The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method f...The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method for infrared and visible image fusion is proposed.The encoder designed according to the optimization objective consists of a base encoder and a detail encoder,which is used to extract low-frequency and high-frequency information from the image.This extraction may lead to some information not being captured,so a compensation encoder is proposed to supplement the missing information.Multi-scale decomposition is also employed to extract image features more comprehensively.The decoder combines low-frequency,high-frequency and supplementary information to obtain multi-scale features.Subsequently,the attention strategy and fusion module are introduced to perform multi-scale fusion for image reconstruction.Experimental results on three datasets show that the fused images generated by this network effectively retain salient targets while being more consistent with human visual perception.展开更多
In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-base...In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system resources.Then,a light-induced plant growth simulation algorithm was established.The performance of the algorithm was compared through several plant types,and the best plant model was selected as the setting for the system.Experimental results show that when the number of test cloud-based web services reaches 2048,the model being 2.14 times faster than PSO,2.8 times faster than the ant colony algorithm,2.9 times faster than the bee colony algorithm,and a remarkable 8.38 times faster than the genetic algorithm.展开更多
Urban combat environments pose complex and variable challenges for UAV path planning due to multidimensional factors,such as static and dynamic obstructions as well as risks of exposure to enemy detection,which threat...Urban combat environments pose complex and variable challenges for UAV path planning due to multidimensional factors,such as static and dynamic obstructions as well as risks of exposure to enemy detection,which threaten flight safety and mission success.Traditional path planning methods typically depend solely on the distribution of static obstacles to generate collision-free paths,without accounting for constraints imposed by enemy detection and strike capabilities.Such a simplified approach can yield safety-compromising routes in highly complex urban airspace.To address these limitations,this study proposes a multi-parameter path planning method based on reachable airspace visibility graphs,which integrates UAV performance constraints,environmental limitations,and exposure risks.An innovative heuristic algorithm is developed to balance operational safety and efficiency by both exposure risks and path length.In the case study set in a typical mixed-use urban area,analysis of airspace visibility graphs reveals significant variations in exposure risk at different regions and altitudes due to building encroachments.Path optimization results indicate that the method can effectively generate covert and efficient flight paths by dynamically adjusting the exposure index,which represents the likelihood of enemy detection,and the path length,which corresponds to mission execution time.展开更多
Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be so...Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be solved. A comprehensive evaluation method is proposed, which combines grey relational analysis (GRA) and cloud model, to evaluate the anti-jamming performances of Link-16. Firstly, on the basis of establishing the anti-jamming performance evaluation indicator system of Link-16, the linear combination of analytic hierarchy process(AHP) and entropy weight method (EWM) are used to calculate the combined weight. Secondly, the qualitative and quantitative concept transformation model, i.e., the cloud model, is introduced to evaluate the anti-jamming abilities of Link-16 under each jamming scheme. In addition, GRA calculates the correlation degree between evaluation indicators and the anti-jamming performance of Link-16, and assesses the best anti-jamming technology. Finally, simulation results prove that the proposed evaluation model can achieve the objective of feasible and practical evaluation, which opens up a novel way for the research of anti-jamming performance evaluations of Link-16.展开更多
DNAN-based insensitive melt-cast explosives have been widely utilized in insensitive munition in recent years. When constrained DNAN-based melt-cast explosives are ignited under thermal stimulation, the base explosive...DNAN-based insensitive melt-cast explosives have been widely utilized in insensitive munition in recent years. When constrained DNAN-based melt-cast explosives are ignited under thermal stimulation, the base explosive exists in a molten liquid state, where high-temperature gases expand and react in the form of bubble clouds within the liquid explosive;this process is distinctly different from the dynamic crack propagation process observed in the case of solid explosives. In this study, a control model for the reaction evolution of burning-bubble clouds was established to describe the reaction process and quantify the reaction violence of DNAN-based melt-cast explosives, considering the size distribution and activation mechanism of the burning-bubble clouds. The feasibility of the model was verified through experimental results. The results revealed that under geometrically similar conditions, with identical confinement strength and aspect ratio, larger charge structures led to extended initial gas flow and surface burning processes, resulting in greater reaction equivalence and violence at the casing fracture.Under constant charge volume and size, a stronger casing confinement accelerated self-enhanced burning, increasing the internal pressure, reaction degree, and reaction violence. Under a constant casing thickness and radius, higher aspect ratios led to a greater reaction violence at the casing fracture.Moreover, under a constant charge volume and casing thickness, higher aspect ratios resulted in a higher internal pressure, increased reaction degree, and greater reaction violence at the casing fracture. Further,larger ullage volumes extended the reaction evolution time and increased the reaction violence under constant casing dimensions. Through a matching design of the opening threshold of the pressure relief holes and the relief structure area, a stable burning reaction could be maintained until completion,thereby achieving a control of the reaction violence. The proposed model could effectively reflect the effects of the intrinsic burning rate, casing confinement strength, charge size, ullage volume, and pressure relief structure on the reaction evolution process and reaction violence, providing a theoretical method for the thermal safety design and reaction violence evaluation of melt-cast explosives.展开更多
