样式: 排序: IF: - GO 导出 标记为已读
-
-
Physical models of traffic safety at crossing streams Physica A (IF 3.3) Pub Date : 2024-03-21 Andreas Leich, Ronald Nippold, Andreas Schadschneider, Peter Wagner
Traffic safety at intersecting streams is studied quantitatively using methods from Statistical Mechanics on the basis of simple microscopic traffic flow models. In order to determine a relationship between traffic flow and the number of crashes, the modeling focus is on the building block of any road network, namely the crossing of two streams. In this paper, it is shown that the number of crossing
-
Impact of risk preferences on evacuee behavior and attention distribution in urban underground space evacuations Physica A (IF 3.3) Pub Date : 2024-03-20 Yixuan Wei, Yixing Zhang, Yifei Xu, Shu Wang, Jianguo Liu, Longzhe Jin, Shengnan Ou, Song Pan, Yiqiao Liu
Evacuation and conducting emergency rescue operations in underground spaces pose substantial challenges. However, limited work has been done to investigate how evacuees’ heterogeneity influence the evacuation efficiency. In this study, we conducted virtual environment experiment and on-site experiment to analyze the physical behavior and attention distribution of evacuees with different risk preferences
-
Enhancing lane changing trajectory prediction on highways: A heuristic attention-based encoder-decoder model Physica A (IF 3.3) Pub Date : 2024-03-19 Xue Xiao, Peng Bo, Yingda Chen, Yili Chen, Keping Li
Accurate prediction of lane changing (LC) trajectories plays a vital role in ensuring safe and efficient traffic flow on highways. This paper proposes a LC trajectory prediction model based on encoder-decoder architecture to address low long-term prediction accuracy problem and to gain insight into the underlying motivations of LC behavior. Three specific enhancements were proposed to improve the performance
-
Universality of area occupancy-based fundamental diagrams in mixed traffic Physica A (IF 3.3) Pub Date : 2024-03-19 Nandan Maiti, Jorge A. Laval, Bhargava Rama Chilukuri
Modeling and investigating the properties of fundamental diagrams (FDs) in mixed traffic, which encompasses heterogeneous with non-lane-based flow, has been one of the emerging research areas in the past few years. The main challenges in modeling are: estimating accurate steady-state () points based on empirical observations and properly representing FDs in mixed traffic conditions. The first part
-
Cooperative bound states in quantum walks of interacting particles Physica A (IF 3.3) Pub Date : 2024-03-18 M.F.V. Oliveira, M.S. Santos Junior, Michele B. Coêlho, F.A.B.F. de Moura, W.S. Dias
Although multiparticle quantum walks have been claimed to be universal for quantum computing, fundamental issues still need further understanding, such as the formation of bound states and their role in particle dynamics. By considering the framework of two-particle quantum walks, we study particles with short- or long-range interactions between them and observe the emergence of local and non-local
-
Segmental estimation and testing method for power-law distributions and some extensions Physica A (IF 3.3) Pub Date : 2024-03-18 Xinyi Luo
For discrete segmental power-law distributions, the probability ratio is a linear function of the exponent parameter. Based on this property, the estimation of the exponent parameter and a goodness-of-fit testing method are provided. The proposed testing method is parameter-independent and the testing statistic is proved to asymptotically follow a chi-square distribution. In the region where power-law
-
Corrigendum to “Spatial early warning signals for tipping points using dynamic mode decomposition” [Phys. A: Stat. Mech. Appl. vol. 596, 15 June 2022, 127152] Physica A (IF 3.3) Pub Date : 2024-03-18 G.M. Donovan, C. Brand
-
Analysis of roadway capacity for heterogeneous traffic flows considering the degree of trust of drivers of HVs in CAVs Physica A (IF 3.3) Pub Date : 2024-03-16 Yulong Pei, Sheng Pan, Yuhang Wen
Future traffic flows will be driven by a mixture of CAVs and HVs. Under heterogeneous traffic flow conditions, drivers of HVs will change their following distance when driving behind CAVs due to psychological factors, which will affect road capacity. This study builds a heterogeneous traffic flow model based on the Markov chain theory, which can derive the proportions of different car-following types
