Article
Mathematical & Computational Biology
N. El Khatib, A. Ghorbel, A. Joumaa, M. Zaydan
Summary: In this paper, a steady state multi-anticipative traffic model is considered, and necessary and sufficient conditions for the existence of traveling solutions are provided. The word "traveling" in this work refers to the continuous variation of the distance between two consecutive vehicles between two different states. As an application, it is shown that by taking a strictly concave optimal velocity, a traveling solution can be constructed such that the distance between two vehicles decreases. The existence, uniqueness, and asymptotic behavior of such solutions are studied at the level of the Hamilton-Jacobi equation.
MATHEMATICAL MODELLING OF NATURAL PHENOMENA
(2023)
Article
Physics, Multidisciplinary
Yanmei Hu, Tianshan Ma, Jianzhong Chen
Summary: This paper proposes an extended car-following model considering bi-directional visual field and multiple anticipation, which can improve the stability of traffic flow and reproduce the local clustering phenomenon of traffic flow.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Hua Kuang, Fenglan Yang, Meiting Wang, Guanghan Peng, Xingli Li
Summary: The study introduces a novel lattice hydrodynamic model to describe traffic flow dynamics under the ITS environment with consideration of multi-anticipative average flux effect. The stability region on the phase diagram can be significantly widened by considering this effect, leading to traffic flow stability. The analytical and numerical results confirm that considering multi-anticipative average flux effect can effectively alleviate traffic congestion.
Article
Physics, Multidisciplinary
Guang-Han Peng, Rui Tang, Hua Kuang, Hui-Li Tan, Tao Chen
Summary: A new coupled map car-following model is proposed in this paper, which aims to improve the stability of vehicle running and reduce CO2 emissions by considering the difference in estimated optimal speeds. The stability of the new model is analyzed using control theory, and conditions for the stability of the traffic system are obtained. Simulation results show that the inclusion of optimal estimation of speed difference in the control term can effectively enhance the stability of vehicle running in the CM car-following model.
Article
Construction & Building Technology
Ting Shang, Jiaxin Lu, Ying Luo, Song Wang, Zhengyu He, Aobo Wang
Summary: The study reveals significant variations in car-following behavior across different types of tunnels and consecutive sections of the same tunnel. As tunnel length increases, the driving stability of following vehicles decreases, but the level of driving safety risk is not positively correlated with tunnel length. Significant vehicle trajectory oscillation is observed within the inner sections of long and extra-long tunnels, and a significant relationship between the acceleration of following vehicles and the location within the tunnel section is found.
TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY
(2024)
Article
Green & Sustainable Science & Technology
Chengju Song, Hongfei Jia
Summary: With the development of intelligent connected vehicles and communication technology, collaborative operation among vehicles will become the future trend. This study analyzed the car-following characteristics in a mixed traffic flow and discussed the effects of different car-following cases and mixing ratios on the traffic flow.
Article
Computer Science, Interdisciplinary Applications
Hua Kuang, Fang-Hua Lu, Feng-Lan Yang, Guang-Han Peng, Xing-Li Li
Summary: An extended car-following model incorporating driver's memory and mean expected velocity field effects is proposed in this paper, showing significantly improved traffic stability compared to existing models. Numerical simulations demonstrate that the coupling effect of driver's memory and mean expected velocity field can effectively suppress traffic congestion.
INTERNATIONAL JOURNAL OF MODERN PHYSICS C
(2021)
Review
Green & Sustainable Science & Technology
Junyan Han, Xiaoyuan Wang, Gang Wang
Summary: This paper explores car-following behavior under intelligent and connected conditions and emphasizes the importance of considering driver-vehicle-environment factors in modeling. Previous research is reviewed, analyzing its contributions and limitations, and discussing future research needs and prospects.
Article
Engineering, Mechanical
Guanghan Peng, Keke Wang, Hongzhuan Zhao, Huili Tan
Summary: Under the connected vehicles environment, a new coupled map car-following model that integrates cyber-attacks on the continuous delay effect has been proposed. Stable conditions related to cyber-attacks have been derived through control theory. Numerical simulations confirm the positive role of the continuous delay effect on traffic stability and pollutants emissions in the coupled map car-following model. However, cyber-attacks can damage traffic stability and lead to increased pollutants emissions, which can be mitigated through a compensation algorithm.
