Many efforts have been devoted to efficient task scheduling in Multi-Unmanned Aerial Vehicle(UAV)edge computing.However,the heterogeneity of UAV computation resource,and the task re-allocating between UAVs have not be...Many efforts have been devoted to efficient task scheduling in Multi-Unmanned Aerial Vehicle(UAV)edge computing.However,the heterogeneity of UAV computation resource,and the task re-allocating between UAVs have not been fully considered yet.Moreover,most existing works neglect the fact that a task can only be executed on the UAV equipped with its desired service function(SF).In this backdrop,this paper formulates the task scheduling problem as a multi-objective task scheduling problem,which aims at maximizing the task execution success ratio while minimizing the average weighted sum of all tasks’completion time and energy consumption.Optimizing three coupled goals in a realtime manner with the dynamic arrival of tasks hinders us from adopting existing methods,like machine learning-based solutions that require a long training time and tremendous pre-knowledge about the task arrival process,or heuristic-based ones that usually incur a long decision-making time.To tackle this problem in a distributed manner,we establish a matching theory framework,in which three conflicting goals are treated as the preferences of tasks,SFs and UAVs.Then,a Distributed Matching Theory-based Re-allocating(DiMaToRe)algorithm is put forward.We formally proved that a stable matching can be achieved by our proposal.Extensive simulation results show that Di Ma To Re algorithm outperforms benchmark algorithms under diverse parameter settings and has good robustness.展开更多
In order to solve the problem the existing vertical handoff algorithms of vehicle heterogeneous wireless network do not consider the diversification of network's status, an optimized vertical handoff algorithm bas...In order to solve the problem the existing vertical handoff algorithms of vehicle heterogeneous wireless network do not consider the diversification of network's status, an optimized vertical handoff algorithm based on markov process is proposed and discussed in this paper. This algorithm takes into account that the status transformation of available network will affect the quality of service(Qo S) of vehicle terminal's communication service. Firstly, Markov process is used to predict the transformation of wireless network's status after the decision via transition probability. Then the weights of evaluating parameters will be determined by fuzzy logic method. Finally, by comparing the total incomes of each wireless network, including handoff decision incomes, handoff execution incomes and communication service incomes after handoff, the optimal network to handoff will be selected. Simulation results show that: the algorithm proposed, compared to the existing algorithm, is able to receive a higher level of load balancing and effectively improves the average blocking rate, packet loss rate and ping-pang effect.展开更多
As one of the typical applications of connected vehicles(CVs),the vehicle platoon control technique has been proven to have the advantages of reducing emissions,improving traffic throughout and driving safety.In this ...As one of the typical applications of connected vehicles(CVs),the vehicle platoon control technique has been proven to have the advantages of reducing emissions,improving traffic throughout and driving safety.In this paper,a unified hierarchical framework is designed for cooperative control of CVs with both heterogeneous model parameters and structures.By separating neighboring information interaction from local dynamics control,the proposed framework is designed to contain an upper-level observing layer and a lower-level tracking control layer,which helps address the heterogeneity in vehicle parameters and structures.Within the proposed framework,an observer is designed for following vehicles to observe the leading vehicle's states using neighboring communication,while a tracking controller is designed to track the observed leading vehicle using local feedback control.Closed-loop stability in the absence and presence of communication time delay is analyzed,and the observer is further extended to a finite time convergent one to address string stability under general communication topology.Numerical simulation and field experiment verify the effectiveness of the proposed method.展开更多
With the increasing maturity of automatic driving technology,the homogeneous traffic flow will gradually evolve into the heterogeneous traffic flow,which consists of human-driving and autonomous vehicles.To better stu...With the increasing maturity of automatic driving technology,the homogeneous traffic flow will gradually evolve into the heterogeneous traffic flow,which consists of human-driving and autonomous vehicles.To better study the characteristics of the heterogeneous traffic system,this paper proposes a new car-following model for autonomous vehicles and heterogeneous traffic flow,which considers the self-stabilizing effect of vehicles.Through linear and nonlinear methods,this paper deduces and analyzes the stability of such a car-following model with the self-stabilizing effect.Finally,the model is verified by numerical simulation.Numerical results show that the self-stabilizing effect can make the heterogeneous traffic flow more stable,and that increasing the self-stabilizing coefficient or historical time length can strengthen the stability of heterogeneous traffic flow and alleviate traffic congestion effectively.In addition,the heterogeneous traffic flow can also be stabilized with a higher proportion of autonomous vehicles.展开更多
A heterogeneous coverage method with multiple unmanned aerial vehicle assisted sink nodes(MUAVSs)for multi-objective optimization problem(MOP)is proposed,which is based on quantum wolf pack evolution algorithm(QWPEA)a...A heterogeneous coverage method with multiple unmanned aerial vehicle assisted sink nodes(MUAVSs)for multi-objective optimization problem(MOP)is proposed,which is based on quantum wolf pack evolution algorithm(QWPEA)and power law entropy(PLE)theory.The method is composed of preset move and autonomous coordination stages for satisfying non-repeated coverage,connectedness,and energy balance of sink layer critical requirements,which is actualized to cover sensors layer in large-scale outside wireless sensor networks(WSNs).Simulation results show that the performance of the proposed technique is better than the existing related coverage technique.展开更多
