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Dirk Helbing

Publications and source records attributed to Dirk Helbing.

At least 145 records · Page 8Linked to original sources
arXiv2004

Empirical Features of Congested Traffic States and Their Implications for Traffic Modeling

We investigate characteristic properties of the congested traffic states on a 30 km long stretch of the German freeway A5 north of Frankfurt/Main. Among the approximately 245 breakdowns of traffic flow in 165 days, we have identified five different kinds of spatio-temporal congestion patterns and their combinations. Based on an "adaptive smoothing method" for the visualization of detector data, we also discuss particular features of breakdowns such as the "boomerang effect" which is a sign of linearly unstable traffic flow. Controversial issues such as "synchronized flow" or stop-and-go waves are addressed as well. Finally, our empirical results are compared with different theoretical concepts and interpretations of congestion patterns, in particular first- and second-order macroscopic traffic models.

cond-mat.stat-mech↗
arXiv2004

Physics, Stability and Dynamics of Supply Networks

We show how to treat supply networks as physical transport problems governed by balance equations and equations for the adaptation of production speeds. Although the non-linear behaviour is different, the linearized set of coupled differential equations is formally related to those of mechanical or electrical oscillator networks. Supply networks possess interesting new features due to their complex topology and directed links. We derive analytical conditions for absolute and convective instabilities. The empirically observed "bull-whip effect" in supply chains is explained as a form of convective instability based on resonance effects. Moreover, it is generalized to arbitrary supply networks. Their related eigenvalues are usually complex, depending on the network structure (even without loops). Therefore, their generic behavior is characterized by oscillations. We also show that regular distribution networks possess two negative eigenvalues only, but perturbations generate a spectrum of complex eigenvalues.

cond-mat.stat-mech↗
arXiv2004

Stability Analysis and Stabilization Strategies for Linear Supply Chains

Due to delays in the adaptation of production or delivery rates, supply chains can be dynamically unstable with respect to perturbations in the consumption rate, which is known as "bull-whip effect". Here, we study several conceivable production strategies to stabilize supply chains, which is expressed by different specifications of the management function controlling the production speed in dependence of the stock levels. In particular, we will investigate, whether the reaction to stock levels of other producers or suppliers has a stabilizing effect. We will also demonstrate that the anticipation of future stock levels can stabilize the supply system, given the forecast horizon is long enough. To show this, we derive linear stability conditions and carry out simulations for different control strategies. The results indicate that the linear stability analysis is a helpful tool for the judgement of the stabilization effect, although unexpected deviations can occur in the non-linear regime. There are also signs of phase transitions and chaotic behavior, but this remains to be investigated more thoroughly in the future.

cond-mat.stat-mech↗
arXiv2004

Network-Induced Oscillatory Behavior in Material Flow Networks

Network theory is rapidly changing our understanding of complex systems, but the relevance of topological features for the dynamic behavior of metabolic networks, food webs, production systems, information networks, or cascade failures of power grids remains to be explored. Based on a simple model of supply networks, we offer an interpretation of instabilities and oscillations observed in biological, ecological, economic, and engineering systems. We find that most supply networks display damped oscillations, even when their units - and linear chains of these units - behave in a non-oscillatory way. Moreover, networks of damped oscillators tend to produce growing oscillations. This surprising behavior offers, for example, a new interpretation of business cycles and of oscillating or pulsating processes. The network structure of material flows itself turns out to be a source of instability, and cyclical variations are an inherent feature of decentralized adjustments.

cond-mat.dis-nn↗
arXiv2004

Optimal traffic organisation in ants under crowded conditions

Efficient transportation, a hot topic in nonlinear science, is essential for modern societies and the survival of biological species. Biological evolution has generated a rich variety of successful solutions, which have inspired engineers to design optimized artificial systems. Foraging ants, for example, form attractive trails that support the exploitation of initially unknown food sources in almost the minimum possible time. However, can this strategy cope with bottleneck situations, when interactions cause delays that reduce the overall flow? Here, we present an experimental study of ants confronted with two alternative routes. We find that pheromone-based attraction generates one trail at low densities, whereas at a high level of crowding, another trail is established before traffic volume is affected, which guarantees that an optimal rate of food return is maintained. This bifurcation phenomenon is explained by a nonlinear modelling approach. Surprisingly, the underlying mechanism is based on inhibitory interactions. It implies capacity reserves, a limitation of the density-induced speed reduction, and a sufficient pheromone concentration for reliable trail perception. The balancing mechanism between cohesive and dispersive forces appears to be generic in natural, urban and transportation systems.

cond-mat.stat-mech↗
arXiv2004

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.

cond-mat.stat-mech↗
arXiv2004

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.

cond-mat.stat-mech↗
arXiv2004

Production, Supply, and Traffic Systems: A Unified Description

The transport of products between different suppliers or production units can be described similarly to driven many-particle and traffic systems. We introduce equations for the flow of goods in supply networks and the adaptation of production speeds. Moreover, we present two examples: The case of linear (sequential) supply chains and the case of re-entrant production. In particular, we discuss the stability conditions, dynamic solutions, and resonance phenomena causing the frequently observed "bullwhip effect", which is an analogue of stop-and-go traffic. Finally, we show how to treat discrete units and cycle times, which can be applied to the description of vehicle queues and travel times in freeway networks.

cond-mat.dis-nn↗
arXiv2003

A Section-Based Queueing-Theoretical Traffic Model for Congestion and Travel Time Analysis in Networks

