Dear Editor,This letter addresses the robust predefined-time control challenge for leaderless optimal formation in networked mobile vehicle(NMV)systems.The aim is to minimize a composite global cost function derived f...Dear Editor,This letter addresses the robust predefined-time control challenge for leaderless optimal formation in networked mobile vehicle(NMV)systems.The aim is to minimize a composite global cost function derived from individual strongly convex functions of each agent,considering both input disturbances and network communication constraints.A novel predefined-time optimal formation control(PTOFC)algorithm is presented,ensuring agent state convergence to optimal formation positions within an adjustable settling time.Through the integration of an integral sliding mode technique,disturbances are effectively countered.A representative numerical example highlights the effectiveness and robustness of the developed approach.展开更多
The real-time path optimization for heterogeneous vehicle fleets in large-scale road networks presents significant challenges due to conflicting traffic demands and imbalanced resource allocation.While existing vehicl...The real-time path optimization for heterogeneous vehicle fleets in large-scale road networks presents significant challenges due to conflicting traffic demands and imbalanced resource allocation.While existing vehicleto-infrastructure coordination frameworks partially address congestion mitigation,they often neglect priority-aware optimization and exhibit algorithmic bias toward dominant vehicle classes—critical limitations in mixed-priority scenarios involving emergency vehicles.To bridge this gap,this study proposes a preference game-theoretic coordination framework with adaptive strategy transfer protocol,explicitly balancing system-wide efficiency(measured by network throughput)with priority vehicle rights protection(quantified via time-sensitive utility functions).The approach innovatively combines(1)a multi-vehicle dynamic routing model with quantifiable preference weights,and(2)a distributed Nash equilibrium solver updated using replicator sub-dynamic models.The framework was evaluated on an urban road network containing 25 intersections with mixed priority ratios(10%–30%of vehicles with priority access demand),and the framework showed consistent benefits on four benchmarks(Social routing algorithm,Shortest path algorithm,The comprehensive path optimisation model,The emergency vehicle timing collaborative evolution path optimization method)showed consistent benefits.Results showthat across different traffic demand configurations,the proposed method reduces the average vehicle traveling time by at least 365 s,increases the road network throughput by 48.61%,and effectively balances the road loads.This approach successfully meets the diverse traffic demands of various vehicle types while optimizing road resource allocations.The proposed coordination paradigm advances theoretical foundations for fairness-aware traffic optimization while offering implementable strategies for next-generation cooperative vehicle-road systems,particularly in smart city deployments requiring mixed-priority mobility guarantees.展开更多
In this paper, with parametric uncertainties such as the mass of vehicle, the inertia of vehicle about vertical axis, and the tire cornering stiffness, we deal with the vehicle lateral control problem in intelligent v...In this paper, with parametric uncertainties such as the mass of vehicle, the inertia of vehicle about vertical axis, and the tire cornering stiffness, we deal with the vehicle lateral control problem in intelligent vehicle systems. Based on the dynamical model of vehicle, by applying Lyapunov function method, the control problem for lane keeping in the presence of parametric uncertainty is studied, the direct adaptive algorithm to compensate for parametric variations is proposed and the terminal sliding mode variable structure control laws are designed with look-ahead references systems. The stability of the system is investigated from the zero dynamics analysis. Simulation results show that convergence rates of the lateral displacement error, yaw angle error and slid angle are fast.展开更多
The lateral stability for railway vehicle dynamic system with uncertainparameters and nonlinear uncertain force vector is studied by using the Lyapunov stability theory. Arobust stability condition for the considered ...The lateral stability for railway vehicle dynamic system with uncertainparameters and nonlinear uncertain force vector is studied by using the Lyapunov stability theory. Arobust stability condition for the considered system is derived, and the obtained stability boundsare not necessarily symmetric with respect to the origin in the parameter space. The lateralstability analysis for a railway bogie model is analyzed by using the proposed approach. Thesymmetric and asymmetric results are both given and the influence of the adjustable parameter betaon the stability bounds is also discussed. With the help of the proposed method, the robuststability analysis can provide a reference for the design of the railway vehicle systems.展开更多
Human reliability analysis(HRA) is an expansion of man-machine engineering. It is also a new multidisciplinary based on behavioral science, cognitive science, information processing, system analysis and probability st...Human reliability analysis(HRA) is an expansion of man-machine engineering. It is also a new multidisciplinary based on behavioral science, cognitive science, information processing, system analysis and probability statistics in order to analyze, predict, reduce and prevent human errors. Firstly, the quantitative analysis model of HRA is proposed based on Markov process theory by using human error probability(HEP) and error correction cycle(ECC) as parameters. And human reliability evaluation criterion is built. Then, the HRA process considering error correction is proposed based on cognitive reliability and error analysis method(CREAM). Finally, according to the characteristics of armored vehicle system, common performance condition(CPC) in CREAM is improved.A reliability impact index is characterized by the overall contexts of tasks. Human reliability evaluation criterion of armored vehicle system is formulated. And the result of HRA is obtained based on the method presented in this paper. In addition, the relative weights are estimated by combining scale of 10/10—18/2 and analytical hierarchy process(AHP), and the triangular fuzzy number considering confidence factor and optimism index is adopted in order to reduce the subjectivity. The analysis results show that the method presented in this paper is reasonable and feasible. Meantime, the method can provide guidance for human reliability analysis of other weapon systems.展开更多
