Article
Green & Sustainable Science & Technology
Haochen Xu, Niaona Zhang, Zonghao Li, Zichang Zhuo, Ye Zhang, Yilei Zhang, Haitao Ding
Summary: This research introduces an energy-conserving speed planning approach using reinforcement learning for autonomous electric vehicles. By leveraging vehicle-to-vehicle and vehicle-to-infrastructure communication, real-time data is obtained to optimize driving behavior and minimize energy consumption. The evaluation results demonstrate the efficacy of the algorithm in reducing energy consumption while considering safety.
Article
Physics, Applied
Yaxing Zheng, Hongxia Ge, Rongjun Cheng
Summary: A modified lattice hydrodynamic model is proposed in this study, which takes into account the driver's sensory memory and the average optimal velocity effect field to efficiently suppress traffic congestion. The theoretical analysis and numerical simulations validate the stability and effectiveness of the model, demonstrating its accuracy in describing the evolution of traffic flow.
MODERN PHYSICS LETTERS B
(2021)
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
Energy & Fuels
Kiwon Yeom
Summary: This research proposes a hybrid learning predictive control architecture that combines model predictive control and deep reinforcement learning networks to improve the energy efficiency of electric vehicles. Experimental results demonstrate the effectiveness of this architecture in energy savings.
Article
Engineering, Mechanical
Sunita Yadav, Poonam Redhu
Summary: With the increasing autonomy of vehicles, there is a growing demand for accurate information about nearby vehicles. A new car-following model has been developed with a passing effect to study the impact of driver's attention on the average velocity of their vehicle and surrounding vehicles. The model's stability condition is obtained through linear stability analysis and the mKdV equation is used to describe the evolution properties of traffic density in jammed regions. Numerical and analytical results show phase transitions and chaotic behavior in different passing rates. Increased driver attention improves the stability region and the model's effectiveness in improving vehicle movement efficiency, reducing congestion, and enhancing road safety.
NONLINEAR DYNAMICS
(2023)
Article
Engineering, Civil
Tie-Qiao Tang, Yong Gui, Jian Zhang
Summary: This paper proposes a car-following model based on automating entropy adjustment for level 3 autonomous driving, trains the model through reinforcement learning, and validates its advantages in safe, efficient, and comfortable driving.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Automation & Control Systems
Jiaqi Xue, Xiaohong Jiao
Summary: A speed cascade control scheme is proposed for hybrid electric vehicles (HEVs), considering car-following scenarios, which utilizes a primary speed adaptive controller and a secondary electronic throttle adaptive nonlinear active disturbance rejection controller. The study shows the effectiveness and advantages of the proposed scheme for ETCS controlled HEVs.
Article
Energy & Fuels
Kiwon Yeom
Summary: This paper proposes a novel control algorithm that uses Model Predictive Control to improve the energy consumption of fully electric vehicles (FEVs) and Deep Reinforcement Learning to understand the driving environment in real-time. The algorithm is evaluated using a high fidelity car simulator and achieves a potential energy saving of 3.2% in freeway cruising and car following scenarios.
Article
Physics, Multidisciplinary
Xiangzhou Zhang, Zhongke Shi, Shaowei Yu, Lijing Ma
Summary: This paper proposes a new car-following model considering the driver's desired visual angle on curved roads, based on the influence of the two-point preview steering decision and stopping sight distance on car-following behavior in small-radius curves from the perspective of driver's visual characteristics. The dynamic performance and safety of the new model are explored. The results demonstrate that introducing the effect of the driver's desired visual, designing a reasonable curve radius, and using a large vehicle as the leading vehicle can improve the stability of traffic flow and alleviate traffic congestion, as well as effectively improve the safety of car-following behavior on curved roads.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2023)
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
Computer Science, Interdisciplinary Applications
Shihao Li, Rongjun Cheng, Hongxia Ge, Pengjun Zheng
Summary: The study explores the influence of electronic throttle dynamics and average speed of multiple preceding vehicles on traffic flow stability. A novel car-following model integrating these factors is proposed and stability conditions are obtained using control theory. Simulation experiments confirm that considering these factors enhances traffic flow stability and increasing the number of preceding vehicles improves stability as well.
ENGINEERING COMPUTATIONS
(2021)
Article
Thermodynamics
Cong Guo, Chunyun Fu, Ronghua Luo, Guanlong Yang
Summary: A cooperative multi-objective platoon control (CMOPC) strategy is proposed for an FRIDEV platoon, combining car-following control and torque distribution control to improve platoon economy. Simulation results demonstrate that the strategy can enhance platoon economy under different driving cycles.