-
Functional form selection and calibration of macroscopic fundamental diagrams Physica A (IF 3.3) Pub Date : 2024-03-16 Wenfei Ma, Yunping Huang, Xiao Jin, Renxin Zhong
Macroscopic fundamental diagram (MFD) is widely applied in network-level traffic control and management with most applications necessitating a well-calibrated MFD. With various data sources, more and more empirical MFDs are documented, while the MFD functional form is predetermined by traffic engineers based on their prior experiences. To our best, no generally accepted functional form has been identified
-
Dynamic relationship between the XRP price and correlation tensor spectra of transaction networks Physica A (IF 3.3) Pub Date : 2024-03-16 Abhijit Chakraborty, Tetsuo Hatsuda, Yuichi Ikeda
The emergence of cryptoassets has sparked a paradigm shift in the world of finance and investment, ushering in a new era of digital assets with profound implications for the future of currency and asset management. A recent study showed that during the bubble period around the year, 2018, the price of cryptoasset, XRP has a strong anti correlation with the largest singular values of the correlation
-
Corrigendum to “Informative fractal dimension associated with nonmetricity in information geometry” [Physica A 625 (2023) 129017] Physica A (IF 3.3) Pub Date : 2024-03-16 Mitsuhiro Hirano, Hiroyuki Nagahama
-
Quantum self-organizing feature mapping neural network algorithm based on Grover search algorithm Physica A (IF 3.3) Pub Date : 2024-03-15 Zi Ye, Kai Yu, Gong-De Guo, Song Lin
Self-organizing feature mapping neural network is a typical unsupervised neural network algorithm, which is often used for clustering analysis and data compression. As the amount of data increases, the time consumption required by the algorithm becomes increasingly large, which becomes a new challenge. To address this issue, a quantum self-organizing feature mapping neural network is proposed in this
-
Eigenvalue-based quantum state verification of three-qubit W class states Physica A (IF 3.3) Pub Date : 2024-03-15 Daipengwei Bao, Min Liu, Yangwei Ou, Qingshan Xu, Qin Li, Xiaoqing Tan
In quantum many-body systems, W class states are typical examples of states with genuine multipartite entanglement. They have been found to be valuable resources in many quantum information processing tasks. However, the characterization and verification of W class states still remains an intractable problem. Here we first propose an eigenvalue-based verification protocol consisting of four practical
-
Platoon-aware cooperative lane-changing strategy for connected automated vehicles in mixed traffic flow Physica A (IF 3.3) Pub Date : 2024-03-14 Yangsheng Jiang, Li Tan, Guosheng Xiao, Yunxia Wu, Zhihong Yao
The platooning management technology for Connected Automated Vehicles (CAVs) can potentially increase the efficiency of the traffic system. However, the randomness in the spatial distribution of CAVs poses a new challenge for CAVs’ platooning strategy in mixed traffic flow. To effectively utilize the advantages of platooning technology, this paper proposes a platoon-aware cooperative lane-changing
-
Modelling the dual dynamic traffic flow evolution with information perception differences between human-driven vehicles and connected autonomous vehicles Physica A (IF 3.3) Pub Date : 2024-03-13 Guanfeng Wang, Hongfei Jia, Tao Feng, Jingjing Tian, Ruiyi Wu, Heyao Gao, Chao Liu
The introduction of connected autonomous vehicles (CAVs) potentially improves the link capacity and backward wave speed of traffic flow, while the advanced communication technology could well make it possible to allow CAV users to share their travel information. To bridge the knowledge gaps in the network evolution under mixed environment of human-driven vehicles (HVs) and CAVs, it is essential to
-
Indications for an alternative breaking of symmetry in fracture-induced electromagnetic emissions recorded prior to the 2023 Mw7.8 and Mw7.5 Turkey Earthquakes Physica A (IF 3.3) Pub Date : 2024-03-13 Stelios M. Potirakis, Yiannis Contoyiannis
