1,199 research outputs found
Generalized Centrifugal Force Model for Pedestrian Dynamics
A spatially continuous force-based model for simulating pedestrian dynamics
is introduced which includes an elliptical volume exclusion of pedestrians. We
discuss the phenomena of oscillations and overlapping which occur for certain
choices of the forces. The main intention of this work is the quantitative
description of pedestrian movement in several geometries. Measurements of the
fundamental diagram in narrow and wide corridors are performed. The results of
the proposed model show good agreement with empirical data obtained in
controlled experiments.Comment: 10 pages, 14 figures, accepted for publication as a Regular Article
in Physical Review E. This version contains minor change
Quantitative analysis of pedestrian counterflow in a cellular automaton model
Pedestrian dynamics exhibits various collective phenomena. Here we study
bidirectional pedestrian flow in a floor field cellular automaton model. Under
certain conditions, lane formation is observed. Although it has often been
studied qualitatively, e.g., as a test for the realism of a model, there are
almost no quantitative results, neither empirically nor theoretically. As basis
for a quantitative analysis we introduce an order parameter which is adopted
from the analysis of colloidal suspensions. This allows to determine a phase
diagram for the system where four different states (free flow, disorder, lanes,
gridlock) can be distinguished. Although the number of lanes formed is
fluctuating, lanes are characterized by a typical density. It is found that the
basic floor field model overestimates the tendency towards a gridlock compared
to experimental bounds. Therefore an anticipation mechanism is introduced which
reduces the jamming probability.Comment: 11 pages, 12 figures, accepted for publication in Phys. Rev.
Modelling supported driving as an optimal control cycle: Framework and model characteristics
Driver assistance systems support drivers in operating vehicles in a safe,
comfortable and efficient way, and thus may induce changes in traffic flow
characteristics. This paper puts forward a receding horizon control framework
to model driver assistance and cooperative systems. The accelerations of
automated vehicles are controlled to optimise a cost function, assuming other
vehicles driving at stationary conditions over a prediction horizon. The
flexibility of the framework is demonstrated with controller design of Adaptive
Cruise Control (ACC) and Cooperative ACC (C-ACC) systems. The proposed ACC and
C-ACC model characteristics are investigated analytically, with focus on
equilibrium solutions and stability properties. The proposed ACC model produces
plausible human car-following behaviour and is unconditionally locally stable.
By careful tuning of parameters, the ACC model generates similar stability
characteristics as human driver models. The proposed C-ACC model results in
convective downstream and absolute string instability, but not convective
upstream string instability observed in human-driven traffic and in the ACC
model. The control framework and analytical results provide insights into the
influences of ACC and C-ACC systems on traffic flow operations.Comment: Submitted to Transportation Research Part C: Emerging Technologie
An Area-Aggregated Dynamic Traffic Simulation Model
Microscopic and macroscopic dynamic traffic models not fast enough to run in an optimization loop to coordinate traffic measures over areas of twice a trip length (50x50 km). Moreover, in strategic planning there are models with a spatial high level of detail, but lacking the features of traffic dynamics. This paper introduces the Network Transmission Model (NTM), a model based on areas, exploiting the Macroscopic or Network Fundamental Diagram (NFD). For the first time, a full operational model is proposed which can be implemented in a network divided into multiple subnetworks, and the physical properties of spillback of traffic jams for subnetwork to subnetwork is ensured. The proposed model calculates the traffic flow between to cell as the minimum of the demand in the origin cell and the supply in the destination cell. The demand first increasing and then decreasing as function of the accumulation in the cell; the supply is first constant and then decreasing as function of the accumulation. Moreover, demand over the boundaries of two cells is restricted by a capacity. This system ensures that traffic characteristics move forward in free flow, congestion moves backward and the NFD is conserved. Adding the capacity gives qualitatively reasonable effects of inhomogeneity. The model applied on a test case with multiple destinations, and re-routing and perimeter control are tested as control measures
Pedestrian flows in bounded domains with obstacles
In this paper we systematically apply the mathematical structures by
time-evolving measures developed in a previous work to the macroscopic modeling
of pedestrian flows. We propose a discrete-time Eulerian model, in which the
space occupancy by pedestrians is described via a sequence of Radon positive
measures generated by a push-forward recursive relation. We assume that two
fundamental aspects of pedestrian behavior rule the dynamics of the system: On
the one hand, the will to reach specific targets, which determines the main
direction of motion of the walkers; on the other hand, the tendency to avoid
crowding, which introduces interactions among the individuals. The resulting
model is able to reproduce several experimental evidences of pedestrian flows
pointed out in the specialized literature, being at the same time much easier
to handle, from both the analytical and the numerical point of view, than other
models relying on nonlinear hyperbolic conservation laws. This makes it
suitable to address two-dimensional applications of practical interest, chiefly
the motion of pedestrians in complex domains scattered with obstacles.Comment: 25 pages, 9 figure
A Framework for Imbalanced Time-Series Forecasting
Time-series forecasting plays an important role in many domains. Boosted by
the advances in Deep Learning algorithms, it has for instance been used to
predict wind power for eolic energy production, stock market fluctuations, or
motor overheating. In some of these tasks, we are interested in predicting
accurately some particular moments which often are underrepresented in the
dataset, resulting in a problem known as imbalanced regression. In the
literature, while recognized as a challenging problem, limited attention has
been devoted on how to handle the problem in a practical setting. In this
paper, we put forward a general approach to analyze time-series forecasting
problems focusing on those underrepresented moments to reduce imbalances. Our
approach has been developed based on a case study in a large industrial
company, which we use to exemplify the approach
Constant net-time headway as key mechanism behind pedestrian flow dynamics
We show that keeping a constant lower limit on the net-time headway is the
key mechanism behind the dynamics of pedestrian streams. There is a large
variety in flow and speed as functions of density for empirical data of
pedestrian streams, obtained from studies in different countries. The net-time
headway however, stays approximately constant over all these different data
sets. By using this fact, we demonstrate how the underlying dynamics of
pedestrian crowds, naturally follows from local interactions. This means that
there is no need to come up with an arbitrary fit function (with arbitrary fit
parameters) as has traditionally been done. Further, by using not only the
average density values, but the variance as well, we show how the recently
reported stop-and-go waves [Helbing et al., Physical Review E, 75, 046109]
emerge when local density variations take values exceeding a certain maximum
global (average) density, which makes pedestrians stop.Comment: 7 pages, 7 figure
Towards Fully Automated Psychotherapy for Adults: BAS - Behavioral Activation Scheduling via web and mobile phone
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