Automobile accidents are one of the leading causes of death worldwide. Every year, over 1.24 million people are killed in traffic accidents. Even though automobiles are designed to help people, they have been used to ...Automobile accidents are one of the leading causes of death worldwide. Every year, over 1.24 million people are killed in traffic accidents. Even though automobiles are designed to help people, they have been used to kill them in large numbers. Automobile accident research has primarily focused on past tragedies to develop and implement policies to combat this pandemic. The aim of this systematic review is to assess the different methods used to investigate the vehicle system-related cause factors of road traffic accidents. Police report reports have served as a foundation for providing historical facts about the causes of automobile accidents. It has been observed that police reports have limitations when it comes to reporting the involvement of vehicle systems in causing a traffic accident. The majority of the research was conducted on articles that investigated vehicle system risk factors using statistical data. Following articles that used statistical data to investigate vehicle system risk factors, the inclusion criteria were chosen. Articles on traffic accidents published in Cameroon were included on the condition that they studied at least one traffic accident risk factor. Two hundred twenty-five distinct records were identified, and 155 full texts were screened for inclusion, resulting in the inclusion of 25 studies in the review. According to the findings, failure to break the braking system, tyre puncture, poor driving, speeding, and overtaking are the leading causes of automobile crash reports reported by police. The majority of the study’s conclusions lamented that accusing vehicle systems was based on assumptions and the reporter’s judgment. It was determined that the use of stringent vetting procedures to investigate vehicle systems is the cause of a traffic accident. As a result, stakeholders will require accurate facts from a traffic crash investigation.展开更多
The non-linear wheel-rail motional model is the first research breakthrough I have made in the field of vehicle system dynamics. The main external interference to a vehicle system in rail-borne transportation comes fr...The non-linear wheel-rail motional model is the first research breakthrough I have made in the field of vehicle system dynamics. The main external interference to a vehicle system in rail-borne transportation comes from the dynamic interaction between the wheel and the rail. To determine the forces exerted on the rail-contacting patches of a railcar is known to be one of the most complicated problems in rail haulage, expecially in its unsaturated state, i.e. before overall sliding occurs. Since the 1960s, many scholars, including K.L. Johnson and J.J.Kalker, have considered it a problem in rolling contact mechanics. However, none of the presented展开更多
The tilt rotor unmanned aerial vehicle（TRUAV） exhibits special application value due to its unique rotor structure. However, varying dynamics and aerodynamic interference caused by tiltable rotors are great technica...The tilt rotor unmanned aerial vehicle（TRUAV） exhibits special application value due to its unique rotor structure. However, varying dynamics and aerodynamic interference caused by tiltable rotors are great technical challenges and key issues for TRUAV＇s high-powered flight controls, which have attracted the attention of many researchers. This paper outlines the concept of TRUAV and some typical TRUAV platforms while focusing on control techniques. TRUAV structural features, dynamics modeling, and flight control methods are discussed, and major challenges and corresponding developmental tendencies associated with TRUAV flight control are summarized.展开更多
With the increasing complexity of logistics operations,traditional static vehicle routing models are no longer sufficient.In practice,customer demands often arise dynamically,and multi-depot systems are commonly used ...With the increasing complexity of logistics operations,traditional static vehicle routing models are no longer sufficient.In practice,customer demands often arise dynamically,and multi-depot systems are commonly used to improve efficiency.This paper first introduces a vehicle routing problem with the goal of minimizing operating costs in a multi-depot environment with dynamic demand.New customers appear in the delivery process at any time and are periodically optimized according to time slices.Then,we propose a scheduling system TS-DPU based on an improved ant colony algorithm TS-ACO to solve this problem.The classical ant colony algorithm uses spatial distance to select nodes,while TS-ACO considers the impact of both temporal and spatial distance on node selection.Meanwhile,we adopt Cordeau’s Multi-Depot Vehicle Routing Problem with Time Windows(MDVRPTW)dataset to evaluate the performance of our system.According to the experimental results,TS-ACO,which considers spatial and temporal distance,is more effective than the classical ACO,which only considers spatial distance.展开更多
Traffic at urban intersections frequently encounters unexpected obstructions,resulting in congestion due to uncooperative and priority-based driving behavior.This paper presents an optimal right-turn coordination syst...Traffic at urban intersections frequently encounters unexpected obstructions,resulting in congestion due to uncooperative and priority-based driving behavior.This paper presents an optimal right-turn coordination system for Connected and Automated Vehicles(CAVs)at single-lane intersections,particularly in the context of left-hand side driving on roads.The goal is to facilitate smooth right turns for certain vehicles without creating bottlenecks.We consider that all approaching vehicles share relevant information through vehicular communications.The Intersection Coordination Unit(ICU)processes this information and communicates the optimal crossing or turning times to the vehicles.The primary objective of this coordination is to minimize overall traffic delays,which also helps improve the fuel consumption of vehicles.By considering information from upcoming vehicles at the intersection,the coordination system solves an optimization problem to determine the best timing for executing right turns,ultimately minimizing the total delay for all vehicles.The proposed coordination system is evaluated at a typical urban intersection,and its performance is compared to traditional traffic systems.Numerical simulation results indicate that the proposed coordination system significantly enhances the average traffic speed and fuel consumption compared to the traditional traffic system in various scenarios.展开更多
Dear Editor,This letter proposes a convex optimization-based model predictive control(MPC)autonomous guidance method for the Mars ascent vehicle(MAV).We use the modified chebyshev-picard iteration(MCPI)to solve optimi...Dear Editor,This letter proposes a convex optimization-based model predictive control(MPC)autonomous guidance method for the Mars ascent vehicle(MAV).We use the modified chebyshev-picard iteration(MCPI)to solve optimization sub-problems within the MPC framework,eliminating the dynamic constraints in solving the optimal control problem and enhancing the convergence performance of the algorithm.Moreover,this method can repeatedly perform trajectory optimization calculations at a high frequency,achieving timely correction of the optimal control command.Numerical simulations demonstrate that the method can satisfy the requirements of rapid computation and reliability for the MAV system when considering uncertainties and perturbations.展开更多