Several evidence has been reported corroborating the view that the MHz band fracture-induced electromagnetic emissions (FEME), also known as fracture-induced electromagnetic radiation (FEMR), which are detected prior to shallow main earthquakes (EQs) of moment magnitude Mw>5.5 with epicenters on land or near coastline, can be studied in analogy to a Z(2) spin system undergoing a second-order phase
-
Dynamic characteristics of the sideways movement of pedestrians: An experimental study based on single-file experiments Physica A (IF 3.3) Pub Date : 2024-03-13 Bangkun Tan, Chenrui Xuan, Wei Xie, Meng Shi, Yi Ma
In this paper, we investigate the dynamic characteristics of the sideways movements of pedestrians toward the left-hand side and right-hand side through a set of single-file experiments. We find that the velocities of pedestrians during sideways movement periodically fluctuate, and the corresponding spatiotemporal diagram of pedestrian movement exhibits a jagged pattern. In addition, by analyzing the
-
Car-following model considering jerk-constrained acceleration stochastic process for emission estimation Physica A (IF 3.3) Pub Date : 2024-03-13 Dongli Meng, Guohua Song, Jianchang Huang, Hongyu Lu, Yizheng Wu, Lei Yu
The continuity of acceleration changes is often overlooked by existing car-following models, leading to a limitation in capturing realistic driving dynamics for emission estimation, which are essential for the application in microscopic traffic evaluations. This paper investigated and modeled the jerk-constrained acceleration stochastic process using the Markov model. A new car-following model considering
-
Heralded quantum network coding of multi-particle states based on quantum time-bin multiplexing Physica A (IF 3.3) Pub Date : 2024-03-12 Bing-Xin Liu, Yu-Guang Yang, Guang-Bao Xu, Dong-Huan Jiang, Yi-Hua Zhou, Wei-Min Shi, Dan Li
Quantum network coding can effectively alleviate bottlenecks in quantum networks thus improving the transmission efficiency and the throughput of the quantum network. Although various quantum network coding protocols have been constructed, most of them focus mainly on addressing the communication congestion issue of simultaneously transmitting single-qubit states via the bottleneck channel in quantum
-
Avalanche scaling law for heterogeneous interfacial fracture Physica A (IF 3.3) Pub Date : 2024-03-12 Jinping Fu, Wei Du, Huiming Hou, Xiaohua Zhao
A new approach is proposed to study the statistical law of avalanches due to the fracture of a heterogeneous interface. Firstly, a discrete interface is considered as a bundle of fibers clamped with two elastic circular plates, fiber strength being either a random variable or a stochastic field. Based on the theory of solid mechanics, equations governing the dynamic fracture process of fibers under
-
Parameter estimation for Gipps’ car following model in a Bayesian framework Physica A (IF 3.3) Pub Date : 2024-03-12 Samson Ting, Thomas Lymburn, Thomas Stemler, Yuchao Sun, Michael Small
Car following model is an important part in traffic modelling and has attracted a lot of attentions in the literature. As the proposed car following models become more complex with more components, reliably estimating their parameters becomes crucial to enhance model predictive performance. While most studies adopt an optimisation-based approach for parameters estimation, we present a statistically
-
Expressway lane change strategy of autonomous driving based on prior knowledge and data-driven Physica A (IF 3.3) Pub Date : 2024-03-11 Zhangu Wang, Changming Guan, Ziliang Zhao, Jun Zhao, Chen Qi, Zilaing Hui
Automatic driving in expressways is generally considered to be the easiest for commercial landing, and vehicle behavior decision-making is the core of automatic driving technology, which directly affects the safety and comfort of vehicle driving. In this paper, an automatic lane change strategy based on prior knowledge and data-driven is proposed for expressway. Our method decouples autonomous driving
-
Collective behaviors of fractional-order FithzHugh–Nagumo network Physica A (IF 3.3) Pub Date : 2024-03-11 Zhao Yao, Kehui Sun, Huihai Wang
