Article
Physics, Multidisciplinary
Zijian Yuan, Tao Wang, Jing Zhang, Shubin Li
Summary: This study developed a new car-following model that utilizes dynamic safe headway to prevent collisions, improve driving performance, and smooth traffic flow. The model achieved quantitative agreement with empirical data.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Engineering, Civil
Hui Jin, Haiming Hao, Xiaoguang Yang
Summary: This research focuses on the stability of vehicle following dynamics in traffic, finding that vehicles under continuous CFM model usually achieve local stability, while stability in the discrete CFM model depends on reaction time.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Physics, Applied
Wen-Jie Wang, Ming-Hui Ma, Shi-Dong Liang, Guang-Yi Ma, Yan-Song Wang
Summary: The intelligent transportation system (ITS) can improve traffic safety and efficiency by utilizing existing transportation facilities. A novel car-following model based on the two-velocity difference model (TVDM) is proposed, considering headway memory and backward looking effect. Stability conditions and evolutionary characteristics of traffic flow density wave are analyzed using linear stability theory and nonlinear theory. Numerical simulation validates that the improved model enhances traffic flow stability and eliminates congestion.
MODERN PHYSICS LETTERS B
(2022)
Article
Physics, Multidisciplinary
Guangyi Ma, Minghui Ma, Shidong Liang, Yansong Wang, Hui Guo
Summary: The newly proposed car-following model that considers backward looking effect and headway changes with memory shows through numerical simulations that it can better stabilize traffic flow and eliminate traffic congestion.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Physics, Applied
Liang Chen, Yun Zhang, Kun Li, Qiaoru Li, Qiang Zheng
Summary: A new AHT-FVD model is proposed in this study, which can effectively stabilize traffic flow and alleviate traffic congestion. Numerical simulations show that increasing the average headway weight and electronic throttle angle difference control signal coefficients can both improve traffic flow stability.
MODERN PHYSICS LETTERS B
(2021)
Article
Computer Science, Interdisciplinary Applications
Dou He, Wen-Xin Sun, Wen-Xiu Hu, Xin-Yue Guo, Geng Zhang
Summary: Based on the optimal velocity car-following model, a modified optimal velocity with dynamical safety headway is introduced, in which the dynamical safety headway is related to the vehicle's velocity compared to the constant safety headway. The influence of dynamical safety headway on the car-following performance is studied through theoretical analysis and numerical simulation. The results show that the dynamical safety headway is more efficient than the constant safety headway in improving traffic stability, enhancing traffic capacity, and shortening the vehicle starting time in the car-following process.
INTERNATIONAL JOURNAL OF MODERN PHYSICS C
(2023)
Article
Engineering, Civil
Ehsan Ramezani-Khansari, Masoud Tabibi, Fereidoon Moghadas Nejad
Summary: This study focused on validating car-following distance in DS under high traffic flow conditions. Male drivers maintained a shorter distance than female drivers, and drivers aged 20-40 were suitable for car-following tests.
IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF CIVIL ENGINEERING
(2021)
Article
Computer Science, Information Systems
Mingfei Mu, Junjie Zhang, Changmiao Wang, Jun Zhang, Can Yang
Summary: The article proposes a stabilization strategy for improving string stability and car-following safety in ACC systems, based on the DSM model and THP method, implemented through a sliding mode controller and verified through numerical simulations, demonstrating its effectiveness in enhancing traffic flow stability and avoiding rear-end collision risks.
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
Transportation
Bijul Raveendran, Tom V. Mathew, Nagendra R. Velaga
Summary: This paper investigates the impact of countdown timers on driver behavior, particularly focusing on temporal, spatial, and vehicle class-specific variations. The study develops a Long Short-Term Memory model for modeling vehicle discharge, and the model's performance is compared with field trajectory data, showing high accuracy.
TRANSPORTATION LETTERS-THE INTERNATIONAL JOURNAL OF TRANSPORTATION RESEARCH
(2022)
Article
Physics, Multidisciplinary
Ziwei Yi, Wenqi Lu, Xu Qu, Jing Gan, Linheng Li, Bin Ran
Summary: This paper presents a bidirectional distance balanced model (BDBM) for car-following in a connected environment, which balances the distance between the host vehicle and its preceding and following vehicles. The model is shown to improve traffic stability while maintaining traffic efficiency through theoretical analysis and simulations.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Engineering, Civil
Saeed Vasebi, Yeganeh M. Hayeri, Peter J. Jin
Summary: Recent advancements in computational power and traffic data availability have allowed for a re-examination of drivers' car-following behavior. While classic models focus on the preceding vehicle, newer studies suggest that incorporating information from surrounding vehicles may improve performance. This study uses deep learning and long short-term memory models to explore the impact of surrounding vehicles on car-following performance. The results suggest that in this particular study, there were minimal differences in performance between classic models and those incorporating surrounding vehicle information.
TRANSPORTATION RESEARCH RECORD
(2021)
Article
Mathematics
Hongxia Ge, Siteng Li, Chunyue Yan
Summary: This study introduces a car-following model considering the electronic throttle, and derives two equations through stability analysis and nonlinear analysis. Numerical simulations show that the visual angle and electronic throttle can enhance traffic flow stability.
Article
Physics, Multidisciplinary
Weixiu Pan, Jing Zhang, Junfang Tian, Fengying Cui, Tao Wang
Summary: This paper proposes a combination car-following model that integrates a theory-driven model with a data-driven model. By optimizing parameters and integrating prediction outcomes, the model improves accuracy and controllability, and achieves significant error reduction in numerical simulations.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2023)
Article
Engineering, Industrial
Tyron Louw, Rafael Goncalves, Guilhermina Torrao, Vishnu Radhakrishnan, Wei Lyu, Pablo Puente Guillen, Natasha Merat
Summary: Research shows that drivers' behavior adapts after using advanced driving assistance systems, leading to a reduction in time headway. However, drivers may not be aware of these changes. The presence of a lead vehicle and experiencing shorter headways during automated car-following may significantly influence drivers' subsequent manual driving behavior.
COGNITION TECHNOLOGY & WORK
(2021)
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)