Article
Mathematics, Applied
Yicai Zhang, Min Zhao, Dihua Sun, Shi Hui Wang, Shuai Huang, Dong Chen
Summary: This study investigates the mixed traffic lattice hydrodynamic model to analyze the mixed traffic situation with connected and non-connected vehicles, and obtains the stability conditions of the traffic system and the modified Korteweg-de Vries equation through linear and nonlinear analysis. The numerical simulation results confirm the theoretical findings, showing that increasing the communication range and permeability of connected vehicles will enhance the stability of the traffic system.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2021)
Article
Transportation Science & Technology
Panagiotis Typaldos, Markos Papageorgiou, Ioannis Papamichail
Summary: This article presents a path-planning algorithm for connected and non-connected automated road vehicles on multilane motorways. The algorithm utilizes real-time information exchange and short-term prediction to improve the efficiency of connected controlled vehicles in achieving their desired speed and improving the overall traffic flow.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Computer Science, Information Systems
Zuping Cao, Lili Lu, Chen Chen, Xu Chen
Summary: This paper proposes a generic car-following modeling framework for mixed traffic flow on urban roads, considering regular vehicles and connected vehicles. The study shows that increasing the market penetration rates of CACC vehicles can significantly improve traffic flow efficiency.
Article
Physics, Multidisciplinary
Jing Zhang, Keyu Xu, Guangyao Li, Shubin Li, Tao Wang
Summary: This study constructs an intelligent microscopic model considering driver reactions to the future motion of preceding vehicles, and the analysis shows that having information about the future motion of multiple preceding vehicles can significantly improve traffic stability. Experimental results demonstrate that knowledge of the changing trend of multiple headways can smooth traffic flow.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Transportation Science & Technology
Qinzheng Wang, Yun Yuan, Xianfeng (Terry) Yang, Zhitong Huang
Summary: This paper proposes an adaptive traffic signal control system in a CV environment, aiming to reduce vehicle delay, improve arterial performance, and show superior effectiveness under various CV penetration rates and demand levels.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Computer Science, Artificial Intelligence
Yi Wang, Yangsheng Jiang, Yunxia Wu, Zhihong Yao
Summary: This paper proposes a control strategy for connected and automated vehicles (CAVs) that considers the driving behavior of CAV platoons. Numerical simulations show that this strategy effectively reduces traffic oscillations and congestion, and performs better than the existing strategy in improving traffic efficiency.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Telecommunications
Quan Yuan, Bo Chen, Guiyang Luo, Jinglin Li, Fangchun Yang
Summary: Intelligent and connected vehicles make use of edge computing to improve their understanding of the environment and planning capabilities. This paper proposes a multi-scale decentralized optimization method to address the curse of dimensionality. The algorithm combines backpressure algorithm for route planning at large scale and game-theoretic multi-agent learning for regional resource allocation at small scale, outperforming baseline algorithms.
CHINA COMMUNICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Hanlin Wu, Haibo Zhou, Jiwei Zhao, Yunting Xu, Bo Qian, Xuemin Shen
Summary: In this paper, a traffic prediction framework and path planning method for connected vehicular networks are developed to alleviate urban traffic congestion. By using deep learning algorithm, the spatial-temporal characteristics of vehicular traffic are obtained, and the path planning is refined based on the traffic prediction information. The proposed approach has been validated using actual vehicle data and digital map, showing its effectiveness in relieving urban traffic congestion and providing guidance for data-intensive traffic management.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2022)
Article
Transportation Science & Technology
Anshuman Sharma, Zuduo Zheng, Jiwon Kim, Ashish Bhaskar, Md Mazharul Haque
Summary: This study models the mixed traffic of traditional vehicles and connected vehicles, considering the impact of driver compliance. Two simulation experiments are conducted to measure traffic flow disturbance, efficiency, and safety, while also investigating the spatial distribution of connected vehicles in platoons. The findings highlight the importance of spatial arrangement of connected vehicles in platoons, showing that they can suppress traffic flow disturbance and enhance efficiency and safety, but caution is needed in their deployment in real-world traffic.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Engineering, Civil
Ellen F. Grumert, Iman Pereira
Summary: Information-sharing between traffic signals and connected vehicles can enhance traffic conditions in signalized intersections. The proposed application, heads-up green, aims to inform queuing connected vehicles about a switch from red to green, reducing drivers' reaction time and increasing the number of vehicles that can pass the intersection. A simulation-based evaluation shows that heads-up green can improve travel time by up to 15% at high demand levels.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Hao Lyu, Ting Wang, Rongjun Cheng, Hongxia Ge
Summary: This paper proposes an improved longitudinal control strategy for connected and automated truck platoons (CATP) to effectively deal with the threat of cyberattacks. By designing a communication topology safety response system (CTSRS) and combining it with the distributed model predictive control (DMPC) method, the stability and security of the truck platoon are ensured even when cyberattacks occur.