With the rapid development of cloud manufacturing technology and the new generation of artificial intelligence technology,the new cloud manufacturing system(NCMS)built on the connotation of cloud manufacturing 3.0 pre...With the rapid development of cloud manufacturing technology and the new generation of artificial intelligence technology,the new cloud manufacturing system(NCMS)built on the connotation of cloud manufacturing 3.0 presents a new business model of“Internet of everything,intelligent leading,data driving,shared services,cross-border integration,and universal innovation”.The network boundaries are becoming increasingly blurred,NCMS is facing security risks such as equipment unauthorized use,account theft,static and extensive access control policies,unauthorized access,supply chain attacks,sensitive data leaks,and industrial control vulnerability attacks.Traditional security architectures mainly use information security technology,which cannot meet the active security protection requirements of NCMS.In order to solve the above problems,this paper proposes an integrated cloud-edge-terminal security system architecture of NCMS.It adopts the zero trust concept and effectively integrates multiple security capabilities such as network,equipment,cloud computing environment,application,identity,and data.It adopts a new access control mode of“continuous verification+dynamic authorization”,classified access control mechanisms such as attribute-based access control,rolebased access control,policy-based access control,and a new data security protection system based on blockchain,achieving“trustworthy subject identity,controllable access behavior,and effective protection of subject and object resources”.This architecture provides an active security protection method for NCMS in the digital transformation of large enterprises,and can effectively enhance network security protection capabilities and cope with increasingly severe network security situations.展开更多
The industrial Internet of Things(IIoT)is a new indus-trial idea that combines the latest information and communica-tion technologies with the industrial economy.In this paper,a cloud control structure is designed for...The industrial Internet of Things(IIoT)is a new indus-trial idea that combines the latest information and communica-tion technologies with the industrial economy.In this paper,a cloud control structure is designed for IIoT in cloud-edge envi-ronment with three modes of 5G.For 5G based IIoT,the time sensitive network(TSN)service is introduced in transmission network.A 5G logical TSN bridge is designed to transport TSN streams over 5G framework to achieve end-to-end configuration.For a transmission control protocol(TCP)model with nonlinear disturbance,time delay and uncertainties,a robust adaptive fuzzy sliding mode controller(AFSMC)is given with control rule parameters.IIoT workflows are made up of a series of subtasks that are linked by the dependencies between sensor datasets and task flows.IIoT workflow scheduling is a non-deterministic polynomial(NP)-hard problem in cloud-edge environment.An adaptive and non-local-convergent particle swarm optimization(ANCPSO)is designed with nonlinear inertia weight to avoid falling into local optimum,which can reduce the makespan and cost dramatically.Simulation and experiments demonstrate that ANCPSO has better performances than other classical algo-rithms.展开更多
To solve the problem of target damage assessment when fragments attack target under uncertain projectile and target intersection in an air defense intercept,this paper proposes a method for calculating target damage p...To solve the problem of target damage assessment when fragments attack target under uncertain projectile and target intersection in an air defense intercept,this paper proposes a method for calculating target damage probability leveraging spatio-temporal finite multilayer fragments distribution and the target damage assessment algorithm based on cloud model theory.Drawing on the spatial dispersion characteristics of fragments of projectile proximity explosion,we divide into a finite number of fragments distribution planes based on the time series in space,set up a fragment layer dispersion model grounded in the time series and intersection criterion for determining the effective penetration of each layer of fragments into the target.Building on the precondition that the multilayer fragments of the time series effectively assail the target,we also establish the damage criterion of the perforation and penetration damage and deduce the damage probability calculation model.Taking the damage probability of the fragment layer in the spatio-temporal sequence to the target as the input state variable,we introduce cloud model theory to research the target damage assessment method.Combining the equivalent simulation experiment,the scientific and rational nature of the proposed method were validated through quantitative calculations and comparative analysis.展开更多
