We present a methodology of cooperative driving in vehicular traffic, in which for short-time traffic prediction rather than one of the statistical approaches of artificial intelligence (AI), we follow a qualitative different microscopic traffic prediction approach developed recently [Phys. Rev. E 106 (2022) 044307]. In the microscopic traffic prediction approach used for the planning of the subject vehicle trajectory, no learning algorithms of AI are applied; instead, microscopic traffic modeling based on the physics of vehicle motion is used. The presented methodology of cooperative driving is devoted to application cases in which microscopic traffic prediction without cooperative driving cannot lead to a successful vehicle control and trajectory planning. For the understanding of the physical features of the methodology of cooperative driving, a traffic city scenario has been numerically studied, in which a subject vehicle, which requires cooperative driving, is an automated vehicle. Based on microscopic traffic prediction, in the methodology first a cooperating vehicle(s) is found; then, motion requirements for the cooperating vehicle(s) and characteristics of automated vehicle control are predicted and used for vehicle motion; to update predicted characteristics of vehicle motion, calculations of the predictions of motion requirements for the cooperating vehicle and automated vehicle control are repeated for each next time instant at which new measured data for current microscopic traffic situation are available. With the use of microscopic traffic simulations, the evaluation of the applicability of this methodology is illustrated for a simple case of unsignalized city intersection, when the automated vehicle wants to turn right from a secondary road onto the priority road.

Boris S. Kerner Sergey L. Klenov Vincent Wiering Michael Schreckenberg

The Prisoner's Dilemma, a 2-person game in which the players can either cooperate or defect, is a common paradigm for studying the evolution of cooperation, when individuals exhibit variable degrees of cooperation. It is known that in the presence of spatial structure, when individuals ``play against'' their neighbours, and ``compare to'' them, cooperative investments can evolve to considerable levels. Here we examine the effect of increasing the neighbourhood size: we find that the mean-field limit of no cooperation is reached for a critical neighbourhood size of about five neighbours. We also find the related result that in a network of players, the critical average degree (number of neighbours) of nodes for which defection is the final state depends only on the network topology. This critical average degree is considerably higher for clustered networks, than for distributed random networks. This result strengthens the argument that clustering is the mechanism which makes the development and maintenance of the cooperation possible.

Margarita Ifti Timothy Killingback Michael Doebeli

In many communication networks, the availability of channel state information at various nodes provides an opportunity for network nodes to work together, or "cooperate." This work studies the benefit of cooperation in the multiple access channel with a cooperation facilitator, distributed state information at the encoders, and full state information available at the decoder. Under various causality constraints, sufficient conditions are obtained such that encoder cooperation through the facilitator results in a gain in sum-capacity that has infinite slope in the information rate shared with the encoders. This result extends the prior work of the authors on cooperation in networks where none of the nodes have access to state information.

Parham Noorzad Michelle Effros Michael Langberg

Stabilizing cooperation among self-interested individuals presents a fundamental challenge in evolutionary theory and social science. While classical models predict the dominance of defection in social dilemmas, empirical and theoretical studies have identified various mechanisms that promote cooperation, including kin selection, reciprocity, and spatial structure. In this work, we investigate the role of localized imitation in the evolutionary dynamics of cooperation within an optional Public Goods Game (PGG). We introduce a model where individuals belong to distinct groups and adapt their strategies based solely on comparisons within their own group. We identify different dynamical regimes, including stable fixed points, limit cycles, and Rock-Scissors-Paper-type oscillations. Our analysis, grounded in a replicator-type framework, reveals that such group-level imitation can stabilize cooperative behavior, provided that groups are not initially polarized around a single strategy. In other words, restricting imitation to group-level interactions mitigates the destabilizing effects of global competition, providing a potential explanation for the resilience of cooperation in structured populations.

Pierre Bousseyroux Gilles Zérah Michael Benzaquen

Cooperation is a ubiquitous phenomenon in many natural, social, and engineered systems with multiple agents. Understanding the formation of cooperation in mixed traffic is of theoretical interest in its own right, and could also benefit the design and operations of future automated and mixed-autonomy transportation systems. However, how cooperativeness of driving agents can be defined and identified from empirical data seems ambiguous and this hinders further empirical characterizations of the phenomenon and revealing its behavior mechanisms. Towards mitigating this gap, in this paper, we propose a unified conceptual framework to identify collective cooperativeness of driving agents. This framework expands the concept of collective rationality from our recent model (Li et al. 2022a), making it empirically identifiable and behaviorally interpretable in realistic (microscopic and dynamic) settings. This framework integrates mixed traffic observations at both microscopic and macroscopic scales to estimate critical behavioral parameters that describe the collective cooperativeness of driving agents. Applying this framework to NGSIM I-80 trajectory data, we empirically confirm the existence of collective cooperation and quantify the condition and likelihood of its emergence. This study provides the first empirical understanding of collective cooperativeness in human-driven mixed traffic and points to new possibilities to manage mixed autonomy traffic systems.

