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Alexandre Nicolas

Publications and source records attributed to Alexandre Nicolas.

At least 19 recordsLinked to original sources
arXiv2026

Physics of anticipatory active matter, with application to crowd dynamics

Statistical Physics has traditionally dealt with entities that interact merely based on the present, and possibly past, configurations. This reactive framework is inefficient in many situations involving living beings, such as predators chasing a prey, pedestrians, or even robots. This paper introduces a statistical physical framework for the dynamics of anticipatory agents, whose present-time dynamics depend on the prospective system state that they anticipate. We clarify how these dynamics can be expressed in terms of a cost function constructed based on observations and we show that the dynamics of an anticipatory agent in d dimensions can be mapped onto the dynamics of a (non-anticipatory) chain in d + 1 dimensions, with fluctuations acting transversely on the chain to account for the uncertainty about the future state. Insights from polymer Physics help us characterize the dynamics of these chains and delineate an anticipation horizon beyond which the blurry future can be handled in a mean-field way. The foregoing framework is successfully applied to pedestrian dynamics, leading to a seamless integration of operational and tactical levels in an agent-based model. Even with a minimal expression of the cost, the model succeeds in reproducing various experimental scenarios which are challenging for state-of-the-art models, such as crossing cluttered environments or alighting from a crowded train. The transparent and flexible basis of the model allows the straightforward incorporation of additional mechanisms.

physics.soc-ph↗
arXiv2026

Smart On-Street Parking: Survey of Actual Implementations in Cities and Insights from Practitioners

Smart solutions for on-street parking, which collect and leverage real-time information about on-street parking space availability to guide drivers or adjust policies, have attracted considerable attention in academia and in the corporate world, but comprehensive feedback on actual implementations was still missing. Here, we survey around 25 smart parking (SP) implementations in cities across the world using online sources. To get more candid insights, we complement this objective review with case studies centred around interviews that we conducted with practitioners from ten cities across continents (San Francisco, Saint Pete Beach, Penang, Douala, Soissons, Grand Paris Seine Ouest, Montpellier, Frauenfeld, Zurich, Perth). Summing up our observations, we underline the broad diversity of SP implementations in terms of contexts and scales, from 2-to-3-year small-scale pilot studies to large deployments that take centre stage in a city's mobility policy. Technological choices also vary widely, from the ground sensors used in pioneering deployments in the early 2010s and still in use, to static cameras (which cover more spaces per device), and to mobile cameras with automatic licence-plate recognition embarked in roaming cars, a more and more popular solution for parking control. Different attitudes to the role given to smartphone applications are also noticed. But, importantly, not only means, but also goals differ: facilitating parking control and enhancing revenue, or providing data for a curb-pricing strategy, or feeding live data into navigation algorithms to reduce parking search times. Unfortunately, their level of achievement is seldom gauged with robust metrics. Hardware durability issues are mentioned as causes of premature termination, particularly for `first-generation' ground sensors, but so, too, are fluctuating political will and changing priorities. Smaller-scale, geographically isolated implementations and pilots are particularly vulnerable to these fluctuations, to discontinued funding or defaulting start-ups, and to limited public awareness.

physics.soc-ph↗
arXiv2025

Model-Based Assessment of__the__Cruising Traffic and Environmental Impact of__Parking Restrictions

In many large metropolitan areas, cars cruising for parking significantly contribute to congestion and pollution. At the same time, parking restrictions are contemplated to encourage the use of greener transport alternatives. We give a short overview of a versatile modelling framework for parking search, which can be solved by both numerical simulations and theoretical developments, and we illustrate its applicability in Lyon, France. Then, we show how this framework can be leveraged to assess the environmental impact of parking restrictions, weighing the antagonistic effects of the thus-induced excess cruising vs. mode shift.

physics.soc-ph↗
arXiv2025

LEMONS: An open-source platform to generate non-circuLar, anthropometry-based pEdestrian shapes and simulate their Mechanical interactiONS in two dimensions