This study observes the process of strategy building and capability accumulation of companies in the currently booming Chinese electric vehicles(EV)1 market from the perspective of business ecosystems.While examining ...This study observes the process of strategy building and capability accumulation of companies in the currently booming Chinese electric vehicles(EV)1 market from the perspective of business ecosystems.While examining the internal and external factors of the formation about the Chinese EV industry business ecosystem,such as industrial structure transformation,technology transfer,government policies,and corporate competition,with the platform theory,I analyze the growth strategies and competitiveness of Chinese companies,particularly BYD Co.,Ltd.(BYD),which has risen to the top of the world in EV completed vehicles,and Contemporary Amperex Technology Co.,Ltd.(CATL),which has risen to the top of the world in electric vehicle batteries(EVB)2.BYD and CATL have gained competitive advantages by utilizing the distinctive management resources,which have accumulated over the years to build platforms for EVBs and EVs in response to changes in the external environment,and have actively developed their platform strategies.展开更多
Current treatments for glioblastoma face challenges such as the blood-brain barrier and lack of targeted therapy,compounded by the aggressive nature,high invasiveness,and heterogeneity of the disease.Exosomes,a subtyp...Current treatments for glioblastoma face challenges such as the blood-brain barrier and lack of targeted therapy,compounded by the aggressive nature,high invasiveness,and heterogeneity of the disease.Exosomes,a subtype of extracellular vesicles are emerging as promising nanocarrier drug delivery systems to address these limitations.Exosomes released by all cell types can be easily obtained and modified as delivery vehicles or therapeutic agents.A systematic review was conducted to evaluate various methods for exosome isolation,characterization,engineering or modification,drug loading and delivery efficiency,including exosome biodistribution and treatment efficacy.A search of four databases for in vitro and in vivo studies(2000–,2023)identified 6165 records,of which 23 articles were found eligible and included for analyses.Most studies applied ultracentrifugation(UC)for exosomes isolation.Cancer cell lines being the most frequently used source of exosomes,followed by stem cells.The incubation approach was predominantly utilized to modify exosomes for drug loading.In vivo analysis showed that exosome biodistribution was primarily concentrated in the brain region,peaking in the first 6 h and remained moderately high.Compared to native exosomes and untreated control groups,utilizing modified native exosomes(cargo loaded)for treating glioblastoma disease models led to more pronounced suppression of tumor growth and proliferation,enhanced stimulation of immune response and apoptosis,effective restoration of drug chemosensitivity,increased anti-tumor effect and prolonged survival rates.Modified exosomes whether through incubation,sonication,transfection,freeze-thawing or their combination,improve targeted delivery and therapeutic efficacy against glioblastoma.展开更多
Transportation of heavy loads is often performed by multi-axle multi-steered heavy duty vehicles In this article a novel nonlinear optimal control method is applied to the kinematic model of the five-axle and three-st...Transportation of heavy loads is often performed by multi-axle multi-steered heavy duty vehicles In this article a novel nonlinear optimal control method is applied to the kinematic model of the five-axle and three-steering coupled vehicle system.First,it is proven that the dynamic model of this articulated multi-vehicle system is differentially flat.Next.the state-space model of the five-axle and three-steering vehicle system undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method.The linearization is based on Taylor series expansion and on the associated Jacobian matrices.For the linearized state-space model of the five-axle and three-steering vehicle system a stabilizing optimal(H-infinity)feedback controller is designed.This controller stands for the solution of the nonlinear optimal control problem under model uncertainty and external perturbations.To compute the controller’s feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm.The stability properties of the control method are proven through Lyapunov analysis.The proposed nonlinear optimal control approach achieves fast and accurate tracking of setpoints under moderate variations of the control inputs and minimal dispersion of energy by the propulsion and steering system of the five-axle and three-steering vehicle system.展开更多
As an essential element of intelligent trans-port systems,Internet of vehicles(IoV)has brought an immersive user experience recently.Meanwhile,the emergence of mobile edge computing(MEC)has enhanced the computational ...As an essential element of intelligent trans-port systems,Internet of vehicles(IoV)has brought an immersive user experience recently.Meanwhile,the emergence of mobile edge computing(MEC)has enhanced the computational capability of the vehicle which reduces task processing latency and power con-sumption effectively and meets the quality of service requirements of vehicle users.However,there are still some problems in the MEC-assisted IoV system such as poor connectivity and high cost.Unmanned aerial vehicles(UAVs)equipped with MEC servers have become a promising approach for providing com-munication and computing services to mobile vehi-cles.Hence,in this article,an optimal framework for the UAV-assisted MEC system for IoV to minimize the average system cost is presented.Through joint consideration of computational offloading decisions and computational resource allocation,the optimiza-tion problem of our proposed architecture is presented to reduce system energy consumption and delay.For purpose of tackling this issue,the original non-convex issue is converted into a convex issue and the alternat-ing direction method of multipliers-based distributed optimal scheme is developed.The simulation results illustrate that the presented scheme can enhance the system performance dramatically with regard to other schemes,and the convergence of the proposed scheme is also significant.展开更多
