List of communications
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| Winnie DAAMEN | The ability of microscopic (simulation) models to represent lane changing behavior according to reality has recently been questioned. In this paper the merging maneuver (a specific type of lane changing) is analyzed using empirical data. First, a conceptual model has been composed, including the factors influencing merging behavior, namely the merge location and its relation to prevailing driving conditions, gap acceptance and the relaxation phenomenon. The empirical dataset consists of 35 minutes covering 400 meters of freeway, collected using a camera mounted underneath a helicopter. This results in a dataset of 3459 vehicles trajectories, from which 704 trajectories describe merging vehicles. It is found that different merge locations are used under congested and free-flow traffic conditions. During free-flow, most vehicles merge at the first half of the acceleration lane. Under congested traffic conditions, relatively more merges are registered at the end of the acceleration lane. The smallest accepted gap observed in the dataset lies between 0.75 s and 1.0 s. Net headways between the merging vehicle and his new leader and new follower of less than 0.25 s are recorded. These very short accepted gaps are growing over time, indicating relaxation behavior. From the data analysis it can be concluded that gap acceptance theories, as they are used in current models and theories to model merge behavior, are not able to model the observed behavior accurately. | Empirical analysis of merging behaviour at freeway on-ramps and consequences for modelling |
| Olivier DAUCHOT |
In many interesting situations, the interactions among self-propelled
agents lead to the spontaneous emergence of self-organized collective
motion. The ubiquity of the phenomenon at all scales raises the
question of the existence of some underlying universal mechanisms.
Recent numerical and analytical studies have confirmed the existence of a transition from a disordered state at large noise to a state with various collective properties reflecting the local symmetry of the particles and their interactions. Though, there are still very few experimental situations where the onset of collective motion can be attributed to spontaneous symmetry breaking. Here, we report on experiments conducted with both polar self propelled and a-polar Brownian disks and by comparing the dynamics of both systems in the same experimental conditions, we demonstrate without ambiguity that collective motion emerges from the interplay of self-propulsion and hard-core repulsion only [1]. Interestingly the alignment, which has no nematic origin, is effectively induced during the collisions because of the self propulsion. [1] Phys. Rev. Lett 105 135702 (2010) | Collective motion of vibrated polar granular disks. |
| David GUILBERT | The communication presents the experimental platform SAROT (Site Angevin de Référence pour l’Observation du Trafic) which is composed of various sensors such as loops, lasers, cameras. From this platform, databases are collected for traffic analysis. Different applications experimented on this platform will be discuss. | Presentation of an experimental platform and applications |
| Henk HILHORST | We consider a two-lane road with two opposite traffic directions and the possibility of platoon formation and vehicles overtaking one another. We model this road on the basis of a minimal set of assumptions. Within the context of this model, as the traffic intensity on both lanes increases, a symmetry breaking occurs: there is a slow lane where long platoons form behind the slowest vehicles, and a fast lane where overtaking is easy due to the wide spacing between the slow platoons in the opposite direction. | A minimal model for two-lane bidirectional overtaking traffic |
| Serge HOOGENDOORN |
This paper proposes a new data-driven stochastic car-following model
based on the principles of psycho-spacing or action-point modeling.
It uses empirical or experimental trajectory data and mimics the main
microscopic behavioral characteristics present in the data.
In the action-point model, regions are defined in the {\em relative speed - distance headway} plane in which the follower is likely to perform an action (increase or decrease acceleration) or not. These regions can be established empirically from vehicle trajectory data, yielding a joint cumulative probability distribution function of the action points. Furthermore, the conditional distribution of the actions (the size of the acceleration or deceleration given the current distance headway and relative speed or given the acceleration before the action) can be determined from these data as well. To assess the data correctly, a new filtering technique is proposed. The main hypothesis behind this idea is that the speed profile is a continuous piecewise linear function: accelerations are piecewise constant changing values at non-equidistant discrete time instants. The durations of these constant acceleration periods are not fixed, but depend on the state of the follower in relation to its leader. The data analysis indeed illustrates that driving behavior shows non-equidistant constant acceleration periods. The aforementioned distributions of the action points and the conditional accelerations form the core of the presented data-driven stochastic model. The paper depicts the mathematical formalization describing how these distributions can be used to simulate car-following behavior. Based on empirical data collected on a Dutch motorway, we illustrate the workings of the approach and the simulation results. | Wiedemann revisited: A New Trajectory Filtering Technique and its Implications for Car-Following Modeling |
| Asja JELIC |
Human crowds and pedestrian groups exhibit complex and
coordinated spatio-temporal patterns such as the spontaneous
spatial organization of pedestrian flows into lines, and the
oscillations of fluxes at gates or intersections. Despite their
importance, these phenomena are not well understood, in
particular the `microscopic' interactions between the
individuals and with their environment which govern the
macroscopic behavior at medium and high densities.