Brain connection is the mechanism of determining the brain function and cognition, and the small world network is widely investigated among these connections. In this paper, the small world complex brain network is constructed by the fractional-order neurons, and the fractional-order memristor is used to connect these neurons. Compared with the integer-order counterpart, the fractional-order memristor
-
A novel regional traffic control strategy for mixed traffic system with the construction of congestion warning communities Physica A (IF 3.3) Pub Date : 2024-03-11 Xiaoning Gu, Chao Chen, Tao Feng, Baozhen Yao
Large-scale congestion can lead to traffic paralysis, which severely hampers the flow of vehicles and disrupts the normal functioning of urban traffic. Traffic optimization strategies can effectively improve the performance of road networks, but often ignore the impact of regional traffic conditions and equity. This paper presents a novel traffic strategy to solve regional traffic congestion in large
-
Collision avoidance behaviours of luggage-laden pedestrians Physica A (IF 3.3) Pub Date : 2024-03-11 Zhigang Shi, Jun Zhang, Zhigang Shang, Weiguo Song
Understanding how pedestrians move and avoid collisions is essential for ensuring safety in crowded environments. In this study, we conducted detailed experiments, focusing on variables such as movement type (walking and running), encounter angles (90 and 180 degrees), and pedestrian characteristics. We analyzed a total of 168 trajectories to gain insights into the collision avoidance strategies employed
-
Modeling heterogenous crowd evacuation on stairs in high-rise buildings using a fine discrete floor field cellular automaton model: Accounting for speed and boundary layer variations Physica A (IF 3.3) Pub Date : 2024-03-11 Qi Huang, Tianyu Qin, Lin Luo, Gaobo Yang, Zhijian Fu, Xiaobo Liu
The article investigates the impact of crowd heterogeneities on stair evacuation dynamics in high-rise building. Using a fine discrete floor field cellular automaton () model, the study explores the often-overlooked influence of crowd variations in mobility and behaviors. The simulation, set in a 21-story staircase, incorporates variations in speeds and boundary layer widths to replicate the heterogenous
-
Measuring user influence in real-time on twitter using behavioural features Physica A (IF 3.3) Pub Date : 2024-03-08 Md Ahsan Ul Hasan, Azuraliza Abu Bakar, Mohd Ridzwan Yaakub
-
Non-extensive (Tsallis) q-statistics and auroral glow Physica A (IF 3.3) Pub Date : 2024-03-04 A.A. Chernyshov, B.V. Kozelov, M.M. Mogilevsky
It is well-known that the auroral region of the magnetosphere–ionosphere interaction is an open, nonlinear dissipative system far from the equilibrium state. It is in this region that auroras are regularly observed, demonstrating not only a wide variety of dynamic forms but also a wide range of temporal and spatial scales. Due to the memory effects and fractal properties of auroral plasma, as well
-
Eco-driving-based mixed vehicular platoon control model for successive signalized intersections Physica A (IF 3.3) Pub Date : 2024-03-04 Pangwei Wang, Xindi Wang, Rongsheng Ye, Yuanzhe Sun, Cheng Liu, Juan Zhang
Electric vehicles have been considered into effective solutions to address energy problems in urban traffic systems for their remarkable performance in energy costs and carbon emissions reduction. However, the energy-saving effect of electric vehicles in urban traffic systems is restricted due to the complexities arising from mixed traffic conditions. To improve energy efficiency, this paper proposes
-
Stability and dynamics of self-bound state of spin–orbit coupled spin-1 Bose–Einstein condensates Physica A (IF 3.3) Pub Date : 2024-03-03 Jie Wang, Jun-Cheng Liang, An-Qing Zhang, Ai-Xia Zhang, Ju-Kui Xue
We study self-bound state of spin–orbit (SO) coupled spin-1 BECs under the action of the SO coupling and the density-dependent and spin-dependent interactions. The phase transition conditions from the magnetized phase to the unmagnetized phase are analytically obtained in the self-bound state, and the physical mechanism of the phase transition is revealed. The distinct properties of self-bound state