NONLINEAR DYNAMICS
(2023)
Article
Physics, Multidisciplinary
Guanghan Peng, Teti Jia, Hongzhuan Zhao, Huili Tan
Summary: The historical evolution information integral (HEII) effect has a significant impact on drivers' subsequent traffic behavior. The HEII effect can be transmitted through vehicle-to-X (V2X) communication technology for connected vehicles, contributing to improving traffic safety, reducing congestion, and decreasing pollution emissions. A novel car-following model is proposed based on the cooperative transmission of the HEII effect under the V2X environment, and its effectiveness is confirmed through theoretical analysis and numerical simulation.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2023)
Article
Engineering, Marine
Wenzhang Yang, Shangkun Jiang, Peng Liao, Hao Wang
Summary: Due to the importance of inland waterway transport in reducing carbon emissions, the demand for inland vessel transportation has significantly increased in China. This research conducted experiments to study vessel-following behavior in different restricted waterways and proposed improved car-following models to describe this behavior accurately. The results provide valuable insights into the characteristics of inland vessel traffic, aiding professionals in understanding and organizing inland waterway transportation effectively.
Article
Economics
Qixiu Cheng, Zhiyuan Liu, Yuqian Lin, Xuesong (Simon) Zhou
Summary: A new S3 traffic flow model was proposed in this study to represent the relationship between flow, speed, and density in highway traffic, which was calibrated using real-world traffic data. This study also derived a consistent car-following model based on the proposed S-shaped speed-density function.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Article
Green & Sustainable Science & Technology
Wenlong Liu, Yixin Chen, Hongtao Li, Hui Zhang
Summary: With the development of electronic communication technology, the driving assistance system that perceives the external traffic environment has rapidly advanced. However, quantifying the complexity of the road traffic environment without considering driving characteristics and subjective feelings can lead to increased false alarm rate, thus affecting the early warning effect. To accurately measure the complexity of the road traffic environment, this study analyzes the impact of road traffic environment changes on drivers under car-following conditions and establishes a quantitative model for road traffic environment complexity.
Article
Green & Sustainable Science & Technology
Yunze Wang, Ranran Xu, Ke Zhang
Summary: This study examines the performance and stability of mixed traffic flow (MTF) with connected and automated vehicles (CAVs) and regular vehicles (RVs). Through theoretical modeling and numerical simulations, the results show that CAVs in the Cooperative Adaptive Cruise Control (CACC) mode can significantly decelerate in response to interference from other vehicles at the microscopic level. At the macroscopic level, as the penetration rate of CAVs increases, the overall acceleration fluctuation of the traffic flow decreases, and higher density of CAVs contributes to higher stability of MTF.
Article
Engineering, Mechanical
Sunita Yadav, Poonam Redhu
Summary: According to traffic flow theory, driver behavior significantly affects traffic stability. This research proposes a novel car-following model that considers both the driver's cautious and aggressive instincts. Numerical simulations and theoretical analyses show that the aspects of the enhanced model related to driver characteristics have a major impact on traffic flow stability.
JOURNAL OF COMPUTATIONAL AND NONLINEAR DYNAMICS
(2023)
Article
Physics, Multidisciplinary
Xingli Li, Fang Guo, Hua Kuang, Zhongfei Geng, Yanhong Fan
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2019)
Article
Physics, Multidisciplinary
Guanghan Peng, Hua Kuang, Hongzhuan Zhao, Li Qing
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2019)
Article
Engineering, Civil
Shan-Shan Wu, Hua Kuang, Siu-Ming Lo
JOURNAL OF URBAN PLANNING AND DEVELOPMENT
(2019)
Article
Physics, Multidisciplinary
Zhongfei Geng, Xingli Li, Hua Kuang, Xuecen Bai, Yanhong Fan
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2019)
Article
Physics, Multidisciplinary
Guanghan Peng, Hua Kuang, Kezhao Bai
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2019)
Article
Physics, Multidisciplinary
Guanghan Peng, Kezhao Bai, Hua Kuang
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2019)
Article
Physics, Multidisciplinary
Xingli Li, Zhongfei Geng, Hua Kuang, Xuecen Bai, Yanhong Fan
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2019)
Article
Computer Science, Interdisciplinary Applications
Hua Kuang, Fang-Hua Lu, Feng-Lan Yang, Guang-Han Peng, Xing-Li Li
Summary: An extended car-following model incorporating driver's memory and mean expected velocity field effects is proposed in this paper, showing significantly improved traffic stability compared to existing models. Numerical simulations demonstrate that the coupling effect of driver's memory and mean expected velocity field can effectively suppress traffic congestion.