This paper investigates the distributed adaptive platoon tracking problem of third-order heterogeneous vehicles subject to model uncertainties. The design process is divided into two steps. Firstly, an adaptive tracki...This paper investigates the distributed adaptive platoon tracking problem of third-order heterogeneous vehicles subject to model uncertainties. The design process is divided into two steps. Firstly, an adaptive tracking controller is designed for the dynamic leading vehicle. And then, the distributed adaptive controllers are established for followers. Moreover, the predictor technique is used to improve the estimate performance of the adaptive law, and the total disturbance is approximated and compensated by the variable gain nonlinear extended state observers(NESOs) driven by the estimation error. By introducing the variable gain hyperbolic tangent tracking differentiator(HTTD), the “complexity explosion” problem is avoided. The feasibility and effectiveness of the proposed protocol are verified by simulation tests.展开更多
The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper coo...The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper cooperative task allocation is superior to over the single UAV.Accordingly,several constraints should be satisfied to realize the efficient cooperation,such as special time-window,variant equipment,specified execution sequence.Hence,a proper task allocation in UAVs is the crucial point for the final success.The task allocation problem of the heterogeneous UAVs can be formulated as a multi-objective optimization problem coupled with the UAV dynamics.To this end,a multi-layer encoding strategy and a constraint scheduling method are designed to handle the critical logical and physical constraints.In addition,four optimization objectives:completion time,target reward,UAV damage,and total range,are introduced to evaluate various allocation plans.Subsequently,to efficiently solve the multi-objective optimization problem,an improved multi-objective quantum-behaved particle swarm optimization(IMOQPSO)algorithm is proposed.During this algorithm,a modified solution evaluation method is designed to guide algorithmic evolution;both the convergence and distribution of particles are considered comprehensively;and boundary solutions which may produce some special allocation plans are preserved.Moreover,adaptive parameter control and mixed update mechanism are also introduced in this algorithm.Finally,both the proposed model and algorithm are verified by simulation experiments.展开更多
By fully exploiting the spatial resources, unmanned aerial vehicles （UAVs） are expected to serve as an efficient complementary to terrestrial wireless communication system to provide enhanced coverage and reliable c...By fully exploiting the spatial resources, unmanned aerial vehicles （UAVs） are expected to serve as an efficient complementary to terrestrial wireless communication system to provide enhanced coverage and reliable connectivity to ground users. With the growing deployment of units such as small cell base stations （BSs）, however, the incurred severe interference may hinder the potential benefits of the integration of UAVs. In this paper, we first discuss the intrinsic features and potential benefits of UAVs and introduce the architecture of multi-layer heterogeneous wireless network （MHetNet）, in which traditional wireless network is assisted by UAVs. Then, an explicit discussion on the factors that limit the performance of MHetNet is presented, including the UAV topology, UAV density, and spectrum sharing of UAV and terrestrial networks. We use simulation results to investigate the performance of MHetNet in terms of spatial throughput （ST）. It is shown that, together with the densities of UAV and terI＇estrial networks, the altitude of UAV is a limiting factor that should be optimized to improve the ST of MHetNet.展开更多
In the context of global carbon neutrality,new energy vehicle promotion(NEVP)has become an important means of reducing carbon emissions.This paper constructs a theoretical model and uses panel data on NEVP in 21 count...In the context of global carbon neutrality,new energy vehicle promotion(NEVP)has become an important means of reducing carbon emissions.This paper constructs a theoretical model and uses panel data on NEVP in 21 countries from 2012 to 2018 to empirically examine the green effect of NEVP.The results indicate the following:(1)NEVP significantly reduces greenhouse gases emissions,and the green effect can be transmitted and diffused through a direct path.(2)Replacing fuel-fired vehicles and accelerating the end-of-life vehicle scrapping process significantly conducted the green effect,and aggravating traffic congestion was not statistically significant.(3)The transmission mechanism of the green effect is regulated by regional economic heterogeneity.In regions with better development of fuel-fired vehicles,the transmission of the green effect is subject to the elimination of fuel-fired vehicles and traffic congestion governance,and the transmission efficiency is low.However,regions with a relatively weak fuel-fired automobile industry foundation show a strong“advantage of backwardness”,and the green effect is more prominent.This means that global NEVP should be further accelerated to achieve the green effect and the goal of global carbon neutrality.展开更多
基金supported by the National Natural Science Foundation of China under Grant 62171465。
文摘Many efforts have been devoted to efficient task scheduling in Multi-Unmanned Aerial Vehicle(UAV)edge computing.However,the heterogeneity of UAV computation resource,and the task re-allocating between UAVs have not been fully considered yet.Moreover,most existing works neglect the fact that a task can only be executed on the UAV equipped with its desired service function(SF).In this backdrop,this paper formulates the task scheduling problem as a multi-objective task scheduling problem,which aims at maximizing the task execution success ratio while minimizing the average weighted sum of all tasks’completion time and energy consumption.Optimizing three coupled goals in a realtime manner with the dynamic arrival of tasks hinders us from adopting existing methods,like machine learning-based solutions that require a long training time and tremendous pre-knowledge about the task arrival process,or heuristic-based ones that usually incur a long decision-making time.To tackle this problem in a distributed manner,we establish a matching theory framework,in which three conflicting goals are treated as the preferences of tasks,SFs and UAVs.Then,a Distributed Matching Theory-based Re-allocating(DiMaToRe)algorithm is put forward.We formally proved that a stable matching can be achieved by our proposal.Extensive simulation results show that Di Ma To Re algorithm outperforms benchmark algorithms under diverse parameter settings and has good robustness.