The development of chassis active safety control technology has improved vehicle stability under extreme conditions.However,its cross-system and multi-functional characteristics make the controller difficult to achiev...The development of chassis active safety control technology has improved vehicle stability under extreme conditions.However,its cross-system and multi-functional characteristics make the controller difficult to achieve cooperative goals.In addition,the chassis system,which has high complexity,numerous subsystems,and strong coupling,will also lead to low computing efficiency and poor control effect of the controller.Therefore,this paper proposes a scenario-driven hybrid distributed model predictive control algorithm with variable control topology.This algorithm divides multiple stability regions based on the vehicle’s β−γ phase plane,forming a mapping relationship between the control structure and the vehicle’s state.A control input fusion mechanism within the transition domain is designed to mitigate the problems of system state oscillation and control input jitter caused by switching control structures.Then,a distributed state-space equation with state coupling and input coupling characteristics is constructed,and a weighted local agent cost function in quadratic programming is derived.Through cost coupling,local agents can coordinate global performance goals.Finally,through Simulink/CarSim joint simulation and hardware-in-the-loop(HIL)test,the proposed algorithm is validated to improve vehicle stability while ensuring trajectory tracking accuracy and has good applicability for multi-objective coordinated control.This paper combines the advantages of distributed MPC and decentralized MPC,achieving a balance between approximating the global optimal results and the solution’s efficiency.展开更多
This article focuses on the remote diagnosis and analysis of rail vehicle status based on the data of the Train Control Management System(TCMS).It first expounds on the importance of train diagnostic analysis and desi...This article focuses on the remote diagnosis and analysis of rail vehicle status based on the data of the Train Control Management System(TCMS).It first expounds on the importance of train diagnostic analysis and designs a unified TCMS data frame transmission format.Subsequently,a remote data transmission link using 4G signals and data processing methods is introduced.The advantages of remote diagnosis are analyzed,and common methods such as correlation analysis,fault diagnosis,and fault prediction are explained in detail.Then,challenges such as data security and the balance between diagnostic accuracy and real-time performance are discussed,along with development prospects in technological innovation,algorithm optimization,and application promotion.This research provides ideas for remote analysis and diagnosis based on TCMS data,contributing to the safe and efficient operation of rail vehicles.展开更多
Electric Vehicle Charging Systems(EVCS)are increasingly vulnerable to cybersecurity threats as they integrate deeply into smart grids and Internet ofThings(IoT)environments,raising significant security challenges.Most...Electric Vehicle Charging Systems(EVCS)are increasingly vulnerable to cybersecurity threats as they integrate deeply into smart grids and Internet ofThings(IoT)environments,raising significant security challenges.Most existing research primarily emphasizes network-level anomaly detection,leaving critical vulnerabilities at the host level underexplored.This study introduces a novel forensic analysis framework leveraging host-level data,including system logs,kernel events,and Hardware Performance Counters(HPC),to detect and analyze sophisticated cyberattacks such as cryptojacking,Denial-of-Service(DoS),and reconnaissance activities targeting EVCS.Using comprehensive forensic analysis and machine learning models,the proposed framework significantly outperforms existing methods,achieving an accuracy of 98.81%.The findings offer insights into distinct behavioral signatures associated with specific cyber threats,enabling improved cybersecurity strategies and actionable recommendations for robust EVCS infrastructure protection.展开更多
The exploration of unmanned aerial vehicle(UAV)swarm systems represents a focal point in the research of multiagent systems,with the investigation of their fission-fusion behavior holding significant theoretical and p...The exploration of unmanned aerial vehicle(UAV)swarm systems represents a focal point in the research of multiagent systems,with the investigation of their fission-fusion behavior holding significant theoretical and practical value.This review systematically examines the methods for fission-fusion of UAV swarms from the perspective of multi-agent systems,encompassing the composition of UAV swarm systems and fission-fusion conditions,information interaction mechanisms,and existing fission-fusion approaches.Firstly,considering the constituent units of UAV swarms and the conditions influencing fission-fusion,this paper categorizes and introduces the UAV swarm systems.It further examines the effects and limitations of fission-fusion methods across various categories and conditions.Secondly,a comprehensive analysis of the prevalent information interaction mechanisms within UAV swarms is conducted from the perspective of information interaction structures.The advantages and limitations of various mechanisms in the context of fission-fusion behaviors are summarized and synthesized.Thirdly,this paper consolidates the existing implementation research findings related to the fission-fusion behavior of UAV swarms,identifies unresolved issues in fission-fusion research,and discusses potential solutions.Finally,the paper concludes with a comprehensive summary and systematically outlines future research opportunities.展开更多
With the widespread adoption of automated guided vehicle(AGV)systems for material handling in manufacturing plants,it has become practical and crucial to delve into the layout problem associated with AGV systems.In th...With the widespread adoption of automated guided vehicle(AGV)systems for material handling in manufacturing plants,it has become practical and crucial to delve into the layout problem associated with AGV systems.In this work,we focus on a unique layout problem encountered in a hybrid workshop where AGV systems are employed for transporting semiproducts along the manufacturing line.Several distinctive features in this system contribute to the challenge of the problem.Notably,manufacturing occurs in an uncertain environment,and certain manufacturing cells may produce semiproducts that do not meet quality standards,necessitating repair.Additionally,each AGV requires recharging in a designated area within the workshop.Given that the proposed layout problem is NP-hard,we present an intelligence variable neighborhood search heuristic integrated with a constraint relaxation strategy to address its complexity.The numerical results demonstrate the algorithm's ability to generate high-quality solutions within a reasonable timeframe,even for large-scale test instances.The layout solutions obtained through our algorithm outperform those produced by the CPLEX solver and the practical layouts devised by the company.This highlights the efficacy of our approach in tackling the unique challenges posed by the layout problem in a hybrid workshop with an AGV system.展开更多
基金supported by the National Natural Science Foundation of China(62373162,U24A20268,624B2055)the Shenzhen Science and Technology Program(JCYJ 20240813114007010)the Knowledge Innovation Program of Wuhan-Basic Research(2023010201010100).
