for this puzzle. We also mention some surprising effects of lane-changing rules observed in a ASEP-based model for 3-lane traffic of army ants. Finally, we explain the conceptual similarities between the pheromone-mediated indirect communication, called stigmergy, between ants on a trail and the floor-field-mediated interaction between humans in a pedestrian traffic. For the floor-field model of human pedestrian traffic we present a major theoretical result that is relevant from the perspective of all types of traffic phenomena.

physics.bio-ph↗

arXiv2024

Mirror symmetry breakdown in the Kardar-Parisi-Zhang universality class

The current/height fluctuation statistics of Kardar-Parisi-Zhang (KPZ) universality in 1+1 dimensions are sensitive to the initial state. We find that the averages over the initial states exhibit universal and scale-invariant patterns when conditioning on fluctuations. To establish universality of our findings we demonstrate scale invariance at different times and heights using large-scale Monte-Carlo simulations of the totally asymmetric simple exclusion process (TASEP) which belongs to the KPZ universality class. Here we focus on current/height fluctuations in the steady state regime described by the Baik-Rains distribution. The conditioned probability distribution of an initial state order parameter shows a transition from uni- to bimodal. Bimodality occurs for negative current/height fluctuations that are dominated by super-diffusive shock dynamics. It is caused by two possible point-symmetric shock profiles and the KPZ mirror symmetry breakdown. Similar surprising relations between initial states and fluctuations might exist in other universality classes as well.

cond-mat.stat-mech↗

arXiv2024

Interacting Streams of Cognitive Active Agents in a Three-Way Intersection

The emergent collective motion of active agents - in particular pedestrians - at a three-way intersection is studied by Langevin simulations of cognitive intelligent active Brownian particles (iABPs) with directed visual perception and self-steering avoidance. Depending on the maneuverability $Ω$, the goal fixation $K$, and the vision angle $ψ$, different types of pedestrian motion emerge. At intermediate relative maneuverability $Δ= Ω/K$ and large $ψ$, pedestrians have noisy trajectories due to multiple scattering events as they encounter other pedestrians in their field of view. For $ψ= π$ and large relative maneuverability $Δ$, an effectively jammed state is found, which belongs to the percolation universality class. For small $ψ$, agents exhibit localised clustering and flocking, while for intermediate $ψ$ self-organized rotational flows can emerge. The analysis of mean squared displacement and velocity auto-correlation of the agents reveals that the motion is well described by fractional Brownian Motion with positively correlated noise. Finally, despite the rich variety of collective behaviour, the fundamental flow diagram for the three-way-crossing setup shows a universal curve for the different vision angles. Our research provides valuable insights into the importance of vision angle and self-steering avoidance on pedestrian dynamics in semi-dense crowds.

cond-mat.stat-mech↗

arXiv2024

Dimensionless Numbers Reveal Distinct Regimes in the Structure and Dynamics of Pedestrian Crowds

In fluid mechanics, dimensionless numbers like the Reynolds number help classify flows. We argue that such a classification is also relevant for crowd flows by putting forward the dimensionless Intrusion and Avoidance numbers.Using an extensive dataset, we show that these delineate regimes that are characterized by distinct structural signatures, best probed in terms of distances at low Avoidance number and times-to-collision at low Intrusion number.These findings prompt a perturbative expansion of the agent-based dynamics; the generic models thus obtained perform well in (and only in) the regime in which they were derived.

cond-mat.stat-mech↗

arXiv2023

Physical models of traffic safety at crossings

Traffic safety at intersections is studied quantitatively using methods from Statistical Mechanics on the basis of simple microscopic traffic flow models. In order to determine a relationship between traffic flow and the number of crashes, the modelling focus is on the building block of any road network, namely the crossing of two streams. In this paper, it is shown that the number of crossing conflicts is proportional to the product of the two traffic flows from which a simple model is developed. This model substantiates known empirical findings. Since real crash data are obtained by an involved process from such building blocks, there is a difference between the theoretical and empirical results. This process is modelled here as well and narrows the gap between theory and observation.

cond-mat.stat-mech↗

arXiv2023

Structure of road networks and the shape of the macroscopic fundamental diagram

The macroscopic fundamental diagram (MFD) is a large scale description of the traffic in a urban area and relates the average car flow to the average car density. This MFD has been observed empirically in several cities but how its properties are related to the structure of the road network has remained unclear so far. The MFD displays in general a maximum flow $q^*$ for an optimal car density $k^*$ which are crucial quantities for practical applications. Here, using numerical modeling and dimensional arguments, we propose scaling laws for these quantities $q^*$ and $k^*$ in terms of the road density, the intersection density, the average car size and the maximum velocity. This framework is able to explain the scaling observed empirically for several cities in the world, such as the scaling of $k^*$ with the road density, the relation between $q^*$ and $k^*$ and the impact of buses on the overall capacity $q^*$. This work opens the way to a better understanding of the traffic on a road network at a large urban scale.