In view of the limitations of traditional measurement methods in the field of building information,such as complex operation,low timeliness and poor accuracy,a new way of combining three-dimensional scanning technolog...In view of the limitations of traditional measurement methods in the field of building information,such as complex operation,low timeliness and poor accuracy,a new way of combining three-dimensional scanning technology and BIM(Building Information Modeling)model was discussed.Focused on the efficient acquisition of building geometric information using the fast-developing 3D point cloud technology,an improved deep learning-based 3D point cloud recognition method was proposed.The method optimised the network structure based on RandLA-Net to adapt to the large-scale point cloud processing requirements,while the semantic and instance features of the point cloud were integrated to significantly improve the recognition accuracy and provide a precise basis for BIM model remodeling.In addition,a visual BIM model generation system was developed,which systematically transformed the point cloud recognition results into BIM component parameters,automatically constructed BIM models,and promoted the open sharing and secondary development of models.The research results not only effectively promote the automation process of converting 3D point cloud data to refined BIM models,but also provide important technical support for promoting building informatisation and accelerating the construction of smart cities,showing a wide range of application potential and practical value.展开更多
The debris cloud generated by the hypervelocity impact(HVI)of orbiting space debris directly threatens the spacecraft.A full understanding of the damage mechanism of rear plate is useful for the optimal design of prot...The debris cloud generated by the hypervelocity impact(HVI)of orbiting space debris directly threatens the spacecraft.A full understanding of the damage mechanism of rear plate is useful for the optimal design of protective structures.In this study,the hypervelocity yaw impact of a cylindrical aluminum projectile on a double-layer aluminum plate is simulated by the FE-SPH adaptive method,and the damage process of the rear plate under the impact of the debris cloud is analyzed based on the debris cloud structure.The damage process can be divided into the main impact stage of the debris cloud and the structural response of the rear plate.The main impact stage lasts a short time and is the basis of the rear plate damage.In the stage of structure response,the continuous deformation and inertial motion of the rear plate dominate the perforation of the rear plate.We further analyze the damage mechanism and damage distribution characteristics of the rear plate in detail.Moreover,the connection between velocity space and position space of the debris cloud is established,which promotes the general analysis of the damage law of debris cloud.Based on the relationship,the features of typical damage areas are identified by the localized fine analysis.Both the cumulative effect and structural response cause the perforation of rear plate;in the non-perforated area,cratering by the impact of hazardous fragments is the main damage mode of the rear plate.展开更多
With the advantage of exceptional long-range traffic perception capabilities and data fusion computational prowess,the cloud control system(CCS)has exhibited formidable poten-tial in the realm of connected assisted dr...With the advantage of exceptional long-range traffic perception capabilities and data fusion computational prowess,the cloud control system(CCS)has exhibited formidable poten-tial in the realm of connected assisted driving,such as the adap-tive cruise control(ACC).Based on the CCS architecture,this paper proposes a cloud-based predictive ACC(PACC)strategy,which fully considers the road slope information and the preced-ing vehicle status.In the cloud,based on the dynamic program-ming(DP),the long-term economic speed planning is carried out by using the slope information.At the vehicle side,the real-time fusion planning of the economic speed and the preceding vehi-cle state is realized based on the model predictive control(MPC),taking into account the safety and economy of driving.In order to ensure the safety and stability of the vehicle-cloud cooperative control system,an event-triggered cruise mode switching method is proposed based on the state of each sub-system of the vehicle-cloud-network-map.Simulation results indicate that the PACC system can still ensure stable cruising under delays and some complex conditions.Moreover,under normal conditions,compared to the ACC system,the PACC sys-tem can further improve economy while ensuring safety and improve the overall energy efficiency of the vehicle,thus achiev-ing fuel savings of 3%to 8%.展开更多
基金Supported by the Henan Province Key Research and Development Project(231111211300)the Central Government of Henan Province Guides Local Science and Technology Development Funds(Z20231811005)+2 种基金Henan Province Key Research and Development Project(231111110100)Henan Provincial Outstanding Foreign Scientist Studio(GZS2024006)Henan Provincial Joint Fund for Scientific and Technological Research and Development Plan(Application and Overcoming Technical Barriers)(242103810028)。
文摘The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method for infrared and visible image fusion is proposed.The encoder designed according to the optimization objective consists of a base encoder and a detail encoder,which is used to extract low-frequency and high-frequency information from the image.This extraction may lead to some information not being captured,so a compensation encoder is proposed to supplement the missing information.Multi-scale decomposition is also employed to extract image features more comprehensively.The decoder combines low-frequency,high-frequency and supplementary information to obtain multi-scale features.Subsequently,the attention strategy and fusion module are introduced to perform multi-scale fusion for image reconstruction.Experimental results on three datasets show that the fused images generated by this network effectively retain salient targets while being more consistent with human visual perception.