To model dense crowds, the usual recourse to oversimplified (circular) pedestrian shapes and contact forces shows limitations. To help modellers overcome these limitations, we propose an open-source numerical tool. It consists of a Python library that generates 2D and 3D pedestrian crowds based on anthropometric data, and a C++ library that computes mechanical contacts with other agents and with obstacles, and evolves the crowd's configuration. Additionally, we provide an online platform with a user-friendly graphical interface for the Python library, and scripts to call the C++ library from Python. The tool enables users to implement their own decisional layer, i.e., to control the agents' choices of desired velocities.

cond-mat.soft↗
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↗
arXiv2025

Towards more reliable public transportation Wi-Fi Origin-Destination matrices: Modeling errors using synthetic noise and optical counts

To continuously monitor mobility flows aboard public transportation, low-cost data collection methods based on the passive detection of Wi-Fi signals are promising technological solutions, but they yield uncertain results. We assess the accuracy of these results in light of a three-month experimentation conducted aboard buses equipped with Wi-Fi sensors in a sizable French conurbation. We put forward a method to quantify the error between the stop-to-stop origin-destination (O-D) matrix produced by Wi-Fi data and the ground truth, when the (estimated and real) volumes per boarding and alighting are known. To do so, the error in the estimated matrix is modeled by random noise. Neither additive, nor multiplicative noise replicate the experimental results. Noise models that concentrate on the short O-D trips and/or the central stops better reflect the structure of the error. But only by introducing distinct uncertainties between the boarding stop and the alighting stop can we recover the asymmetry between the alighting and boarding errors, as well as the correct ratios between these aggregate errors and the O-D error. Thus, our findings give insight into the main sources of error in the Wi-Fi based reconstruction of O-D matrices. They also provide analysts with an automatic and reproducible way to control the quality of O-D matrices produced by Wi-Fi data, using (readily available) count data.

stat.ME↗
arXiv2024

Modelling vehicle and pedestrian collective dynamics: Challenges and advances

In our urbanised societies, the management and regulation of traffic and pedestrian flows is of considerable interest for public safety, economic development, and the conservation of the environment. However, modelling and controlling the collective dynamics of vehicles and pedestrians raises several challenges. Not only are the individual entities self-propelled and hard to describe, but their complex nonlinear physical and social interactions makes the multi-agent problem of crowd and traffic flow even more involved. In this chapter, we purport to review the suitability and limitations of classical modelling approaches through four examples of collective behaviour: stop-and-go waves in traffic flow, lane formation, long-term avoidance behaviour, and load balancing in pedestrian dynamics. While stop-and-go dynamics and lane formation can both be addressed by basic reactive models (at least to some extent), the latter two require anticipation and/or coordination at the level of the group. The results highlight the limitations of classical force-based models, but also the need for long-term anticipation mechanisms and multiscale modelling approaches. In response, we review new developments and modelling concepts.

physics.soc-ph↗
arXiv2024

Continuous agent-based modeling of adult-child pairs based on a pseudo-energy: Relevance for public safety and egress efficiency

Pushes, falls, stampedes, and crushes are safety hazards that emerge from the collective motion of crowds, but might be avoided by better design and guidance. While pedestrian dynamics are now getting better understood on the whole, complex heterogeneous flows involvinge.g. adult-child pairs, though widely found at e.g. crowded Chinese training schools, still defy the current understanding and capabilities of crowd simulation models. We substantially extend a recent agent-based model in which each agent's choice of motion results from the minimization ofa sum of intuitive contributions, in order to integrate adult-child pairs. This is achieved by adding a suitably defined pairing potential. The resulting model captures the relative positions of pair members in a quantitative fashion, as confirmed by small-scale controlled experiments, and alsosucceeds in describing collision avoidance between pairs. The model is used to simulate mixed adult-child flows at a T-junction and test the sensitivity to the design and pairing strategies. Simulation shows that making the post-confluence corridor wide enough is critical to avoidfriction in the flow, and that tight hand-holding is advisable for safer evacuations (whereas more loosely bound pairs get split at high density) and, more marginally, more efficient egresses in normal conditions.

physics.soc-ph↗
arXiv2024

Dense Crowd Dynamics and Pedestrian Trajectories: A Multiscale Field Study at the F\^ete des Lumi\`eres in Lyon