physics.soc-ph↗

arXiv2023

Single-file pedestrian dynamics: a review of agent-following models

Single-file dynamics has been studied intensively, both experimentally and theoretically. It shows interesting collective effects, such as stop-and-go waves, which are validation cornerstones for any agent-based modeling approach of traffic systems. Many models have been proposed, e.g. in the form of car-following models for vehicular traffic. These approaches can be adapted for pedestrian streams. In this study, we delve deeper into these models, with particular attention on their interconnections. We do this by scrutinizing the influence of different parameters, including relaxation times, anticipation time, and reaction time. Specifically, we analyze the inherent fundamental problems with force-based models, a classical approach in pedestrian dynamics. Furthermore, we categorize car-following models into stimulus-response and optimal velocity models, highlighting their historical and conceptual differences. These classes can further be subdivided considering the conceptual definitions of the models, e.g. first-order vs. second-order models, or stochastic vs. deterministic models with and without noise. Our analysis shows how car-following models originally developed for vehicular traffic can provide new insights into pedestrian behavior. The focus on single-file motion, which is similar to single-lane vehicular traffic, allows for a detailed examination of the relevant interactions between pedestrians.

physics.soc-ph↗

arXiv2023

Social distancing and the future of pedestrian dynamics

Many countries have introduced social distancing rules during the COVID-19 pandemic in order to reduce spreading of the virus in public spaces. This has inspired research on pedestrian dynamics in more ways than just one. Many studies have been performed, not only to determine the effectiveness of such measures, but also in order to understand its effects on crowd dynamics in general. In this Perspective article, we reflect on the insights derived from these investigations and their relevance for future advancements in the field of pedestrian dynamics. This includes impacts on safety regulations and the potential for new theoretical and experimental approaches which may hold relevance even beyond applied restrictions.

physics.soc-ph↗

arXiv2022

Heterogeneity-induced lane and band formation in self-driven particle systems

The collective motion of interacting self-driven particles describes many types of coordinated dynamics and self-organisation. Prominent examples are alignment or lane formation which can be observed alongside other ordered structures and nonuniform patterns. In this article, we investigate the effects of different types of heterogeneity in a two-species self-driven particle system. We show that heterogeneity can generically initiate segregation in the motion and identify two heterogeneity mechanisms. Longitudinal lanes parallel to the direction of motion emerge when the heterogeneity statically lies in the agent characteristics (quenched disorder). While transverse bands orthogonal to the motion direction arise from dynamic heterogeneity in the interactions (annealed disorder). In both cases, non-linear transitions occur as the heterogeneity increases, from disorder to ordered states with lane or band patterns. These generic features are observed for a first and a second order motion model and different characteristic parameters related to particle speed and size. Simulation results show that the collective dynamics occur in relatively short time intervals, persist stationary, and are partly robust against random perturbations.

nlin.AO↗

arXiv2020

The Effect of Modern Traffic Information on Braess' Paradox

Braess' paradox has been shown to appear rather generically in many systems of transport on networks. It is especially relevant for vehicular traffic where it shows that in certain situations building a new road in an urban or highway network can lead to increased average travel times for all users. Here we address the question whether this changes if the drivers (agents) have access to traffic information as available for modern traffic networks, i.e. through navigation apps and or personal experiences in the past. We study the effect of traffic information in the classical Braess network, but using a microscopic model for the traffic dynamics, to find out if the paradox can really be observed in such a scenario or if it only exists in some theoretically available user optima that are never realized by drivers that base their route choice decisions intelligently upon realistic traffic information. We address this question for different splits of the two information types.

physics.soc-ph↗

arXiv2020

Braess' paradox in the age of traffic information

The Braess paradox describes the counterintuitive situation that the addition of new roads to road networks can lead to higher travel times for all network users. Recently we could show that user optima leading to the paradox exist in networks of microscopic transport models. We derived phase diagrams for two kinds of route choice strategies that were externally tuned and applied by all network users. Here we address the question whether these user optima are still realized if intelligent route choice decisions are made based upon two kinds of traffic information. We find that the paradox still can occur if the drivers 1) make informed decisions based on their own past experiences or 2) use traffic information similar to that provided by modern navigation apps. This indicates that modern traffic information systems are not able to resolve Braess' paradox.