-
Vehicle group identification and evolutionary analysis using vehicle trajectory data Physica A (IF 3.3) Pub Date : 2024-03-03 Cailin Lei, Yuxiong Ji, Qiangqiang Shangguan, Yuchuan Du, Siby Samuel
Vehicles often move forward in groups on the highways, especially when speed and density are high simultaneously. Abnormal maneuvers of a vehicle in a group influence multiple vehicles surrounding it, potentially leading to traffic accidents. We propose an approach to identify vehicle groups and analyse the factors influencing their evolutions using vehicle trajectory data. The proposed approach quantifies
-
Evaluating and enhancing the safety performance of automated longitudinal control at on-ramp merging bottleneck: A simulation study in the framework of Kerner’s three-phase traffic theory Physica A (IF 3.3) Pub Date : 2024-03-02 Haifei Yang, Enze Zhao, Yi Zhao, Yishun Li
The adaptive cruise control (ACC) system, an essential component of commercial autonomous driving that functions in longitudinal control, has attracted significant research interest because of its potential to reduce accident rates. By introducing a non-fixed headway concept, Kerner recently proposed the Three-traffic-Phase ACC (TPACC) model, which integrates a speed adaptation module derived from
-
Microbiome abundance patterns as attractors and the implications for the inference of microbial interaction networks Physica A (IF 3.3) Pub Date : 2024-03-02 Isabella-Hilda Mendler, Barbara Drossel, Marc-Thorsten Hütt
Inferring microbial interaction networks from abundance patterns is an important approach to advance our understanding of microbial communities in general and the human microbiome in particular. Here we suggest discriminating two levels of information contained in microbial abundance data: (1) the quantitative abundance values and (2) the pattern of presences and absences of microbial organisms. The
-
On the ideal gas law for crowds with high pressure Physica A (IF 3.3) Pub Date : 2024-03-02 Zexu Li, Lei Fang
Active particle systems, such as human crowds, are out of equilibrium posing a significant challenge in identifying a suitable equation of state. However, several previous observations suggest that a crowd’s speed distribution may conform to a two-dimensional Maxwell–Boltzmann distribution under certain yet-to-be-determined conditions. Our research uncovers that the divergence between the fluctuation
-
Exploring synchronizability of complex dynamical networks from edges perspective Physica A (IF 3.3) Pub Date : 2024-03-02 Ying Zheng, Yayong Wu, Guo-Ping Jiang
With the rapid development of network information technology, synchronization problem of complex dynamical networks has garnered extensive attention. Current research predominantly concentrates on analyzing synchronizability and synchronization control in the complex dynamical networks with static edge weights or single weight attribute connections. However, there is limited research on networks characterized
-
“All-or-none” dynamics and local-range dominated interaction leading to criticality in neural systems Physica A (IF 3.3) Pub Date : 2024-03-01 JinHao Yang, Yiming Ding, Zengru Di, DaHui Wang
Since the first observation of criticality in neural systems, many researchers have thought that the nervous system can operate in a critical state, and an increasing number of models equipped with different mechanisms have been proposed. We believe that there are simple mechanisms underlying the criticality in neural systems. We constructed a neural network model to investigate the mechanism underlying
-
Modeling dedicated lanes for connected autonomous vehicles with poly-information uncertainties and electronic throttle dynamics Physica A (IF 3.3) Pub Date : 2024-03-01 Zihao Wang, Chen Xing, WENXING ZHU, Xiaolong Ma
Numerous studies have demonstrated that connected autonomous vehicles and human-driven vehicles are now coexisting throughout a transitional phase. Traffic flow can be improved, the system can be stabilized, and less energy will be used with dedicated lanes for connected autonomous vehicles. Additionally, with few communication resources, no communication delivery is ever perfect, leading to issues
-