We present one of the first comprehensive field datasets capturing dense pedestrian dynamics across multiple scales, ranging from macroscopic crowd flows over distances of several hundred meters to microscopic individual trajectories, including approximately 7,000 recorded trajectories. The dataset also includes a sample of GPS traces, statistics on contact and push interactions, as well as a catalog of non-standard crowd phenomena observed in video recordings. Data were collected during the 2022 Festival of Lights in Lyon, France, within the framework of the French-German MADRAS project, covering pedestrian densities up to 4 individuals per square meter.

physics.soc-ph↗
arXiv2024

Modeling of obstacle avoidance by a dense crowd as a Mean-Field Game

In this paper we use a minimal model based on Mean-Field Games (a mathematical framework apt to describe situations where a large number of agents compete strategically) to simulate the scenario where a static dense human crowd is crossed by a cylindrical intruder. After a brief explanation of the mathematics behind it, we compare our model directly against the empirical data collected during a controlled experiment replicating the aforementioned situation. We then summarize the features that make the model adhere so well to the experiment and clarify the anticipation time in this framework.

physics.soc-ph↗
arXiv2023

Viral transmission in pedestrian crowds: Coupling an open-source code assessing the risks of airborne contagion with diverse pedestrian dynamics models

We study viral transmission in crowds via the short-ranged airborne pathway using a purely model-based approach. Our goal is two-pronged. Firstly, we illustrate with a concrete and pedagogical case study how to estimate the risks of new viral infections by coupling pedestrian simulations with the transmission algorithm that we recently released as open-source code. The algorithm hinges on pre-computed viral concentration maps derived from computational fluid dynamics (CFD) simulations. Secondly, we investigate to what extent the transmission risk predictions depend on the pedestrian dynamics model in use. For the simple bidirectional flow under consideration, the predictions are found to be surprisingly stable across initial conditions and models, despite the different microscopic arrangements of the simulated crowd, as long as the crowd evolves in a qualitatively similarly way. On the other hand, when major changes are observed in the crowd's behaviour, notably whenever a jam occurs at the centre of the channel, the estimated risks surge drastically.

cs.MA↗
arXiv2023

Revisiting the theoretical basis of agent-based models for pedestrian dynamics

Robust agent-based models for pedestrian dynamics, which can predict the motion of pedestrians in various situations without specific adjustment of the model or its parameters, are highly desirable. But the modeller's task is challenging, in part because it mingles different types of processes (cognitive and mechanical ones) and different levels of description (global path planning and local navigation). We argue that the articulations between these processes or levels are not given sufficient attention in many current modelling frameworks and that this deficiency hampers the effectiveness of these models. Conversely, if a decision-making layer and a mechanical one are adequately distinguished, the former controlling the desired velocity that enters the latter, and if local navigation is not guided solely by intermediate way-points towards the target, but by broader spatial information (e.g., a floor field), then greater robustness can be achieved. This is illustrated with the ANDA model, recently proposed based on such considerations, which was found to reproduce a remarkably wide range of crowd scenarios with a single set of intrinsic parameters.

physics.soc-ph↗
arXiv2023

Non-monotonic flow variations in a TASEP-based traffic model featuring cars searching for parking

The Totally Asymmetric Simple Exclusion Process (TASEP) is a paradigm of out-of-equilibrium Statistical Physics that serves as a simplistic model for one-way vehicular traffic. Since traffic is perturbed by cars cruising for parking in many metropolises, we introduce a variant of TASEP, dubbed SFP, in which particles are initially cruising at a slower speed and aiming to park on one of the sites adjacent to the main road, described by a unidimensional lattice. After parking, they pull out at a finite rate and move at a normal speed. We show that this model, which breaks many of the conservation rules applicable in other TASEP variants, exhibits singular features, in particular non-monotonic variations of the steady-state current with the injection rate and re-entrant transitions in the phase diagram, for some range of parameters. These features are robust to variations in the update rule and the boundary conditions.Neither the slow speed of cruising cars nor the perturbation of the flow due to pull-out maneuvers, taken in isolation, can rationalize these observations. Instead, they originate in a cramming (or `paper jam') effect which results from the coupling of these mechanisms: injecting too many cars into the system saturates the first sites of the road, which prevents parked cars from pulling out, thus forcing cruising cars to travel farther along the road.These strong discrepancies with even the qualitative trends of the baseline TASEP model highlight the importance of considering the effect of perturbations on traffic.