文摘Dear Editor,This letter addresses the robust predefined-time control challenge for leaderless optimal formation in networked mobile vehicle(NMV)systems.The aim is to minimize a composite global cost function derived from individual strongly convex functions of each agent,considering both input disturbances and network communication constraints.A novel predefined-time optimal formation control(PTOFC)algorithm is presented,ensuring agent state convergence to optimal formation positions within an adjustable settling time.Through the integration of an integral sliding mode technique,disturbances are effectively countered.A representative numerical example highlights the effectiveness and robustness of the developed approach.
基金funded by the National Key Research and Development Program Project 2022YFB4300404.
文摘The real-time path optimization for heterogeneous vehicle fleets in large-scale road networks presents significant challenges due to conflicting traffic demands and imbalanced resource allocation.While existing vehicleto-infrastructure coordination frameworks partially address congestion mitigation,they often neglect priority-aware optimization and exhibit algorithmic bias toward dominant vehicle classes—critical limitations in mixed-priority scenarios involving emergency vehicles.To bridge this gap,this study proposes a preference game-theoretic coordination framework with adaptive strategy transfer protocol,explicitly balancing system-wide efficiency(measured by network throughput)with priority vehicle rights protection(quantified via time-sensitive utility functions).The approach innovatively combines(1)a multi-vehicle dynamic routing model with quantifiable preference weights,and(2)a distributed Nash equilibrium solver updated using replicator sub-dynamic models.The framework was evaluated on an urban road network containing 25 intersections with mixed priority ratios(10%–30%of vehicles with priority access demand),and the framework showed consistent benefits on four benchmarks(Social routing algorithm,Shortest path algorithm,The comprehensive path optimisation model,The emergency vehicle timing collaborative evolution path optimization method)showed consistent benefits.Results showthat across different traffic demand configurations,the proposed method reduces the average vehicle traveling time by at least 365 s,increases the road network throughput by 48.61%,and effectively balances the road loads.This approach successfully meets the diverse traffic demands of various vehicle types while optimizing road resource allocations.The proposed coordination paradigm advances theoretical foundations for fairness-aware traffic optimization while offering implementable strategies for next-generation cooperative vehicle-road systems,particularly in smart city deployments requiring mixed-priority mobility guarantees.
基金Sponsored by the National Natural Science Foundation of China(Grant No.10772152)
文摘In this paper, with parametric uncertainties such as the mass of vehicle, the inertia of vehicle about vertical axis, and the tire cornering stiffness, we deal with the vehicle lateral control problem in intelligent vehicle systems. Based on the dynamical model of vehicle, by applying Lyapunov function method, the control problem for lane keeping in the presence of parametric uncertainty is studied, the direct adaptive algorithm to compensate for parametric variations is proposed and the terminal sliding mode variable structure control laws are designed with look-ahead references systems. The stability of the system is investigated from the zero dynamics analysis. Simulation results show that convergence rates of the lateral displacement error, yaw angle error and slid angle are fast.
基金This project is supported by National Natural Science Foundation of China (No.50175094)Excellent PhD Dissertation Foundation of Ministry of Education, China (No.200048).
文摘The lateral stability for railway vehicle dynamic system with uncertainparameters and nonlinear uncertain force vector is studied by using the Lyapunov stability theory. Arobust stability condition for the considered system is derived, and the obtained stability boundsare not necessarily symmetric with respect to the origin in the parameter space. The lateralstability analysis for a railway bogie model is analyzed by using the proposed approach. Thesymmetric and asymmetric results are both given and the influence of the adjustable parameter betaon the stability bounds is also discussed. With the help of the proposed method, the robuststability analysis can provide a reference for the design of the railway vehicle systems.