基金supported in part by the National Natural Science Foundation of China under grant No. 61271259, No. 61301123, No. 61471076Scientific and Technological Research Program of Chongqing Municipal Education Commission of Chongqing of China under Grant No.KJ130536
文摘In order to solve the problem the existing vertical handoff algorithms of vehicle heterogeneous wireless network do not consider the diversification of network's status, an optimized vertical handoff algorithm based on markov process is proposed and discussed in this paper. This algorithm takes into account that the status transformation of available network will affect the quality of service(Qo S) of vehicle terminal's communication service. Firstly, Markov process is used to predict the transformation of wireless network's status after the decision via transition probability. Then the weights of evaluating parameters will be determined by fuzzy logic method. Finally, by comparing the total incomes of each wireless network, including handoff decision incomes, handoff execution incomes and communication service incomes after handoff, the optimal network to handoff will be selected. Simulation results show that: the algorithm proposed, compared to the existing algorithm, is able to receive a higher level of load balancing and effectively improves the average blocking rate, packet loss rate and ping-pang effect.
基金the National Key Research and Development Program of China(2021YFB2501803)the National Natural Science Foundation of China(52172384,52002126,52102394)+2 种基金Hunan Provincial Natural Science Foundation of China(2021JJ40065)the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body(61775006)the Fundamental Research Funds for the Central Universities。
文摘As one of the typical applications of connected vehicles(CVs),the vehicle platoon control technique has been proven to have the advantages of reducing emissions,improving traffic throughout and driving safety.In this paper,a unified hierarchical framework is designed for cooperative control of CVs with both heterogeneous model parameters and structures.By separating neighboring information interaction from local dynamics control,the proposed framework is designed to contain an upper-level observing layer and a lower-level tracking control layer,which helps address the heterogeneity in vehicle parameters and structures.Within the proposed framework,an observer is designed for following vehicles to observe the leading vehicle's states using neighboring communication,while a tracking controller is designed to track the observed leading vehicle using local feedback control.Closed-loop stability in the absence and presence of communication time delay is analyzed,and the observer is further extended to a finite time convergent one to address string stability under general communication topology.Numerical simulation and field experiment verify the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(Grant No.61773243)the Major Technology Innovation Project of Shandong Province,China(Grant No.2019TSLH0203)the National Key Research and Development Program of China(Grant No.2020YFB1600501)。
文摘With the increasing maturity of automatic driving technology,the homogeneous traffic flow will gradually evolve into the heterogeneous traffic flow,which consists of human-driving and autonomous vehicles.To better study the characteristics of the heterogeneous traffic system,this paper proposes a new car-following model for autonomous vehicles and heterogeneous traffic flow,which considers the self-stabilizing effect of vehicles.Through linear and nonlinear methods,this paper deduces and analyzes the stability of such a car-following model with the self-stabilizing effect.Finally,the model is verified by numerical simulation.Numerical results show that the self-stabilizing effect can make the heterogeneous traffic flow more stable,and that increasing the self-stabilizing coefficient or historical time length can strengthen the stability of heterogeneous traffic flow and alleviate traffic congestion effectively.In addition,the heterogeneous traffic flow can also be stabilized with a higher proportion of autonomous vehicles.