INTERNATIONAL JOURNAL OF MODERN PHYSICS C
(2021)
Article
Physics, Multidisciplinary
Guang-Han Peng, Rui Tang, Hua Kuang, Hui-Li Tan, Tao Chen
Summary: A new coupled map car-following model is proposed in this paper, which aims to improve the stability of vehicle running and reduce CO2 emissions by considering the difference in estimated optimal speeds. The stability of the new model is analyzed using control theory, and conditions for the stability of the traffic system are obtained. Simulation results show that the inclusion of optimal estimation of speed difference in the control term can effectively enhance the stability of vehicle running in the CM car-following model.
Article
Physics, Multidisciplinary
Guanghan Peng, Teti Jia, Hua Kuang, Huili Tan
Summary: A novel lattice hydrodynamic model is proposed based on the delayed effect of synergistic information transmission involving density and flux. The model's stability condition is theoretically analyzed, and the modified Korteweg-de Vries equation near the critical point is obtained through nonlinear analysis. The results show that the delayed effect of collaborative information transmission can effectively suppress traffic congestion, reduce energy consumption, and improve the stability of the traffic system.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Physics, Multidisciplinary
Guang-Han Peng, Te-Ti Jia, Hua Kuang, Hui-Li Tan, Tao Chen
Summary: A novel car-following model is proposed based on the delayed effect of cooperative information transmission, which can improve traffic stability and reduce additional energy consumption according to theoretical analysis and numerical simulation.
Article
Computer Science, Interdisciplinary Applications
Xingli Li, Jie Zheng, Jiangtao Tian, Shanshan Ma, Hua Kuang
Summary: This study proposes an extended cellular automata model to simulate the behavior of blind people in evacuation process taking into account the influence of obstacles. Numerical simulations show that longitudinal obstacles can effectively divert blind people, while horizontal obstacles of appropriate length can improve evacuation efficiency. These findings provide theoretical basis for the organization, management, and optimization of evacuation strategies for blind people.
INTERNATIONAL JOURNAL OF MODERN PHYSICS C
(2023)
Article
Computer Science, Information Systems
Hua Kuang, Fenglan Yang, Meiting Wang, Guanghan Peng, Xingli Li
Summary: The study introduces a novel lattice hydrodynamic model to describe traffic flow dynamics under the ITS environment with consideration of multi-anticipative average flux effect. The stability region on the phase diagram can be significantly widened by considering this effect, leading to traffic flow stability. The analytical and numerical results confirm that considering multi-anticipative average flux effect can effectively alleviate traffic congestion.
Article
Physics, Multidisciplinary
Xiaoyu Shi, Jian Zhang, Xia Jiang, Juan Chen, Wei Hao, Bo Wang
Summary: This study presents a novel framework using offline reinforcement learning to improve energy consumption in road transportation. By leveraging real-world human driving trajectories, the proposed method achieves significant improvements in energy consumption. The offline learning approach demonstrates generalizability across different scenarios.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Junhyuk Woo, Soon Ho Kim, Hyeongmo Kim, Kyungreem Han
Summary: Reservoir computing (RC) is a new machine-learning framework that uses an abstract neural network model to process information from complex dynamical systems. This study investigates the neuronal and network dynamics of liquid state machines (LSMs) using numerical simulations and classification tasks. The findings suggest that the computational performance of LSMs is closely related to the dynamic range, with a larger dynamic range resulting in higher performance.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Yuwei Yang, Zhuoxuan Li, Jun Chen, Zhiyuan Liu, Jinde Cao
Summary: This paper proposes an extreme learning machine (ELM) algorithm based on residual correction and Tent chaos sequence (TRELM-DROP) for accurate prediction of traffic flow. The algorithm reduces the impact of randomness in traffic flow through the Tent chaos strategy and residual correction method, and avoids weight optimization using the iterative method. A DROP strategy is introduced to improve the algorithm's ability to predict traffic flow under varying conditions.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Chengwei Dong, Min Yang, Lian Jia, Zirun Li
Summary: This work presents a novel three-dimensional system with multiple types of coexisting attractors, and investigates its dynamics using various methods. The mechanism of chaos emergence is explored, and the periodic orbits in the system are studied using the variational method. A symbolic coding method is successfully established to classify the short cycles. The flexibility and validity of the system are demonstrated through analogous circuit implementation. Various chaos-based applications are also presented to show the system's feasibility.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Viorel Badescu