基金the Technical Basis Projects of China’s Ministry of Industry and Information Technology(No.ZQ092012B003)
文摘Human reliability analysis(HRA) is an expansion of man-machine engineering. It is also a new multidisciplinary based on behavioral science, cognitive science, information processing, system analysis and probability statistics in order to analyze, predict, reduce and prevent human errors. Firstly, the quantitative analysis model of HRA is proposed based on Markov process theory by using human error probability(HEP) and error correction cycle(ECC) as parameters. And human reliability evaluation criterion is built. Then, the HRA process considering error correction is proposed based on cognitive reliability and error analysis method(CREAM). Finally, according to the characteristics of armored vehicle system, common performance condition(CPC) in CREAM is improved.A reliability impact index is characterized by the overall contexts of tasks. Human reliability evaluation criterion of armored vehicle system is formulated. And the result of HRA is obtained based on the method presented in this paper. In addition, the relative weights are estimated by combining scale of 10/10—18/2 and analytical hierarchy process(AHP), and the triangular fuzzy number considering confidence factor and optimism index is adopted in order to reduce the subjectivity. The analysis results show that the method presented in this paper is reasonable and feasible. Meantime, the method can provide guidance for human reliability analysis of other weapon systems.
文摘Automobile accidents are one of the leading causes of death worldwide. Every year, over 1.24 million people are killed in traffic accidents. Even though automobiles are designed to help people, they have been used to kill them in large numbers. Automobile accident research has primarily focused on past tragedies to develop and implement policies to combat this pandemic. The aim of this systematic review is to assess the different methods used to investigate the vehicle system-related cause factors of road traffic accidents. Police report reports have served as a foundation for providing historical facts about the causes of automobile accidents. It has been observed that police reports have limitations when it comes to reporting the involvement of vehicle systems in causing a traffic accident. The majority of the research was conducted on articles that investigated vehicle system risk factors using statistical data. Following articles that used statistical data to investigate vehicle system risk factors, the inclusion criteria were chosen. Articles on traffic accidents published in Cameroon were included on the condition that they studied at least one traffic accident risk factor. Two hundred twenty-five distinct records were identified, and 155 full texts were screened for inclusion, resulting in the inclusion of 25 studies in the review. According to the findings, failure to break the braking system, tyre puncture, poor driving, speeding, and overtaking are the leading causes of automobile crash reports reported by police. The majority of the study’s conclusions lamented that accusing vehicle systems was based on assumptions and the reporter’s judgment. It was determined that the use of stringent vetting procedures to investigate vehicle systems is the cause of a traffic accident. As a result, stakeholders will require accurate facts from a traffic crash investigation.
文摘The non-linear wheel-rail motional model is the first research breakthrough I have made in the field of vehicle system dynamics. The main external interference to a vehicle system in rail-borne transportation comes from the dynamic interaction between the wheel and the rail. To determine the forces exerted on the rail-contacting patches of a railcar is known to be one of the most complicated problems in rail haulage, expecially in its unsaturated state, i.e. before overall sliding occurs. Since the 1960s, many scholars, including K.L. Johnson and J.J.Kalker, have considered it a problem in rolling contact mechanics. However, none of the presented
基金co-supported by the National Natural Science Foundation of China (Nos. 61503369 and 61433016)
文摘The tilt rotor unmanned aerial vehicle（TRUAV） exhibits special application value due to its unique rotor structure. However, varying dynamics and aerodynamic interference caused by tiltable rotors are great technical challenges and key issues for TRUAV＇s high-powered flight controls, which have attracted the attention of many researchers. This paper outlines the concept of TRUAV and some typical TRUAV platforms while focusing on control techniques. TRUAV structural features, dynamics modeling, and flight control methods are discussed, and major challenges and corresponding developmental tendencies associated with TRUAV flight control are summarized.
基金supported by the Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology.
文摘With the increasing complexity of logistics operations,traditional static vehicle routing models are no longer sufficient.In practice,customer demands often arise dynamically,and multi-depot systems are commonly used to improve efficiency.This paper first introduces a vehicle routing problem with the goal of minimizing operating costs in a multi-depot environment with dynamic demand.New customers appear in the delivery process at any time and are periodically optimized according to time slices.Then,we propose a scheduling system TS-DPU based on an improved ant colony algorithm TS-ACO to solve this problem.The classical ant colony algorithm uses spatial distance to select nodes,while TS-ACO considers the impact of both temporal and spatial distance on node selection.Meanwhile,we adopt Cordeau’s Multi-Depot Vehicle Routing Problem with Time Windows(MDVRPTW)dataset to evaluate the performance of our system.According to the experimental results,TS-ACO,which considers spatial and temporal distance,is more effective than the classical ACO,which only considers spatial distance.
基金supported by the Japan Society for the Promotion of Science(JSPS)Grants-in-Aid for Scientific Research(C)23K03898.
文摘Traffic at urban intersections frequently encounters unexpected obstructions,resulting in congestion due to uncooperative and priority-based driving behavior.This paper presents an optimal right-turn coordination system for Connected and Automated Vehicles(CAVs)at single-lane intersections,particularly in the context of left-hand side driving on roads.The goal is to facilitate smooth right turns for certain vehicles without creating bottlenecks.We consider that all approaching vehicles share relevant information through vehicular communications.The Intersection Coordination Unit(ICU)processes this information and communicates the optimal crossing or turning times to the vehicles.The primary objective of this coordination is to minimize overall traffic delays,which also helps improve the fuel consumption of vehicles.By considering information from upcoming vehicles at the intersection,the coordination system solves an optimization problem to determine the best timing for executing right turns,ultimately minimizing the total delay for all vehicles.The proposed coordination system is evaluated at a typical urban intersection,and its performance is compared to traditional traffic systems.Numerical simulation results indicate that the proposed coordination system significantly enhances the average traffic speed and fuel consumption compared to the traditional traffic system in various scenarios.