In the frame of a collective project implying four French laboratories (LPT in Orsay, CRCA and IMT in Toulouse, BUNRAKU in Rennes), we have started an experimental and theoretical study of the formation of spatio-temporal structures within moving pedestrians crowds. We shall present the first results from the experimental campaign of 2009. Our aim is to better understand the role of the various (physical and behavioral) parameters which control and modulate these structures in controlled laboratory conditions, and to develop realistic analytical and simulation models of crowds based on these experimental data. | Dynamics of pedestrians: crowds and individuals |
| Jean-Patrick LEBACQUE |
The presentation addresses first static assignment, with emphasis on
the principles of user choice and utility. The main problem
formulations: fixed point, variational inequalities and dynamic
system, will be described. The specific difficulties related to
multi-modality will be stated. Second the communication addresses
predictive dynamic assignment, focusing on dynamic system and field
approaches. An example based on multi-agents and the cross-entropy
approch will be described.
Authors for the communication: J.P. Lebacque(1), M.M. Khoshyaran (2), T.Y. Ma(3) (1) GRETIA - INRETS (2) ETC Economics Traffic Clinic (3) LET - ISH | A short survey of assignment in transportation networks |
| Jean-Pierre NADAL | Reaction times in simple decision tasks: from neural modelling to psychophysics |
| Bertrand MAURY | We propose a general framework to incorporate congestion in the modeling of crowd motion in evacuation situations. In its simpler, microscopic form, the approach we propose is based on the definition of a desired velocity (corresponding to the velocity one would have in the absence of others); the actual velocity is then defined as the projection of this desired velocity onto the set of feasible velocities (velocity which do not violate the nonoverlapping constraints between individuals). We proposed recently a macroscopic version of this approach, which raises several issues from the theoretical, numerical, and modeling standpoints. In particular, the difference between both models sheds light on the importance of the microscopic arrangements between individuals upstream an exit door in highly packed situations. | Handling of congestion in crowd motion modeling |
| Pascal PANIZZA | Understanding the flow of discrete elements through networks is of importance for diverse phenomena, including microfluidics for controlled droplet traffic, blood flows for functioning cardiovascular systems, and even for road traffic for optimized road networks. Addressing this issue requires a description of the mechanisms that govern flow partitioning at a node. In most case, splitting rules arte complex since they often involve either human decision making or noise. droplet traffic thus appears as a model system since a droplet reaching a node simply flows through the arm having the largest volumetric flow rate. Despite this robust and simple rule this paradigmatic system exhibits complex dynamics: numerous bifurcations between periodic regimes as well as multistability are observed. Our aim is to present an overview of recent results obtained on droplet traffic in microfluidic devices. | Droplet traffic in microfluidic networks |
| Fernando PERUANI |
Self-propelled particle systems are ubiquitous in nature, flocks of
birds, school of fish, and human crows are just a few of the many
existing examples. One relevant question is how information spreads
in these highly dynamical ad-hoc networks. As one can presume, the
information propagation depends on the motility pattern exhibited by
the agents, which can be highly ordered as in a flock of birds, or
poorly organized as in a crowd.
We will start with the simple case where particles perform a simple
Brownian motion, and learn how the speed of the particles affects the
way information spreads [1,2,3]. We will then focus on a coherently
moving flock to find that statistical properties of the information
spreading are significantly different from the classical contact
process [3]. We will see that the ordering of particles, i.e., the
emergence of common moving direction, facilitates the spreading of
information.