Transparent windows in a layered medium with mosaic layers.Windows distribution by area Physica A (IF 3.3) Pub Date : 2024-03-01 R, o, m, a, n, , Y, e, ., , B, r, o, d, s, k, i, i
The work considers a layered system, the layers of which consist of transparent and opaque elements. At the places where parts of the transparent elements are opposite each other in all layers, a transparent through window is formed. The work is devoted to the case when transparent and opaque elements are the cells of a Voronoi mosaic. The distributions of windows by area were obtained for different
-
Uncertainty modeling of connected and automated vehicle penetration rate under mixed traffic environment Physica A (IF 3.3) Pub Date : 2024-03-01 Jiali Peng, Wei Shangguan, Cong Peng, Linguo Chai
Accurate knowledge of the penetration rate of connected and automated vehicles (CAVs) is crucial for effective control applications during the transition from mixed traffic to full CAV deployment. Previous studies have focused on characterizing or controlling mixed traffic with a fixed CAV penetration rate. However, in reality, the on-road penetration rate of CAVs varies, even if their market share
-
A strength and sparsity preserving algorithm for generating weighted, directed networks with predetermined assortativity Physica A (IF 3.3) Pub Date : 2024-02-28 Yelie Yuan, Jun Yan, Panpan Zhang
Degree-preserving rewiring is a widely used technique for generating unweighted networks with given assortativity, but for weighted networks, it is unclear how an analog would preserve the strengths and other critical network features such as sparsity level. This study introduces a novel approach for rewiring weighted networks to achieve desired directed assortativity. The method utilizes a mixed integer
-
Surrounding vehicle trajectory prediction under mixed traffic flow based on graph attention network Physica A (IF 3.3) Pub Date : 2024-02-28 Yuan Gao, Jinlong Fu, Wenwen Feng, Tiandong Xu, Kaifeng Yang
This paper proposes a trajectory prediction method based on graph attention network to accurately predict the trajectories of HDV (Human Drive Vehicles) around the ICV (Intelligent Connected Vehicles) under mixed traffic flow scenario on highways. Firstly, the vehicle trajectory data is filtered and smoothed to construct a trajectory prediction dataset containing map information. Secondly, the vehicle
-
Resilience analysis of highway network under rainfall using a data-driven percolation theory-based method Physica A (IF 3.3) Pub Date : 2024-02-28 Yang Li, Jialu Wu, Yunjiang Xiao, Hangqi Hu, Wei Wang, Jun Chen
This paper proposes a data-driven approach using percolation theory to analyze the resilience of highway networks under rainfall conditions. The proposed approach's main contribution is integrating real-world traffic data with percolation theory to evaluate the impact of rainfall on traffic flow and identify the critical links of highway networks. The resilience indicators, accounting for network topology
-
Modular nudging models: Formulation and identification from real-world traffic data sets Physica A (IF 3.3) Pub Date : 2024-02-28 Jing Li, Di Liu, Simone Baldi
The vehicle nudging behaviour suggests that a vehicle in the traffic flow may induce a ‘pushing effect’ to its preceding vehicle. In other words, while the traditional vehicle-following behaviour results in look-ahead interaction, the nudging behaviour may result in look-behind interaction: the combination of the two effects would result in bidirectional inter-vehicle interactions. Unfortunately, all
-
Real-time freeway traffic state estimation for inhomogeneous traffic flow Physica A (IF 3.3) Pub Date : 2024-02-27 Mingming Zhao, Hongxin Yu, Yibing Wang, Bin Song, Liang Xu, Dianchen Zhu
This paper addresses model-based approach considering online model parameters estimation to estimate the real-time freeway traffic state for inhomogeneous traffic flow. Its effectiveness is demonstrated through macroscopic simulation and the influence of detector configuration on the estimation performance is investigated. The results indicate that when a freeway is inhomogeneity, additional detectors
-