基金supported by the National Defense Basic Scientific Research Program(JCKY2021603B030)the National Natural Science Foundation of China(62273118,12150008)the Natural Science Foundation of Heilongjiang Province(LH2022F023).
文摘Dear Editor,This letter proposes a convex optimization-based model predictive control(MPC)autonomous guidance method for the Mars ascent vehicle(MAV).We use the modified chebyshev-picard iteration(MCPI)to solve optimization sub-problems within the MPC framework,eliminating the dynamic constraints in solving the optimal control problem and enhancing the convergence performance of the algorithm.Moreover,this method can repeatedly perform trajectory optimization calculations at a high frequency,achieving timely correction of the optimal control command.Numerical simulations demonstrate that the method can satisfy the requirements of rapid computation and reliability for the MAV system when considering uncertainties and perturbations.
文摘This study observes the process of strategy building and capability accumulation of companies in the currently booming Chinese electric vehicles(EV)1 market from the perspective of business ecosystems.While examining the internal and external factors of the formation about the Chinese EV industry business ecosystem,such as industrial structure transformation,technology transfer,government policies,and corporate competition,with the platform theory,I analyze the growth strategies and competitiveness of Chinese companies,particularly BYD Co.,Ltd.(BYD),which has risen to the top of the world in EV completed vehicles,and Contemporary Amperex Technology Co.,Ltd.(CATL),which has risen to the top of the world in electric vehicle batteries(EVB)2.BYD and CATL have gained competitive advantages by utilizing the distinctive management resources,which have accumulated over the years to build platforms for EVBs and EVs in response to changes in the external environment,and have actively developed their platform strategies.
基金supported by the Bridging Grant from Universiti Sains Malaysia (R501LR-RND003–0000001319–0000)funding through the Fundamental Research Grant Scheme (FRGS/1/2020/TK0/USM/02/32–6171275) awarded by the Ministry of Higher Education Malaysia
文摘Current treatments for glioblastoma face challenges such as the blood-brain barrier and lack of targeted therapy,compounded by the aggressive nature,high invasiveness,and heterogeneity of the disease.Exosomes,a subtype of extracellular vesicles are emerging as promising nanocarrier drug delivery systems to address these limitations.Exosomes released by all cell types can be easily obtained and modified as delivery vehicles or therapeutic agents.A systematic review was conducted to evaluate various methods for exosome isolation,characterization,engineering or modification,drug loading and delivery efficiency,including exosome biodistribution and treatment efficacy.A search of four databases for in vitro and in vivo studies(2000–,2023)identified 6165 records,of which 23 articles were found eligible and included for analyses.Most studies applied ultracentrifugation(UC)for exosomes isolation.Cancer cell lines being the most frequently used source of exosomes,followed by stem cells.The incubation approach was predominantly utilized to modify exosomes for drug loading.In vivo analysis showed that exosome biodistribution was primarily concentrated in the brain region,peaking in the first 6 h and remained moderately high.Compared to native exosomes and untreated control groups,utilizing modified native exosomes(cargo loaded)for treating glioblastoma disease models led to more pronounced suppression of tumor growth and proliferation,enhanced stimulation of immune response and apoptosis,effective restoration of drug chemosensitivity,increased anti-tumor effect and prolonged survival rates.Modified exosomes whether through incubation,sonication,transfection,freeze-thawing or their combination,improve targeted delivery and therapeutic efficacy against glioblastoma.
文摘Transportation of heavy loads is often performed by multi-axle multi-steered heavy duty vehicles In this article a novel nonlinear optimal control method is applied to the kinematic model of the five-axle and three-steering coupled vehicle system.First,it is proven that the dynamic model of this articulated multi-vehicle system is differentially flat.Next.the state-space model of the five-axle and three-steering vehicle system undergoes approximate linearization around a temporary operating point that is recomputed at each time-step of the control method.The linearization is based on Taylor series expansion and on the associated Jacobian matrices.For the linearized state-space model of the five-axle and three-steering vehicle system a stabilizing optimal(H-infinity)feedback controller is designed.This controller stands for the solution of the nonlinear optimal control problem under model uncertainty and external perturbations.To compute the controller’s feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm.The stability properties of the control method are proven through Lyapunov analysis.The proposed nonlinear optimal control approach achieves fast and accurate tracking of setpoints under moderate variations of the control inputs and minimal dispersion of energy by the propulsion and steering system of the five-axle and three-steering vehicle system.
基金in part by the National Natural Science Foundation of China(NSFC)under Grant 62371012in part by the Beijing Natural Science Foundation under Grant 4252001.
文摘As an essential element of intelligent trans-port systems,Internet of vehicles(IoV)has brought an immersive user experience recently.Meanwhile,the emergence of mobile edge computing(MEC)has enhanced the computational capability of the vehicle which reduces task processing latency and power con-sumption effectively and meets the quality of service requirements of vehicle users.However,there are still some problems in the MEC-assisted IoV system such as poor connectivity and high cost.Unmanned aerial vehicles(UAVs)equipped with MEC servers have become a promising approach for providing com-munication and computing services to mobile vehi-cles.Hence,in this article,an optimal framework for the UAV-assisted MEC system for IoV to minimize the average system cost is presented.Through joint consideration of computational offloading decisions and computational resource allocation,the optimiza-tion problem of our proposed architecture is presented to reduce system energy consumption and delay.For purpose of tackling this issue,the original non-convex issue is converted into a convex issue and the alternat-ing direction method of multipliers-based distributed optimal scheme is developed.The simulation results illustrate that the presented scheme can enhance the system performance dramatically with regard to other schemes,and the convergence of the proposed scheme is also significant.