[1] Phys. Rev. Lett. 100, 168103 (2008). [2] IEEE JSAC 28, 524-531 (2010) [3] Peruani and Chate in preparation. | Information spreading in self-propelled particle systems |
| Julien PETTRE | In the everyday exercise of controlling their locomotion, humans rely on their optic flow of the perceived environment to achieve collision-free navigation. In crowds, in spite of the complexity of the environment made of numerous obstacles, humans demonstrate remarkable capacities in avoiding collisions. Cognitive science work on human locomotion states that relatively succinct information is extracted from the optic flow to achieve safe locomotion. In this paper, we explore a novel vision-based approach of collision avoidance between walkers that fits the requirements of interactive crowd simulation. By simulating humans based on cognitive science results, we detect future collisions as well as the level of danger from visual stimuli. The motor-response is twofold: a reorientation strategy prevents future collision, whereas a deceleration strategy prevents imminent collisions. Several examples of our simulation results show that the emergence of self-organized patterns of walkers is reinforced using our approach. The emergent phenomena are visually appealing. More importantly, they improve the overall efficiency of the walkers? traffic and avoid improbable locking situations. | A Synthetic-Vision-Based Steering Approach for Crowd Simulation |
| Ludger SANTEN | We introduce a model for active transport on inhomogeneous networks embedded in a diffusive environment which is motivated by vesicular transport on actin filaments. In the presence of a hard-core interaction, particle clusters are observed that exhibit an algebraically decaying distribution in a large parameter regime, indicating the existence of clusters on all scales. The scale-free behavior can be understood by a mechanism promoting preferential attachment of particles to large clusters. The results are compared with a diffusion-limited aggregation model and active transport on a regular network. For both models we observe aggregation of particles to clusters which are characterized by a finite size scale if the relevant time scales and particle densities are considered. | Active transport and cluster formation on disordered networks |
| Andreas SCHADSCHNEIDER | We report results from large-scale experiments of pedestrian dynamics. Different scenarios are investigated, e.g. fundamental diagrams in corridors, bottlenecks and motion around corners. We also discuss the implications of these experiments for the modelling of pedestrian dynamics, especially for cellular automata approaches. | Pedestrian dynamics: From experiments to models |
| Martin TREIBER | In spite of investigating traffic flow dynamics for decades, some fundamental questions are not yet settled: Can the multitude of observed spatiotemporal patterns of congested traffic be decomposed into elementary patterns? If so, into how many patterns, and what are their defining properties? Are there two or three traffic phases, or is the concept of a ``traffic phase'' meaningless? Of which type are instabilities of traffic flow? In this contribution we want to elucidate these questions with the combined force of empirical data, models, simulations, and analytic calculations. Analyzing detector data from several hundred traffic jams on freeways in several countries, we found that nearly all of them are consistent with linear instability of the upstream-convective type, i.e., isolated perturbations grow but eventually leave the investigated area in the upstream direction. Based on this type of instability and sustained localized perturbations (e.g., lane changings near ramp regions), we develop a generic dynamic model in terms of stochastic differential equations whose parameters are analytically related to that of microscopic and macroscopic models. The approximate analytic solutions of the generic model are nearly identical to simulations of the respective microscopic or macroscopic models and consistent with observations. This gives evidence that traffic instabilities may be a product of convective instabilities and sustained perturbations. | Tackling traffic flow dynamics with the combined force of empirical data, models, simulations, and analytics |
| Véronique VEQUE | A Vehicular Ad-Hoc Network, or VANET, is a technology that uses moving cars as nodes in a network to create a mobile ad hoc network. In a VANET, each car is supposed to be equipped with a wireless network interface, and each car acts as a wireless router. In this presentation, we present VANET, its most promising applications, and related research domains which are still open: unicast routing, dissemination of message, security, etc. We focus on two specific problems and propose two associated protocols. The first problem takes place in Internet-based applications between a source and a destination where a client in the vehicle needs to access a server in Internet. This type of communication needs first to communicate with the Internet gateway. In the VANET, we have thus to provide a unicast routing scheme to find a path to reach a destination through intermediate vehicles used as routers/forwarders. The second one intends to improve safety on road by broadcasting alert messages to all the vehicles on a given highway/road section. We show that requirements for these both applications are very different. We discuss the impact of vehicles traffic (vehicle density and distributions) on these protocol performances. | Impact of vehicular traffic on some VANET applications |
| Jonathan WARD | Motivated by inductance loop data, I will speak about some recent results in the classification of the (linear) stability of highway traffic models - a much studied topic, in which nevertheless we have found new ground! In car-following models, perturbations always propagate backwards relative to platoons, but since the vehicles drive forward in space, it is not clear a priori whether "information" propagates forward or backwards relative to the road. I will thus develop the concept of "signal velocity" and show how it may be computed via asymptotic methods. It turns out that the related concept of "group velocity" is not quite the right thing to compute - and in fact, the distinction between these two velocities dates back to seminal work by Sommerfeld and Einstein at the beginning of the 20th century. - This talk represents joint work with Jonathan Ward (University of Limerick, Ireland) and also ongoing conversations with Martin Treiber (TU Dresden). | Mathematical Criteria for Convective versus Absolute Instability |
List of posters
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