physics.soc-ph↗

arXiv2019

Stop-and-go waves induced by correlated noise in pedestrian models without inertia

Stop-and-go waves are commonly observed in traffic and pedestrian flows. In most traffic models they occur through a phase transition after fine tuning of parameters when the model has unstable homogeneous solutions. Inertia effects are believed to play an important role in this mechanism. Here, we present a novel explanation for stop-and-go waves based on stochastic effects in the absence of inertia. The introduction of specific coloured noises in a stable microscopic first order model allows to describe realistic stop-and-go behaviour without requiring instabilities or phase transitions. We apply the approach to pedestrian single-file motion and compare simulation results to real pedestrian trajectories. Plausible values for the model parameters are discussed.

physics.soc-ph↗

arXiv2019

The trouble with 2nd order models or how to generate stop-and-go traffic in a 1st order model

Classical second order models of pedestrian dynamics, like the social-force model, suffer from various unrealistic behaviors in the dynamics, e.g. backward motion, oscillations and overlapping of pedestrians. These effects are not related to the discretization of the equations of motion, but intrinsic to the dynamics. They are the consequence of strong inertia effects that usually appear in second order models. We show that the experimentally observed stop-and-go behavior, which is an important test for any pedestrian model, can be reproduced with a stochastic first order model that does not suffer from the dynamical artefacts resulting from strong inertia. The model provides a new mechanism for stop-and-go behavior which is based on correlated noise.

physics.soc-ph↗

arXiv2019

Kardar-Parisi-Zhang Universality of the Nagel-Schreckenberg Model

Dynamical universality classes are distinguished by their dynamical exponent $z$ and unique scaling functions encoding space-time asymmetry for, e.g. slow-relaxation modes or the distribution of time-integrated currents. So far the universality class of the Nagel-Schreckenberg (NaSch) model, which is a paradigmatic model for traffic flow on highways, was not known except for the special case $v_{\text{max}}=1$. Here the model corresponds to the TASEP (totally asymmetric simple exclusion process) that is known to belong to the superdiffusive Kardar-Parisi-Zhang (KPZ) class with $z=3/2$. In this paper, we show that the NaSch model also belongs to the KPZ class \cite{KPZ} for general maximum velocities $v_{\text{max}}>1$. Using nonlinear fluctuating hydrodynamics theory we calculate the nonuniversal coefficients, fixing the exact asymptotic solutions for the dynamical structure function and the distribution of time-integrated currents. Performing large-scale Monte-Carlo simulations we show that the simulation results match the exact asymptotic KPZ solutions without any fitting parameter left. Additionally, we find that nonuniversal early-time effects or the choice of initial conditions might have a strong impact on the numerical determination of the dynamical exponent and therefore lead to inconclusive results. We also show that the universality class is not changed by extending the model to a two-lane NaSch model with dynamical lane changing rules.

cond-mat.stat-mech↗

arXiv2018

Braess paradox in a network with stochastic dynamics and fixed strategies

The Braess paradox can be observed in road networks used by selfish users. It describes the counterintuitive situation in which adding a new, per se faster, origin-destination connection to a road network results in increased travel times for all network users. We study the network as originally proposed by Braess but introduce microscopic particle dynamics based on the totally asymmetric exclusion processes. In contrast to our previous work [10.1103/PhysRevE.94.062312], where routes were chosen randomly according to turning rates, here we study the case of drivers with fixed route choices. We find that travel time reduction due to the new road only happens at really low densities and Braess' paradox dominates the largest part of the phase diagram. Furthermore, the domain wall phase observed in [10.1103/PhysRevE.94.062312] vanishes. In the present model gridlock states are observed in a large part of phase space. We conclude that the construcion of a new road can often be very critical and should be considered carefully.

physics.soc-ph↗

arXiv2018

Noise-induced Stop-and-Go Dynamics

Stop-and-go waves are commonly observed in traffic and pedestrian flows. In traffic theory they are described by phase transitions of metastable models. The self-organization phenomenon occurs due to inertia mechanisms but requires fine tuning of the parameters. Here, a novel explanation for stop-and-go waves based on stochastic effects is presented for pedestrian dynamics. We show that the introduction of specific coloured noises in a stable microscopic model allows to describe realistic pedestrian stop-and-go behaviour without requirement of metastability and phase transition. We compare simulation results of the stochastic model to real pedestrian trajectories and discuss plausible values for the model's parameters.

physics.soc-ph↗