基金Supported by the National Natural Science Foundation of China(No.61571318)Key Research and Development Project of Hainan(No.ZDYF2018006)+1 种基金Independent Innovation Fund of Tianjin UniversityDoctoral Fund Funded Projects
文摘A heterogeneous coverage method with multiple unmanned aerial vehicle assisted sink nodes(MUAVSs)for multi-objective optimization problem(MOP)is proposed,which is based on quantum wolf pack evolution algorithm(QWPEA)and power law entropy(PLE)theory.The method is composed of preset move and autonomous coordination stages for satisfying non-repeated coverage,connectedness,and energy balance of sink layer critical requirements,which is actualized to cover sensors layer in large-scale outside wireless sensor networks(WSNs).Simulation results show that the performance of the proposed technique is better than the existing related coverage technique.
基金supported by the National Natural Science Foundation of China(Grant Nos.62373208 and 62003097)the Taishan Scholar Program of Shandong Province of China(Grant No.tsqn202306218)the Talent Introduction and Cultivation Plan for Youth Innovation of Universities in Shandong Province。
文摘This paper investigates the distributed adaptive platoon tracking problem of third-order heterogeneous vehicles subject to model uncertainties. The design process is divided into two steps. Firstly, an adaptive tracking controller is designed for the dynamic leading vehicle. And then, the distributed adaptive controllers are established for followers. Moreover, the predictor technique is used to improve the estimate performance of the adaptive law, and the total disturbance is approximated and compensated by the variable gain nonlinear extended state observers(NESOs) driven by the estimation error. By introducing the variable gain hyperbolic tangent tracking differentiator(HTTD), the “complexity explosion” problem is avoided. The feasibility and effectiveness of the proposed protocol are verified by simulation tests.
基金Project(61801495)supported by the National Natural Science Foundation of China
文摘The application of multiple UAVs in complicated tasks has been widely explored in recent years.Due to the advantages of flexibility,cheapness and consistence,the performance of heterogeneous multi-UAVs with proper cooperative task allocation is superior to over the single UAV.Accordingly,several constraints should be satisfied to realize the efficient cooperation,such as special time-window,variant equipment,specified execution sequence.Hence,a proper task allocation in UAVs is the crucial point for the final success.The task allocation problem of the heterogeneous UAVs can be formulated as a multi-objective optimization problem coupled with the UAV dynamics.To this end,a multi-layer encoding strategy and a constraint scheduling method are designed to handle the critical logical and physical constraints.In addition,four optimization objectives:completion time,target reward,UAV damage,and total range,are introduced to evaluate various allocation plans.Subsequently,to efficiently solve the multi-objective optimization problem,an improved multi-objective quantum-behaved particle swarm optimization(IMOQPSO)algorithm is proposed.During this algorithm,a modified solution evaluation method is designed to guide algorithmic evolution;both the convergence and distribution of particles are considered comprehensively;and boundary solutions which may produce some special allocation plans are preserved.Moreover,adaptive parameter control and mixed update mechanism are also introduced in this algorithm.Finally,both the proposed model and algorithm are verified by simulation experiments.
文摘By fully exploiting the spatial resources, unmanned aerial vehicles （UAVs） are expected to serve as an efficient complementary to terrestrial wireless communication system to provide enhanced coverage and reliable connectivity to ground users. With the growing deployment of units such as small cell base stations （BSs）, however, the incurred severe interference may hinder the potential benefits of the integration of UAVs. In this paper, we first discuss the intrinsic features and potential benefits of UAVs and introduce the architecture of multi-layer heterogeneous wireless network （MHetNet）, in which traditional wireless network is assisted by UAVs. Then, an explicit discussion on the factors that limit the performance of MHetNet is presented, including the UAV topology, UAV density, and spectrum sharing of UAV and terrestrial networks. We use simulation results to investigate the performance of MHetNet in terms of spatial throughput （ST）. It is shown that, together with the densities of UAV and terI＇estrial networks, the altitude of UAV is a limiting factor that should be optimized to improve the ST of MHetNet.
文摘In the context of global carbon neutrality,new energy vehicle promotion(NEVP)has become an important means of reducing carbon emissions.This paper constructs a theoretical model and uses panel data on NEVP in 21 countries from 2012 to 2018 to empirically examine the green effect of NEVP.The results indicate the following:(1)NEVP significantly reduces greenhouse gases emissions,and the green effect can be transmitted and diffused through a direct path.(2)Replacing fuel-fired vehicles and accelerating the end-of-life vehicle scrapping process significantly conducted the green effect,and aggravating traffic congestion was not statistically significant.(3)The transmission mechanism of the green effect is regulated by regional economic heterogeneity.In regions with better development of fuel-fired vehicles,the transmission of the green effect is subject to the elimination of fuel-fired vehicles and traffic congestion governance,and the transmission efficiency is low.However,regions with a relatively weak fuel-fired automobile industry foundation show a strong“advantage of backwardness”,and the green effect is more prominent.This means that global NEVP should be further accelerated to achieve the green effect and the goal of global carbon neutrality.