基金Shanxi Province Higher Education Science and Technology Innovation Fund Project(2022-676)Shanxi Soft Science Program Research Fund Project(2016041008-6)。
文摘In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system resources.Then,a light-induced plant growth simulation algorithm was established.The performance of the algorithm was compared through several plant types,and the best plant model was selected as the setting for the system.Experimental results show that when the number of test cloud-based web services reaches 2048,the model being 2.14 times faster than PSO,2.8 times faster than the ant colony algorithm,2.9 times faster than the bee colony algorithm,and a remarkable 8.38 times faster than the genetic algorithm.
基金supported by the Ministry of Industry and Information Technology(No.23100002022102001)。
文摘Urban combat environments pose complex and variable challenges for UAV path planning due to multidimensional factors,such as static and dynamic obstructions as well as risks of exposure to enemy detection,which threaten flight safety and mission success.Traditional path planning methods typically depend solely on the distribution of static obstacles to generate collision-free paths,without accounting for constraints imposed by enemy detection and strike capabilities.Such a simplified approach can yield safety-compromising routes in highly complex urban airspace.To address these limitations,this study proposes a multi-parameter path planning method based on reachable airspace visibility graphs,which integrates UAV performance constraints,environmental limitations,and exposure risks.An innovative heuristic algorithm is developed to balance operational safety and efficiency by both exposure risks and path length.In the case study set in a typical mixed-use urban area,analysis of airspace visibility graphs reveals significant variations in exposure risk at different regions and altitudes due to building encroachments.Path optimization results indicate that the method can effectively generate covert and efficient flight paths by dynamically adjusting the exposure index,which represents the likelihood of enemy detection,and the path length,which corresponds to mission execution time.
基金Heilongjiang Provincial Natural Science Foundation of China (LH2021F009)。
文摘Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be solved. A comprehensive evaluation method is proposed, which combines grey relational analysis (GRA) and cloud model, to evaluate the anti-jamming performances of Link-16. Firstly, on the basis of establishing the anti-jamming performance evaluation indicator system of Link-16, the linear combination of analytic hierarchy process(AHP) and entropy weight method (EWM) are used to calculate the combined weight. Secondly, the qualitative and quantitative concept transformation model, i.e., the cloud model, is introduced to evaluate the anti-jamming abilities of Link-16 under each jamming scheme. In addition, GRA calculates the correlation degree between evaluation indicators and the anti-jamming performance of Link-16, and assesses the best anti-jamming technology. Finally, simulation results prove that the proposed evaluation model can achieve the objective of feasible and practical evaluation, which opens up a novel way for the research of anti-jamming performance evaluations of Link-16.