Article
Computer Science, Information Systems
Hongqing Chu, Lulu Guo, Hong Chen, Bingzhao Gao
Summary: This study proposes a hierarchical design of optimal car-following control system, which splits the system into high-level and low-level subsystems to address issues such as preceding vehicle acceleration disturbance and road slope. The performance of the proposed optimal control scheme is evaluated through simulation and real-vehicle experiments, showing superior car-following performance compared to a factory-installed adaptive cruise controller.
SCIENCE CHINA-INFORMATION SCIENCES
(2021)
Article
Thermodynamics
Harikishan Perugu, Sonya Collier, Yi Tan, Seungju Yoon, Jorn Herner
Summary: Decarbonizing transport is an important strategy for combating climate change and reducing the health impacts of air pollutants. The transit bus sector has the potential to be electrified with Battery Electric Buses (BEBs). We analyzed the energy consumption and charging patterns of BEBs based on data collected from a transit fleet, and found that factors such as bus speed and seasonal variations in energy consumption are significant.
Article
Environmental Sciences
Junjie Zhang, Can Yang, Jun Zhang, Haojie Ji
Summary: This paper aimed to analyze the effect of different driver's behavior characteristics on car-following safety based on the desired safety margin car-following model. Through Monte Carlo simulation, the impact of driver's behavior characteristics on car-following safety under a given rear-end collision condition is investigated. The study finds that larger subjective risk perception levels, smaller acceleration sensitivity (or larger deceleration sensitivity), and faster reaction abilities of the driver can improve car-following safety. It suggests that driver's behavior characteristics can cause traffic waves in the car-following process. Therefore, adjusting driver's behavior characteristics can enhance traffic flow stability and improve car-following safety through traffic control strategies.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2023)
Article
Computer Science, Interdisciplinary Applications
Ting Wang, Rongjun Cheng, Hongxia Ge
Summary: This paper explores the impact of mixed traffic flow, self-stabilization effect, and lane changing behavior on traffic flow stability through an extended two-lane lattice hydrodynamic model. The results show that self-stabilization effect and lane changing behavior can alleviate traffic congestion. The numerical simulation verifies the theoretical findings and highlights the importance of considering these factors in traffic flow analysis.
ENGINEERING COMPUTATIONS
(2021)
Article
Computer Science, Interdisciplinary Applications
Shihao Li, Rongjun Cheng, Hongxia Ge, Pengjun Zheng
Summary: The study explores the influence of electronic throttle dynamics and average speed of multiple preceding vehicles on traffic flow stability. A novel car-following model integrating these factors is proposed and stability conditions are obtained using control theory. Simulation experiments confirm that considering these factors enhances traffic flow stability and increasing the number of preceding vehicles improves stability as well.
ENGINEERING COMPUTATIONS
(2021)
Article
Computer Science, Interdisciplinary Applications
Qingying Wang, Rongjun Cheng, Hongxia Ge
Summary: This paper explores how curved roads and empirical lane-changing rates affect the stability of traffic flow. The extended two-lane lattice hydrodynamic model takes into account the empirical lane-changing rate on a curved road. The findings suggest that the lane-changing rate can alleviate traffic congestion, and the model provides a theoretical reference for actual traffic governance.
ENGINEERING COMPUTATIONS
(2021)
Article
Physics, Multidisciplinary
Lixiang Li, Rongjun Cheng, Hongxia Ge
Summary: A novel two-dimensional lattice hydrodynamic model is proposed in this study, with linear stability condition derived by exploiting control method and kink-antikink solution of modified Korteweg-de Vries (mKdV) equation obtained through nonlinear analysis. The numerical simulation results confirm the effectiveness of the new control signal in stabilizing traffic flow, while also indicating that increasing the driver's memory time leads to increased traffic flow instability.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Physics, Applied
Rongjun Cheng, Shihao Li, Hongxia Ge
Summary: This study constructed an extended car-following model accounting for two preceding vehicles with mixed maximum velocity for more accurate analysis of traffic flow evolution. Theoretical and numerical analyses were conducted to infer the stability condition of the model and depict the propagation of traffic density wave, as well as to verify the correctness of theoretical analysis and analyze the influences of factors on traffic flow. Theoretical and experimental results indicate that considering two preceding vehicles' motion status with mixed maximum velocity leads to more stable traffic flow compared to only considering individual preceding vehicle's motion status.