Di Chen Jia Li H. Michael Zhang

Several aspects of intermolecular effects in molecular conduction have been studied in recent years. These experimental and theoretical studies, made on several setups of molecular conduction junctions, have focused on the current-voltage characteristic that is usually dominated by the elastic transmission properties of such junctions. In this paper we address cooperative intermolecular effects in the inelastic tunneling signal calculated for simple generic models of such systems. We find that peaks heights in the inelasticspectrum may be affected by such cooperative effects even when direct intermolecular interactions can be disregarded. This finding suggests that comparing experimental results to calculations made on single-molecule junctions should be done with care.

Michael Galperin Abraham Nitzan

We propose utilizing the Cooper pair to induce magnetic frustration in systems of two-dimensional (2D) magnetic adatom lattices on s-wave superconducting surfaces. The competition between singlet electron correlations and the RKKY coupling is shown to lead to a variety of hidden order states that break the point-group symmetry of the 2D adatom lattice at finite temperature. The phase diagram is constructed using a newly developed effective bond theory [M. Schecter et al., Phys. Rev. Lett. 119, 157202 (2017)], and exhibits broad regions of long-range vestigial nematic order.

Michael Schecter Olav F. Syljuåsen Jens Paaske

We present a novel approach allowing the study of rare events like fixation under fluctuating environments, modeled as extrinsic noise, in evolutionary processes characterized by the dominance of one species. Our treatment consists of mapping the system onto an auxiliary model, exhibiting metastable species coexistence, that can be analyzed semiclassically. This approach enables us to study the interplay between extrinsic and demographic noise on the statistics of interest. We illustrate our theory by considering the paradigmatic prisoner's dilemma game whose evolution is described by the probability that cooperators fixate the population and replace all defectors. We analytically and numerically demonstrate that extrinsic noise may drastically enhance the cooperation fixation probability and even change its functional dependence on the population size. These results, which generalize earlier works in population genetics, indicate that extrinsic noise may help sustain and promote a much higher level of cooperation than static settings.

Michael Assaf Mauro Mobilia Elijah Roberts

Use of cooperative information, distributed by road-side units, offers large potential for intelligent vehicles (IVs). As vehicle automation progresses and cooperative perception is used to fill the blind spots of onboard sensors, the question of reliability of the data becomes increasingly important in safety considerations (SOTIF, Safety of the Intended Functionality). This paper addresses the problem to estimate the reliability of cooperative information for in-vehicle use. We propose a novel method to infer the reliability of received data based on the theory of Subjective Logic (SL). Using SL, we fuse multiple information sources, which individually only provide mild cues of the reliability, into a holistic estimate, which is statistically sound through an end-to-end modeling within the theory of SL. Using the proposed scheme for probabilistic SL-based fusion, IVs are able to separate faulty from correct data samples with a large margin of safety. Real world experiments show the applicability and effectiveness of our approach.

Johannes Müller Michael Gabb Michael Buchholz

Quantum cooperativity is evident in light-matter platforms where quantum emitter ensembles are interfaced with confined optical modes and are coupled via the ubiquitous electromagnetic quantum vacuum. Cooperative effects can find applications, among other areas, in topological quantum optics, in quantum metrology or in quantum information. This tutorial provides a set of theoretical tools to tackle the behavior responsible for the onset of cooperativity by extending open quantum system dynamics methods, such as the master equation and quantum Langevin equations, to electron-photon interactions in strongly coupled and correlated quantum emitter ensembles. The methods are illustrated on a wide range of current research topics such as the design of nanoscale coherent light sources, highly-reflective quantum metasurfaces or low intracavity power superradiant lasers. The analytical approaches are developed for ensembles of identical two-level quantum emitters and then extended to more complex systems where frequency disorder or vibronic couplings are taken into account. The relevance of the approach ranges from atoms in optical lattices to quantum dots or molecular systems in solid-state environments.

Michael Reitz Christian Sommer Claudiu Genes