Coupled dynamics of information propagation and emotion influence: Emerging emotion clusters for public health emergency messages on the Chinese Sina Microblog Physica A (IF 3.3) Pub Date : 2024-02-27 Fulian Yin, Xinyi Tang, Tongyu Liang, Qinghua Kuang, Jinxia Wang, Rui Ma, Fang Miao, Jianhong Wu
A major distinction between the COVID-19 pandemic and previous pandemics is the significant role of social media platforms in shaping public adherence to non-pharmaceutical interventions and vaccine acceptance. The information propagation and individual emotion communication relevant to public health messages have been promoted in the Chinese Sina Microblog, one of the most popular social platforms
-
Effects of three-faced strategy on the evolution of cooperation in social dilemma Physica A (IF 3.3) Pub Date : 2024-02-27 Sinan Feng, Xuesong Liu
Cooperative behavior can contribute to the development of society. Evolutionary game theory is a fundamental framework for studying cooperative behavior. This article explores the evolutionary dynamics of the three-faced strategy, which can demonstrate its different attribute behaviors according to different types of objects encountered by paying a certain role-switching cost. When three-faced individuals
-
A multi-task spatio-temporal generative adversarial network for prediction of travel time reliability in peak hour periods Physica A (IF 3.3) Pub Date : 2024-02-27 Feng Shao, Hu Shao, Dongle Wang, William H.K. Lam
Travel time reliability (TTR) serves as a crucial indicator for evaluating the efficiency and service quality of a road traffic network. This paper proposes a multi-task spatio-temporal generative adversarial network (MTST-GAN) model that simultaneously predicts the TTR in morning and evening peak hour periods. The model incorporates multi-graph convolutional networks to extract spatial correlations
-
Analysis of local density during football stadium access: Integrating pedestrian flow simulations and empirical data Physica A (IF 3.3) Pub Date : 2024-02-27 Ander García, Dariel Hernández-Delfin, Borja González, Germán Garitaonaindia, Dae-Jin Lee, Marco Ellero
This study analyzes numerically the access of football fans to a typical football stadium through pedestrian flow simulations. With this aim, we introduce a novel framework to address the difficulty of simulating pedestrian dynamics in highly complex geometries with multiple accesses. The framework consists of a combination of the Social Force Model (SFM) and Computational Fluid Dynamics tools to calculate
-
Accurate solution of the Index Tracking problem with a hybrid simulated annealing algorithm Physica A (IF 3.3) Pub Date : 2024-02-27 Álvaro Rubio-García, Samuel Fernández-Lorenzo, Juan José García-Ripoll, Diego Porras
An actively managed portfolio almost never beats the market in the long term. Thus, many investors often resort to passively managed portfolios whose aim is to follow a certain financial index. The task of building such passive portfolios aiming also to minimize the transaction costs is called Index Tracking (IT), where the goal is to track the index by holding only a small subset of assets in the
-
Multistep traffic speed prediction: A sequence-to-sequence spatio-temporal attention model Physica A (IF 3.3) Pub Date : 2024-02-27 Di Yang, Hong Li, Peng Wang, Lihong Yuan
Multistep traffic speed prediction plays a crucial role in alleviating road congestion and improving transport efficiency. In actual traffic networks, the spatio-temporal dependence among roads dynamically changes over time due to factors such as road conditions and unforeseen incidents, which brings great challenges to multistep traffic speed prediction. Additionally, multistep traffic speed prediction
-
Impact of detour on traffic flow in branching Koch curve network with bottleneck Physica A (IF 3.3) Pub Date : 2024-02-24 Takashi Nagatani
There are various routes with and without detours in city traffic network with a complex connectivity. Branching Koch curve fractal has such complex connectivity with singly, doubly, and multiply connecting links. We consider branching Koch curve as a city traffic network. We study the effect of detour routes (bypasses) on macroscopic traffic flow in branching Koch curve network with a bottleneck.