cond-mat.stat-mech↗
arXiv2023

Near-future projections in continuous agent-based models for crowd dynamics: mathematical structures in use and their implications

This paper addresses the theoretical foundations of pedestrian models for crowd dynamics. While the topic gains momentum, current models differ widely in their mathematical structure, even if we only consider continuous agent-based models. To clarify their underpinning, we first lay the mathematical foundations of the common hierarchical decomposition into strategic, tactical, and operational levels and underline the practical interest in preserving the continuity between the latter two levels by working with a floor field, rather than way-points. Turning to local navigation, we clarify how three archetypical approaches, namely, purely reactive models, anticipatory models based on the idea of times to collision, and game theory, differ in the way they extrapolate trajectories in the near future. We also insist on the oft-overlooked distinction between processes pertaining to decision-making and physical contact forces. The implications of these differences are illustrated with a comparison of the numerical predictions of these models in the simple scenario of head-on collision avoidance between agents, by varying the walking speed, the reaction times, and the degree of courtesy of the agents, notably.

physics.soc-ph↗
arXiv2023

Time-continuous microscopic pedestrian models: an overview

We give an overview of time-continuous pedestrian models with a focus on data-driven modelling. Starting from pioneer, reactive force-based models we move forward to modern, active pedestrian models with sophisticated collision-avoidance and anticipation techniques through optimisation problems. The overview focuses on the mathematical aspects of the models and their different components. We include methods used for data-based calibration of model parameters, hybrid approaches incorporating neural networks, and purely data-based models fitted by deep learning. The conclusion outlines some development perspectives that we expect to grow in the coming years.

physics.soc-ph↗
arXiv2023

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

Parking search in urban street networks: Taming down the complexity of the search-time problem via a coarse-graining approach

The parking issue is central in transport policies and drivers' concerns, but the determinants of the parking search time remain relatively poorly understood. The question is often handled in a fairly ad hoc way, or by resorting to crude approximations. Very recently, we proposed a more general agent-based approach, which notably takes due account of the role of the street network and the unequal attractiveness of parking spaces, and showed that it can be solved analytically by leveraging the machinery of Statistical Physics and Graph Theory, in the steady-state mean-field regime. Although the analytical formula is computationally more efficient than direct agent-based simulations, it involves cumbersome matrices, with linear size proportional to the number of parking spaces. Here, we extend the theoretical approach and demonstrate that it can be further simplified, by coarse-graining the parking spot occupancy at the street level. This results in even more efficient analytical formulae for the parking search time, which could be used efficiently by transport engineers.

physics.soc-ph↗
arXiv2022

Body and mind: Decoding the dynamics of pedestrians and the effect of smartphone distraction by coupling mechanical and decisional processes

Pedestrians are able to anticipate, which gives them an edge in avoiding collisions and navigating in cluttered spaces. However, these capabilities are impaired by digital distraction through smartphones, a growing safety concern. To capture these features, we put forward a continuous agent-based model (dubbed ANDA) hinging on a transparent delineation of a decision-making process, wherein a desired velocity is selected as the optimum of a perceived cost, and a mechanical layer that handles contacts and collisions. Altogether, the model includes less than a dozen parameters, many of which are fit using independent experimental data. The versatility of ANDA is demonstrated by numerical simulations that successfully replicate empirical observations in a very wide range of scenarios. These scenarios vary from collision avoidance involving one, two, or more agents, to collective flow properties in unidirectional and bidirectional settings, and to the dynamics of evacuation through a bottleneck, where contact forces are directly accessible. Remarkably, the model is able to replicate the enhanced chaoticity of the flow observed experimentally in 'smartphone-walking' pedestrians, by reducing the frequency of decisional updates, replicating the digital distraction effect. The conceptual transparency of the model makes it easy to pinpoint the origin of its current limitations and to clarify the singular position of pedestrian crowds amid active-matter systems.

cond-mat.stat-mech↗