Summary: This article discusses the maximum work extraction from confined particles energy, considering both reversible and irreversible processes. The results vary for different types of particles and conditions. The concept of exergy cannot be defined for particles that undergo spontaneous creation and annihilation. It is also noted that the Carnot efficiency is not applicable to the conversion of confined thermal radiation into work.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
P. M. Centres, D. J. Perez-Morelo, R. Guzman, L. Reinaudi, M. C. Gimenez
Summary: In this study, a phenomenological investigation of epidemic spread was conducted using a model of agent diffusion over a square region based on the SIR model. Two possible contagion mechanisms were considered, and it was observed that the number of secondary infections produced by an individual during its infectious period depended on various factors.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zuan Jin, Minghui Ma, Shidong Liang, Hongguang Yao
Summary: This study proposes a differential variable speed limit (DVSL) control strategy considering lane assignment, which sets dynamic speed limits for each lane to attract vehicle lane-changing behaviors before the bottleneck and reduce the impact of traffic capacity drop. Experimental results show that the proposed DVSL control strategy can alleviate traffic congestion and improve efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Matthew Dicks, Andrew Paskaramoorthy, Tim Gebbie
Summary: In this study, we investigate the learning dynamics of a single reinforcement learning optimal execution trading agent when it interacts with an event-driven agent-based financial market model. The results show that the agents with smaller state spaces converge faster and are able to intuitively learn to trade using spread and volume states. The introduction of the learning agent has a robust impact on the moments of the model, except for the Hurst exponent, which decreases, and it can increase the micro-price volatility as trading volumes increase.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zhouzhou Yao, Xianyu Wu, Yang Yang, Ning Li
Summary: This paper developed a cooperative lane-changing decision system based on digital technology and indirect reciprocity. By introducing image scoring and a Q-learning based reinforcement learning algorithm, drivers can continuously evaluate gains and adjust their strategies. The study shows that this decision system can improve driver cooperation and traffic efficiency, achieving over 50% cooperation probability under any connected vehicles penetration and traffic density, and reaching 100% cooperation probability under high penetration and medium to high traffic density.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Josephine Nanyondo, Henry Kasumba
Summary: This paper presents a multi-class Aw-Rascle (AR) model with area occupancy expressed in terms of vehicle class proportions. The qualitative properties of the proposed equilibrium velocity and the stability conditions of the model are established. The numerical results show the effect of proportional densities on the flow of vehicle classes, indicating the realism of the proposed model.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Oliver Smirnov
Summary: This study proposes a new method for simultaneously estimating the parameters of the 2D Ising model. The method solves a constrained optimization problem, where the objective function is a pseudo-log-likelihood and the constraint is the Hamiltonian of the external field. Monte Carlo simulations were conducted using models of different shapes and sizes to evaluate the performance of the method with and without the Hamiltonian constraint. The results demonstrate that the proposed estimation method yields lower variance across all model shapes and sizes compared to a simple pseudo-maximum likelihood.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Przemyslaw Chelminiak
Summary: The study investigates the first-passage properties of a non-linear diffusion equation with diffusivity dependent on the concentration/probability density through a power-law relationship. The survival probability and first-passage time distribution are determined based on the power-law exponent, and both exact and approximate expressions are derived, along with their asymptotic representations. The results pertain to diffusing particles that are either freely or harmonically trapped. The mean first-passage time is finite for the harmonically trapped particle, while it is divergent for the freely diffusing particle.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Hidemaro Suwa
Summary: The choice of transition kernel is crucial for the performance of the Markov chain Monte Carlo method. A one-parameter rejection control transition kernel is proposed, and it is shown that the rejection process plays a significant role in determining the sampling efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Xudong Wang, Yao Chen
Summary: This article investigates the joint influence of expanding medium and constant force on particle diffusion. By starting from the Langevin picture and introducing the effect of external force in two different ways, two models with different force terms are obtained. Detailed analysis and derivation yield the Fokker-Planck equations and moments for the two models. The sustained force behaves as a decoupled force, while the intermittent force changes the diffusion behavior with specific effects depending on the expanding rate of the medium.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