While many classical traffic models treat the spatial extension of streets continuously or by discretization into cells of a certain length, we will subdivide roads into comparatively long homogeneous road sections of constant capacity with an inhomogeneity at the end. The related model is simple and numerically efficient. It is inspired by models of dynamic queueing networks and takes into account essential features of traffic flows. Instead of treating single vehicles or velocity profiles, it focusses on flows at specific cross sections and average travel times of vehicles.

cond-mat.stat-mech↗
arXiv2003

Modeling Supply Networks and Business Cycles as Unstable Transport Phenomena

Physical concepts developed to describe instabilities in traffic flows can be generalized in a way that allows one to understand the well-known instability of supply chains (the so-called ``bullwhip effect''). That is, small variations in the consumption rate can cause large variations in the production rate of companies generating the requested product. Interestingly, the resulting oscillations have characteristic frequencies which are considerably lower than the variations in the consumption rate. This suggests that instabilities of supply chains may be the reason for the existence of business cycles. At the same time, we establish some link to queuing theory and between micro- and macroeconomics.

cond-mat.stat-mech↗
arXiv2003

Fokker-Planck equation approach to vehicle statistics

This contribution presents a derivation of the steady-state distribution of velocities and distances of vehicles in freeway traffic which has been suggested for the evaluation of interaction potentials among vehicles (see preprint cond-mat/0301484). Despite the forwardly directed interactions and the additional driving terms in vehicle traffic, the steady-state velocity and distance distributions agree with the equilibrium distributions of classical many-particle systems with symmetrical interactions, if the system is large enough. Finally, this analytical result is confirmed by computer simulations.

cond-mat.stat-mech↗
arXiv2003

Assessing Interaction Networks with Applications to Catastrophe Dynamics and Disaster Management

In this paper we present a versatile method for the investigation of interaction networks and show how to use it to assess effects of indirect interactions and feedback loops. The method allows to evaluate the impact of optimization measures or failures on the system. Here, we will apply it to the investigation of catastrophes, in particular to the temporal development of disasters (catastrophe dynamics). The mathematical methods are related to the master equation, which allows the application of well-known solution methods. We will also indicate connections of disaster management with excitable media and supply networks. This facilitates to study the effects of measures taken by the emergency management or the local operation units. With a fictious, but more or less realistic example of a spreading epidemic disease or a wave of influenza, we illustrate how this method can, in principle, provide decision support to the emergency management during such a disaster. Similar considerations may help to assess measures to fight the SARS epidemics, although immunization is presently not possible.

cond-mat.stat-mech↗
arXiv2003

Many-particle simulation of the evacuation process from a room without visibility

We study the evacuation process from a smoky room by means of experiments and simulations. People in a dark or smoky room are mimicked by ``blind'' students wearing eye masks. The evacuation of the disoriented students from the room is observed by video cameras, and the escape time of each student is measured. We find that the disoriented students exhibit a distinctly different behavior compared with a situation in which people can see and orient themselves. Our experimental results are reproduced by an extended lattice gas model taking into account the empirically observed behavior. Our particular focus is on the mean value and distribution of escape times. For a large number of people in the room, the escape time distribution is wide because of jamming. Surprisingly, adding more exits does not improve the situation in the expected way, since most people use the exit that is discovered first, which may be viewed as ``herding effect'' based on accoustic interactions. Moreover, the average escape time becomes minimal for a certain finite number of people in the dark or smoky room. These non-linear effects have practical implications for emergency evacuation and the planning of safer buildings.

cond-mat.stat-mech↗
arXiv2003

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-$λ$ 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.

cond-mat.stat-mech↗
arXiv2003

Energy and Scaling Laws in Human Travel Behaviour

We show that energy concepts can contribute to the understanding of human travel behaviour. First, the average travel times for different modes of transportation are inversely proportional to the energy consumption rates measured for the respective physical activities. Second, when daily travel-time distributions by different modes of transport such as walking, cycling, bus or car travel are appropriately scaled, they turn out to have a universal functional relationship. This corresponds to a canonical-like energy distribution with exceptions for short trips, which can be theoretically explained. Altogether, this points to a law of constant average energy consumption by the physical activity of daily travelling. Applying these natural laws could help to improve long-term urban and transport planning.

cond-mat.stat-mech↗
arXiv2003

Modeling Supply Chains and Business Cycles as Unstable Transport Phenomena

Physical concepts developed to describe instabilities in traffic flows can be generalized in a way that allows one to understand the well-known instability of supply chains (the so-called ``bullwhip effect''). That is, small variations in the consumption rate can cause large variations in the production rate of companies generating the requested product. Interestingly, the resulting oscillations have characteristic frequencies which are considerably lower than the variations in the consumption rate. This suggests that instabilities of supply chains may be the reason for the existence of business cycles. At the same time, we establish some link to queuing theory and between micro- and macroeconomics.

cond-mat.stat-mech↗
arXiv2002

Drift- or Fluctuation-Induced Ordering and Self-Organization in Driven Many-Particle Systems

According to empirical observations, some pattern formation phenomena in driven many-particle systems are more pronounced in the presence of a certain noise level. We investigate this phenomenon of fluctuation-driven ordering with a cellular automaton model of interactive motion in space and find an optimal noise strength, while order breaks down at high(er) fluctuation levels. Additionally, we discuss the phenomenon of noise- and drift-induced self-organization in systems that would show disorder in the absence of fluctuations. In the future, related studies may have applications to the control of many-particle systems such as the efficient separation of particles. The rather general formulation of our model in the spirit of game theory may allow to shed some light on several different kinds of noise-induced ordering phenomena observed in physical, chemical, biological, and socio-economic systems (e.g., attractive and repulsive agglomeration, or segregation).

cond-mat.stat-mech↗