MODERN PHYSICS LETTERS B
(2021)
Article
Physics, Applied
Yaxing Zheng, Hongxia Ge, Rongjun Cheng
Summary: A modified lattice hydrodynamic model is proposed in this study, which takes into account the driver's sensory memory and the average optimal velocity effect field to efficiently suppress traffic congestion. The theoretical analysis and numerical simulations validate the stability and effectiveness of the model, demonstrating its accuracy in describing the evolution of traffic flow.
MODERN PHYSICS LETTERS B
(2021)
Article
Engineering, Multidisciplinary
Weilin Ren, Rongjun Cheng, Hongxia Ge
Summary: This paper proposes a novel heterogeneous continuum traffic flow model that considers the differences of driver's psychological headway and their self-stabilizing effect on optimal velocity. Through linear and nonlinear analysis, the characteristic of traffic flow evolution is described, and numerical simulations are conducted to explore density evolution and Hopf bifurcation. The study reveals significantly different phenomena in heterogeneous traffic flow under different density conditions and the involvement of Hopf bifurcation in traffic flow evolution.
APPLIED MATHEMATICAL MODELLING
(2021)
Article
Mathematics, Applied
Weilin Ren, Rongjun Cheng, Hongxia Ge
Summary: This study introduces a novel heterogeneous traffic flow model accounting for different ratios of multiple optimal velocity functions and changes in electronic throttle angle with memory. The linear stability criterion, Korteweg-de Vries-Burgers equation, and Hopf bifurcation conditions for the improved model are theoretically derived and numerically simulated to investigate density fluctuations. The research focuses on addressing the evolution of bifurcation behavior in heterogeneous traffic flow through the initial point of the Hopf bifurcation.
APPLIED MATHEMATICS AND COMPUTATION
(2021)
Article
Computer Science, Interdisciplinary Applications
Huizhe Li, Hongxia Ge, Rongjun Cheng
Summary: The study reveals that driving between two lanes on a curved road has a negative impact on traffic flow stability; when speed is fixed, traffic flow becomes more unstable with the increase in the radius of the curve; estimating the speed of the vehicle ahead also affects the stability of traffic flow.
ENGINEERING COMPUTATIONS
(2022)
Article
Physics, Applied
Huimin Liu, Rongjun Cheng, Hongxia Ge
Summary: A novel two-lane lattice hydrodynamic model considering heterogeneous traffic flow on a gradient road is proposed and validated through linear stability analysis and nonlinear analysis. The study reveals that factors such as time lane change, slope, and mixing of different types of vehicles significantly influence traffic flow stability. Additionally, the modified Korteweg-de Vries equation is derived to describe the propagation characteristics of traffic density waves near critical points.
MODERN PHYSICS LETTERS B
(2021)
Article
Physics, Multidisciplinary
Xueyi Guan, Rongjun Cheng, Hongxia Ge
Summary: The paper introduces a feedback control considering both driver's anticipated time and response time-delay, and designs a bifurcated controller to suppress traffic congestion effectively. Simulation results demonstrate the controller's efficacy and stability in improving traffic efficiency and stability.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Liyou Li, Hang Yang, Rongjun Cheng
Summary: This paper designs a communication topology anomaly response system (CTARS) to ensure the safety of connected and automated vehicles platoons (CAVP), which has shown remarkable effectiveness in experiments.
IET INTELLIGENT TRANSPORT SYSTEMS
(2023)
Article
Engineering, Multidisciplinary
Qun Ji, Hao Lyu, Hang Yang, Qi Wei, Rongjun Cheng
Summary: In this study, a feedback control method with consideration of time delay is designed for the solid angle model (SAM) in order to alleviate unstable factor-caused bifurcation and reduce oscillations in traffic flow. The stability and bifurcation condition of the new SAM is derived through linear analysis and bifurcation analysis, and the accurate range of stable region is obtained. Numerical simulations are performed to verify the feasibility and effectiveness of the proposed method, which show that feedback gain and delay are two key factors to alleviate traffic congestion in the SAM.
JOURNAL OF ZHEJIANG UNIVERSITY-SCIENCE A
(2023)
Article
Computer Science, Information Systems
Weilin Ren, Rongjun Cheng, Hongxia Ge, Qi Wei
Article
Physics, Multidisciplinary
Shihao Li, Rongjun Cheng, Hongxia Ge
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2020)
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)