-
Analytical results in calculating the entropy of recurrence microstates Physica A (IF 3.3) Pub Date : 2024-02-24 Felipe Eduardo Lopes da Cruz, João Vitor Vieira Flauzino, Sergio Roberto Lopes, Thiago de Lima Prado
Since the development of recurrence plots (RP) and recurrence quantification analysis (RQA), there has been a growing interest in many areas in studying physical systems using recursion techniques. In particular, as part of the RQAs, we observed the development of the concept of recurrence microstates, defined as small blocks obtained from a recurrence graph. It can be shown that some other RQAs can
-
Collective dynamics of fluctuating–damping coupled oscillators in network structures: Stability, synchronism, and resonant behaviors Physica A (IF 3.3) Pub Date : 2024-02-24 Ruoqi Zhang, Lin Meng, Lei Yu, Sihong Shi, Huiqi Wang
The investigation of collective behaviors and synergies in coupled systems holds great significance in many fields. In this paper, we propose the coupled system of overdamped fluctuating–damping oscillators in a general network framework. Our initial theoretical analysis focuses on the system’s synchronization and stability, revealing that both the first and second moments of the mean field are asymptotic
-
Cooperative control of dynamic CAV dedicated lanes and vehicle active lane changing in expressway bottleneck areas Physica A (IF 3.3) Pub Date : 2024-02-22 Yunran Di, Weihua Zhang, Heng Ding, Xiaoyan Zheng, Bin Ran
Bottleneck areas on expressways plague the operational efficiency of entire road systems. In mixed traffic flow environments consisting of connected and autonomous vehicles (CAVs) and connected human-driven vehicles (CHVs), it is believed that road capacity can be improved to relieve traffic congestion in bottleneck areas by setting CAV dedicated lanes (CDLs) on expressways. Existing static CDL setup
-
Urban rail transit passenger flow prediction with ResCNN-GRU based on self-attention mechanism Physica A (IF 3.3) Pub Date : 2024-02-22 Changxi Ma, Bowen Zhang, Shukai Li, Youpeng Lu
With the development of modern cities, urban rail transit has become an indispensable part of residents' travelling mode, and accurate prediction of urban rail transit passenger flow is particularly important. However, due to the non-linearity and non-stability of passenger flow, the low quality of big data and the lack of data make it more and more difficult to predict the passenger flow of urban
-
Interplay of network topologies in aviation delay propagation: A complex network and machine learning analysis Physica A (IF 3.3) Pub Date : 2024-02-22 Qiang Li, Lu Wu, Xinjia Guan, Ze-jin Tian
In this study, the fundamental characteristics of flight delay propagation and the key factors influencing such propagation are investigated. Three distinct types of networks were constructed: an aviation network, a traffic flow network, and a delay propagation network. Employing complex network theory, an analysis of the fundamental topological attributes of each network was conducted, exploring the
-
Simulating the bi-directional pedestrian flow under high densities by a floor field cellular automaton model Physica A (IF 3.3) Pub Date : 2024-02-22 Shuyi Fang, Cheng-Jie Jin, Rui Jiang, Dawei Li
In this paper we propose one floor field cellular automaton model, which can simulate the bi-directional pedestrian flow at high densities. Based on the model rules proposed by Nowak and Schadschneider, we make some modifications, including changes of cell size, realistic velocity configurations and extended lateral movement. The best parameters are determined by the results of sensitivity analysis
-
Multifractal information on reading eye tracking data Physica A (IF 3.3) Pub Date : 2024-02-21 Marcos M. Meo, Francisco R. Iaconis, Jessica A. Del Punta, Claudio A. Delrieux, Gustavo Gasaneo
The study of the multifractal characteristics of physiological processes attracted wide interest in recent decades, since evidence has been found that the presence of certain alterations in these processes is reflected in the variability of their dynamics. However, neurocognitive processes have not been so widely studied from this perspective. We aim to provide new insights regarding the alterations
-
Recovering network topology and dynamics from sequences: A machine learning approach Physica A (IF 3.3) Pub Date : 2024-02-20 Lucas Guerreiro, Filipi N. Silva, Diego R. Amancio
Sequences are prevalent in myriad real-world scenarios, making it imperative to discern the mechanisms behind symbol generation and, subsequently, to decode complex system behaviors. Diverging from conventional graph analysis methods that primarily relies on Markov chains and time series analysis, this paper offers a fresh perspective based on network science to understand sequences produced by agents