基金Supported by National Natural Science Foundation of China(Grant Nos.52225212,52272418,U22A20100)National Key Research and Development Program of China(Grant No.2022YFB2503302).
文摘The development of chassis active safety control technology has improved vehicle stability under extreme conditions.However,its cross-system and multi-functional characteristics make the controller difficult to achieve cooperative goals.In addition,the chassis system,which has high complexity,numerous subsystems,and strong coupling,will also lead to low computing efficiency and poor control effect of the controller.Therefore,this paper proposes a scenario-driven hybrid distributed model predictive control algorithm with variable control topology.This algorithm divides multiple stability regions based on the vehicle’s β−γ phase plane,forming a mapping relationship between the control structure and the vehicle’s state.A control input fusion mechanism within the transition domain is designed to mitigate the problems of system state oscillation and control input jitter caused by switching control structures.Then,a distributed state-space equation with state coupling and input coupling characteristics is constructed,and a weighted local agent cost function in quadratic programming is derived.Through cost coupling,local agents can coordinate global performance goals.Finally,through Simulink/CarSim joint simulation and hardware-in-the-loop(HIL)test,the proposed algorithm is validated to improve vehicle stability while ensuring trajectory tracking accuracy and has good applicability for multi-objective coordinated control.This paper combines the advantages of distributed MPC and decentralized MPC,achieving a balance between approximating the global optimal results and the solution’s efficiency.
文摘This article focuses on the remote diagnosis and analysis of rail vehicle status based on the data of the Train Control Management System(TCMS).It first expounds on the importance of train diagnostic analysis and designs a unified TCMS data frame transmission format.Subsequently,a remote data transmission link using 4G signals and data processing methods is introduced.The advantages of remote diagnosis are analyzed,and common methods such as correlation analysis,fault diagnosis,and fault prediction are explained in detail.Then,challenges such as data security and the balance between diagnostic accuracy and real-time performance are discussed,along with development prospects in technological innovation,algorithm optimization,and application promotion.This research provides ideas for remote analysis and diagnosis based on TCMS data,contributing to the safe and efficient operation of rail vehicles.
文摘Electric Vehicle Charging Systems(EVCS)are increasingly vulnerable to cybersecurity threats as they integrate deeply into smart grids and Internet ofThings(IoT)environments,raising significant security challenges.Most existing research primarily emphasizes network-level anomaly detection,leaving critical vulnerabilities at the host level underexplored.This study introduces a novel forensic analysis framework leveraging host-level data,including system logs,kernel events,and Hardware Performance Counters(HPC),to detect and analyze sophisticated cyberattacks such as cryptojacking,Denial-of-Service(DoS),and reconnaissance activities targeting EVCS.Using comprehensive forensic analysis and machine learning models,the proposed framework significantly outperforms existing methods,achieving an accuracy of 98.81%.The findings offer insights into distinct behavioral signatures associated with specific cyber threats,enabling improved cybersecurity strategies and actionable recommendations for robust EVCS infrastructure protection.
基金supported by the National Natural Science Foundation of China(U20B2042).
文摘The exploration of unmanned aerial vehicle(UAV)swarm systems represents a focal point in the research of multiagent systems,with the investigation of their fission-fusion behavior holding significant theoretical and practical value.This review systematically examines the methods for fission-fusion of UAV swarms from the perspective of multi-agent systems,encompassing the composition of UAV swarm systems and fission-fusion conditions,information interaction mechanisms,and existing fission-fusion approaches.Firstly,considering the constituent units of UAV swarms and the conditions influencing fission-fusion,this paper categorizes and introduces the UAV swarm systems.It further examines the effects and limitations of fission-fusion methods across various categories and conditions.Secondly,a comprehensive analysis of the prevalent information interaction mechanisms within UAV swarms is conducted from the perspective of information interaction structures.The advantages and limitations of various mechanisms in the context of fission-fusion behaviors are summarized and synthesized.Thirdly,this paper consolidates the existing implementation research findings related to the fission-fusion behavior of UAV swarms,identifies unresolved issues in fission-fusion research,and discusses potential solutions.Finally,the paper concludes with a comprehensive summary and systematically outlines future research opportunities.
文摘With the widespread adoption of automated guided vehicle(AGV)systems for material handling in manufacturing plants,it has become practical and crucial to delve into the layout problem associated with AGV systems.In this work,we focus on a unique layout problem encountered in a hybrid workshop where AGV systems are employed for transporting semiproducts along the manufacturing line.Several distinctive features in this system contribute to the challenge of the problem.Notably,manufacturing occurs in an uncertain environment,and certain manufacturing cells may produce semiproducts that do not meet quality standards,necessitating repair.Additionally,each AGV requires recharging in a designated area within the workshop.Given that the proposed layout problem is NP-hard,we present an intelligence variable neighborhood search heuristic integrated with a constraint relaxation strategy to address its complexity.The numerical results demonstrate the algorithm's ability to generate high-quality solutions within a reasonable timeframe,even for large-scale test instances.The layout solutions obtained through our algorithm outperform those produced by the CPLEX solver and the practical layouts devised by the company.This highlights the efficacy of our approach in tackling the unique challenges posed by the layout problem in a hybrid workshop with an AGV system.