IET INTELLIGENT TRANSPORT SYSTEMS
(2022)
Article
Robotics
Florent Lamiraux, Joseph Mirabel
Summary: This article introduces a software platform called humanoid path planner tailored for prehensile manipulation planning. The platform uses a constraint graph to model manipulation planning and extends the RRT algorithm to solve a variety of problems. It also provides replicable experimental results through a Docker image for readers to download and run on their own.
IEEE TRANSACTIONS ON ROBOTICS
(2022)
Article
Computer Science, Artificial Intelligence
Haotian Shi, Yang Zhou, Keshu Wu, Sikai Chen, Bin Ran, Qinghui Nie
Summary: This study proposes an innovative integrated two-dimensional control strategy for connected automated vehicles, using deep reinforcement learning. The strategy efficiently controls the vehicles in terms of both stability-wise longitudinal control performance and accurate lateral path-tracking performance. The controller utilizes vehicle-to-everything communication and roadway geometry information, and applies a physics-informed DRL state fusion approach and reward function to better utilize the information and borrow the merits of control theory concepts. Simulated experiments validate the controller's accuracy and stability-wise performance in diverse traffic scenarios.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Engineering, Civil
Zhihong Yao, Yunxia Wu, Yangsheng Jiang, Bin Ran
Summary: This study aims to address the issues of when and how many dedicated lanes for connected automated vehicles (CAVs) should be set up. The researchers analyzed the car-following models and their proportions in mixed traffic flow with and without CAVs dedicated lanes. They derived the fundamental diagram of mixed traffic flow and analyzed the traffic capacity with and without CAVs dedicated lanes. The study also discussed the sensitivity of related parameters and found that increasing CAVs penetration rate and free-flow speed can improve traffic capacity.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Shaohua Cui, Feng Cao, Bin Yu, Baozhen Yao
Summary: As inter-vehicle communication and automatic driving technology continue to develop, regular vehicles, connected vehicles, and connected autonomous vehicles (CAVs) will coexist on the road for a long time. The impact of connected and autonomous technologies on heterogeneous traffic stability was theoretically analyzed, with the conclusion that certain communication and cooperation methods can help stabilize mixed traffic. Increasing CAV penetration rates improve the stability of heterogeneous traffic, while a larger single fleet size can weaken stability according to the theoretical results.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Yilun Lin, Xingyuan Dai, Li Li, Fei-Yue Wang
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2019)
Article
Physics, Multidisciplinary
Xiao Wang, Rui Jiang, Li Li, Yi-Lun Lin, Fei-Yue Wang
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2019)
Article
Transportation Science & Technology
Yunpeng Wang, Pinlong Cai, Guangquan Lu
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2020)
Article
Chemistry, Physical
Yihan Yang, Guangmeng Qu, Hua Wei, Zhiquan Wei, Chao Liu, Yilun Lin, Xinming Li, Cuiping Han, Chunyi Zhi, Hongfei Li
Summary: By designing an aqueous electrolyte with a weakly solvating effect, a durable anion-derived solid electrolyte interface (SEI) with high ion conduction properties is constructed, which significantly restrains dendrite formation and adverse reactions on the Zn anode surface, leading to high reversibility of deposition/stripping, ultra-long lifespan over 5000 h, and exceptional cumulative capacity. The formation mechanism of SEI and the composition distribution of anion-derived inorganic-rich SEI are clarified in detail. Furthermore, the Zn//Prussian blue analogue (PBA) full battery exhibits a high voltage platform of 2.1 V and delivers 99.3% capacity retention after 5000 cycles, benefiting from the synergy of the elaborate SEI and regulated electrolyte environment.