基金supported by the National Natural Science Foundation of China (Grant No. 12002044)。
文摘DNAN-based insensitive melt-cast explosives have been widely utilized in insensitive munition in recent years. When constrained DNAN-based melt-cast explosives are ignited under thermal stimulation, the base explosive exists in a molten liquid state, where high-temperature gases expand and react in the form of bubble clouds within the liquid explosive;this process is distinctly different from the dynamic crack propagation process observed in the case of solid explosives. In this study, a control model for the reaction evolution of burning-bubble clouds was established to describe the reaction process and quantify the reaction violence of DNAN-based melt-cast explosives, considering the size distribution and activation mechanism of the burning-bubble clouds. The feasibility of the model was verified through experimental results. The results revealed that under geometrically similar conditions, with identical confinement strength and aspect ratio, larger charge structures led to extended initial gas flow and surface burning processes, resulting in greater reaction equivalence and violence at the casing fracture.Under constant charge volume and size, a stronger casing confinement accelerated self-enhanced burning, increasing the internal pressure, reaction degree, and reaction violence. Under a constant casing thickness and radius, higher aspect ratios led to a greater reaction violence at the casing fracture.Moreover, under a constant charge volume and casing thickness, higher aspect ratios resulted in a higher internal pressure, increased reaction degree, and greater reaction violence at the casing fracture. Further,larger ullage volumes extended the reaction evolution time and increased the reaction violence under constant casing dimensions. Through a matching design of the opening threshold of the pressure relief holes and the relief structure area, a stable burning reaction could be maintained until completion,thereby achieving a control of the reaction violence. The proposed model could effectively reflect the effects of the intrinsic burning rate, casing confinement strength, charge size, ullage volume, and pressure relief structure on the reaction evolution process and reaction violence, providing a theoretical method for the thermal safety design and reaction violence evaluation of melt-cast explosives.
文摘With the rapid development of cloud manufacturing technology and the new generation of artificial intelligence technology,the new cloud manufacturing system(NCMS)built on the connotation of cloud manufacturing 3.0 presents a new business model of“Internet of everything,intelligent leading,data driving,shared services,cross-border integration,and universal innovation”.The network boundaries are becoming increasingly blurred,NCMS is facing security risks such as equipment unauthorized use,account theft,static and extensive access control policies,unauthorized access,supply chain attacks,sensitive data leaks,and industrial control vulnerability attacks.Traditional security architectures mainly use information security technology,which cannot meet the active security protection requirements of NCMS.In order to solve the above problems,this paper proposes an integrated cloud-edge-terminal security system architecture of NCMS.It adopts the zero trust concept and effectively integrates multiple security capabilities such as network,equipment,cloud computing environment,application,identity,and data.It adopts a new access control mode of“continuous verification+dynamic authorization”,classified access control mechanisms such as attribute-based access control,rolebased access control,policy-based access control,and a new data security protection system based on blockchain,achieving“trustworthy subject identity,controllable access behavior,and effective protection of subject and object resources”.This architecture provides an active security protection method for NCMS in the digital transformation of large enterprises,and can effectively enhance network security protection capabilities and cope with increasingly severe network security situations.
文摘The industrial Internet of Things(IIoT)is a new indus-trial idea that combines the latest information and communica-tion technologies with the industrial economy.In this paper,a cloud control structure is designed for IIoT in cloud-edge envi-ronment with three modes of 5G.For 5G based IIoT,the time sensitive network(TSN)service is introduced in transmission network.A 5G logical TSN bridge is designed to transport TSN streams over 5G framework to achieve end-to-end configuration.For a transmission control protocol(TCP)model with nonlinear disturbance,time delay and uncertainties,a robust adaptive fuzzy sliding mode controller(AFSMC)is given with control rule parameters.IIoT workflows are made up of a series of subtasks that are linked by the dependencies between sensor datasets and task flows.IIoT workflow scheduling is a non-deterministic polynomial(NP)-hard problem in cloud-edge environment.An adaptive and non-local-convergent particle swarm optimization(ANCPSO)is designed with nonlinear inertia weight to avoid falling into local optimum,which can reduce the makespan and cost dramatically.Simulation and experiments demonstrate that ANCPSO has better performances than other classical algo-rithms.
基金supported by National Natural Science Foundation of China(Grant No.62073256)the Shaanxi Provincial Science and Technology Department(Grant No.2023-YBGY-342).
文摘To solve the problem of target damage assessment when fragments attack target under uncertain projectile and target intersection in an air defense intercept,this paper proposes a method for calculating target damage probability leveraging spatio-temporal finite multilayer fragments distribution and the target damage assessment algorithm based on cloud model theory.Drawing on the spatial dispersion characteristics of fragments of projectile proximity explosion,we divide into a finite number of fragments distribution planes based on the time series in space,set up a fragment layer dispersion model grounded in the time series and intersection criterion for determining the effective penetration of each layer of fragments into the target.Building on the precondition that the multilayer fragments of the time series effectively assail the target,we also establish the damage criterion of the perforation and penetration damage and deduce the damage probability calculation model.Taking the damage probability of the fragment layer in the spatio-temporal sequence to the target as the input state variable,we introduce cloud model theory to research the target damage assessment method.Combining the equivalent simulation experiment,the scientific and rational nature of the proposed method were validated through quantitative calculations and comparative analysis.
文摘In view of the limitations of traditional measurement methods in the field of building information,such as complex operation,low timeliness and poor accuracy,a new way of combining three-dimensional scanning technology and BIM(Building Information Modeling)model was discussed.Focused on the efficient acquisition of building geometric information using the fast-developing 3D point cloud technology,an improved deep learning-based 3D point cloud recognition method was proposed.The method optimised the network structure based on RandLA-Net to adapt to the large-scale point cloud processing requirements,while the semantic and instance features of the point cloud were integrated to significantly improve the recognition accuracy and provide a precise basis for BIM model remodeling.In addition,a visual BIM model generation system was developed,which systematically transformed the point cloud recognition results into BIM component parameters,automatically constructed BIM models,and promoted the open sharing and secondary development of models.The research results not only effectively promote the automation process of converting 3D point cloud data to refined BIM models,but also provide important technical support for promoting building informatisation and accelerating the construction of smart cities,showing a wide range of application potential and practical value.
基金supported by the Innovative Research Groups of the National Natural Science Foundation of China(Grant No.12221002)。
文摘The debris cloud generated by the hypervelocity impact(HVI)of orbiting space debris directly threatens the spacecraft.A full understanding of the damage mechanism of rear plate is useful for the optimal design of protective structures.In this study,the hypervelocity yaw impact of a cylindrical aluminum projectile on a double-layer aluminum plate is simulated by the FE-SPH adaptive method,and the damage process of the rear plate under the impact of the debris cloud is analyzed based on the debris cloud structure.The damage process can be divided into the main impact stage of the debris cloud and the structural response of the rear plate.The main impact stage lasts a short time and is the basis of the rear plate damage.In the stage of structure response,the continuous deformation and inertial motion of the rear plate dominate the perforation of the rear plate.We further analyze the damage mechanism and damage distribution characteristics of the rear plate in detail.Moreover,the connection between velocity space and position space of the debris cloud is established,which promotes the general analysis of the damage law of debris cloud.Based on the relationship,the features of typical damage areas are identified by the localized fine analysis.Both the cumulative effect and structural response cause the perforation of rear plate;in the non-perforated area,cratering by the impact of hazardous fragments is the main damage mode of the rear plate.
基金supported by the National Key R&D Program of China(2021YFB2501000)the Consultancy Research Project on the Strategic Study of the Integration and Innovative Development of Intelligent Connected Vehicles and New Energy Ecology in Zhejiang Province(2023ZL0007)+1 种基金the Hetao Shenzhen-HongKong Science and Technology Innovation Cooperation Zone(HZQB-KCZYZ-2021055)the Open Project of the Key Laboratory of Modern Measurement and Control Technology of the Ministry of Education(KF2022-1123202).
文摘With the advantage of exceptional long-range traffic perception capabilities and data fusion computational prowess,the cloud control system(CCS)has exhibited formidable poten-tial in the realm of connected assisted driving,such as the adap-tive cruise control(ACC).Based on the CCS architecture,this paper proposes a cloud-based predictive ACC(PACC)strategy,which fully considers the road slope information and the preced-ing vehicle status.In the cloud,based on the dynamic program-ming(DP),the long-term economic speed planning is carried out by using the slope information.At the vehicle side,the real-time fusion planning of the economic speed and the preceding vehi-cle state is realized based on the model predictive control(MPC),taking into account the safety and economy of driving.In order to ensure the safety and stability of the vehicle-cloud cooperative control system,an event-triggered cruise mode switching method is proposed based on the state of each sub-system of the vehicle-cloud-network-map.Simulation results indicate that the PACC system can still ensure stable cruising under delays and some complex conditions.Moreover,under normal conditions,compared to the ACC system,the PACC sys-tem can further improve economy while ensuring safety and improve the overall energy efficiency of the vehicle,thus achiev-ing fuel savings of 3%to 8%.