ADVANCED ENERGY MATERIALS
(2023)
Article
Computer Science, Information Systems
Xingyuan Dai, Chen Zhao, Xiao Wang, Yisheng Lv, Yilun Lin, Fei-Yue Wang
Summary: Traffic signal control is shifting towards proactive control, requiring an effective prediction model for controllers. This paper proposes a learning-based traffic world model that describes traffic states in image form and generates planning data for control policy optimization. Experimental results show that the model provides accurate prediction and outperforms baseline methods in optimized control policy.
FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING
(2022)
Article
Engineering, Civil
Feng Mao, Zhiheng Li, Yilun Lin, Li Li
Summary: Recent studies have attempted to apply multi-agent deep reinforcement learning (MARL) for large-scale traffic signal control but have overlooked arterial traffic signal control. This study proposes a multi-agent attention-based soft actor-critic (MASAC) model to address these issues. The MASAC method significantly outperforms existing MARL algorithms and the multiband-based method according to testing results.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Automation & Control Systems
Chen Zhao, Xingyuan Dai, Yisheng Lv, Jinglong Niu, Yilun Lin
Summary: This article examines a management architecture called decentralized/distributed autonomous operations/organizations (DAOs) that takes into account the human and social factors in transportation systems. Blockchain technology is used to ensure secure information exchange, mapping people's transportation needs from physical space to digital counterparts in cyberspace, ultimately creating the Internet of Minds (IoM). By incorporating consensus, community voting, and smart contracts into the organizational, coordination, and execution structure, reliable and prompt traffic decisions can be made using the federated intelligence of IoM. The article also provides details on operational procedures and key technologies, and showcases a case study on world model-driven cooperative signal control as a promising application of DAOs-based management in future transportation.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Editorial Material
Automation & Control Systems
Fei-Yue Wang, Qinghai Miao, Xuan Li, Xingxia Wang, Yilun Lin
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2023)
Article
Engineering, Civil
Fei-Yue Wang, Yilun Lin, Petros A. Ioannou, Ljubo Vlacic, Xiaoming Liu, Azim Eskandarian, Yisheng Lv, Xiaoxiang Na, David Cebon, Jiaqi Ma, Lingxi Li, Cristina Olaverri-Monreal
Summary: This paper provides a brief summary of the main research and findings over the last decade, identifying the main directions for the research and development of next-generation intelligent transportation systems.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Yilun Lin, Xiaoxiang Na, Ding Wang, Xingyuan Dai, Fei-Yue Wang
Summary: The logistics and transportation industry has made significant progress in sustainability, efficiency, and accessibility through the development of technologies such as clean energy, advanced algorithms, unmanned vehicles, and privacy-enhancing techniques. The Mobility 5.0 paradigm, introduced in the ITSS Intelligent Vehicle 5.0 project meeting, discusses the changes in mobility resource supply and demand and the essential components for its implementation. By integrating emerging technologies into Cyber-Physical-Social Systems (CPSS), Mobility 5.0 has the potential to shape a new era of intelligent logistics and transportation services, benefiting individuals, businesses, the government, and society as a whole.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2023)
Article
Computer Science, Artificial Intelligence
Yilun Lin, Wei Hu, Xi Chen, Shuang Li, Fei-Yue Wang
Summary: The development of smart cities aims to improve citizens' quality of life through technology and data. However, current smart city models have limitations in centralized control and lack of citizen participation. City 5.0 proposes a new paradigm that emphasizes the symbiotic relationship between humans and technology. This article presents the concept of Spatial Symbiotic Intelligence, which enables a city to dynamically respond to citizen and environmental needs through data integration and the use of decentralized autonomous organizations and parallel systems.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2023)
Article
Engineering, Civil
Chen Zhao, Xiao Wang, Yisheng Lv, Yonglin Tian, Yilun Lin, Fei-Yue Wang
Summary: This paper introduces the idea and application of using artificial intelligence technology to construct integrated transportation systems for safer, smarter, greener, and more reliable transportation services through parallel transportation and federated intelligence.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Proceedings Paper
Automation & Control Systems
Chao Guo, Tianxiang Bai, Yue Lu, Yilun Lin, Gang Xiong, Xiao Wang, Fei-Yue Wang
2020 IEEE 16TH INTERNATIONAL CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING (CASE)
(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)
