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铜绿山矿床蚀变矿物光谱EVS三维可视化建模及指示意义
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作者 姚亦菲 王金林 +2 位作者 陈华勇 张世涛 初高彬 《地球化学》 CAS CSCD 北大核心 2024年第5期719-733,I0001-I0009,共24页
随着浅表金属矿产资源的逐渐枯竭,深部隐伏矿体找矿勘查成为未来趋势,相应找矿勘查技术和方法的创新势在必行。近年来,短波红外(SWIR)光谱技术在全球典型斑岩–浅成低温热液矿床和矽卡岩型矿床的深部找矿勘查中发挥了重要作用,但目前主... 随着浅表金属矿产资源的逐渐枯竭,深部隐伏矿体找矿勘查成为未来趋势,相应找矿勘查技术和方法的创新势在必行。近年来,短波红外(SWIR)光谱技术在全球典型斑岩–浅成低温热液矿床和矽卡岩型矿床的深部找矿勘查中发挥了重要作用,但目前主要是基于二维剖面的工作。EVS(earth volumetric studio)建模系统是应用于地球科学领域的3D建模软件,此软件基于数据驱动,具有数据可视化及模型动态更新的特点,可以满足地质建模的需求。本文利用EVS软件,对鄂东南矿集区铜绿山矽卡岩型Cu-Fe-Au矿床ⅩⅢ和ⅩⅣ号隐伏矿体不同蚀变矿物的空间分布、绿泥石和高岭石族矿物SWIR光谱特征参数的空间变化进行了三维可视化建模,探讨不同蚀变矿物和SWIR光谱参数与隐伏矿体之间的三维空间耦合关系;通过MATLAB原创程序计算含绿泥石SWIR光谱参数的样品点与深部矿化中心的三维最短距离,评价了SWIR光谱参数对深部热液矿化中心的精准指示潜力。结果表明,EVS软件三维建模在未来隐伏矿体勘查和预测中具有较大的应用潜力。 展开更多
关键词 evs三维建模 短波红外光谱 蚀变矿物 铜绿山Cu-Fe-Au矿床 鄂东南矿集区
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基于EVS建模分析物探-钻探在Cr(Ⅵ)污染场地勘察中的应用
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作者 郭佳林 刘芳 +1 位作者 楚振哲 杨旭 《环境科学与技术》 CAS CSCD 北大核心 2024年第10期171-178,共8页
为了探索物探和钻探技术在污染场地勘察中的综合应用,该研究选取河北省某铬污染场地作为案例。通过EVS软件对钻探数据进行三维建模,并结合高密度电法勘测结果综合分析了污染物的分布特征。建模结果揭示了试验地块的总体积为306.822 m^(... 为了探索物探和钻探技术在污染场地勘察中的综合应用,该研究选取河北省某铬污染场地作为案例。通过EVS软件对钻探数据进行三维建模,并结合高密度电法勘测结果综合分析了污染物的分布特征。建模结果揭示了试验地块的总体积为306.822 m^(3),其中Cr(Ⅵ)含量超标的体积达299.049 m^(3)。具体来看,超标1倍的体积为287.71 m^(3),2倍和3倍的分别仅为10.522 m^(3)和0.817 m^(3)。Cr(Ⅵ)含量在1倍超标时在地层中分布较为均匀,但在2~3倍超标时,主要集中于粉质黏土层,且底层Cr(Ⅵ)浓度较高。高密度电法勘测显示,粉砂、粉土和粉质黏土的视电阻率分别为2.5~5Ω·m、1~2.5Ω·m和小于1Ω·m,表明该技术对地层的响应良好。研究结果表明,EVS建模在清晰度和完整性方面优于传统分析方法,有助于更准确地评估污染场地的状况。此外,该方法通过区分不同土层,增强了物探分析的效能。然而,由于依赖钻探数据,模型可能受到钻孔数量的限制。高密度电法勘测作为一种有效的辅助手段,在钻探前能够识别不同地层,减少钻孔数量,同时确保模型建立的可信度。尽管如此,由于影响因素众多,视电阻率变化的原因难以简单归结。总体而言,结合EVS建模和高密度电法勘测不仅可以有效降低钻探工作量,还能准确识别污染严重区域,为污染场地的修复提供重要信息。 展开更多
关键词 evs建模 钻孔 高密度电法 污染场地勘察
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A blockchain based privacy-preserving federated learning scheme for Internet of Vehicles 被引量:1
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作者 Naiyu Wang Wenti Yang +4 位作者 Xiaodong Wang Longfei Wu Zhitao Guan Xiaojiang Du Mohsen Guizani 《Digital Communications and Networks》 SCIE CSCD 2024年第1期126-134,共9页
The application of artificial intelligence technology in Internet of Vehicles(lov)has attracted great research interests with the goal of enabling smart transportation and traffic management.Meanwhile,concerns have be... The application of artificial intelligence technology in Internet of Vehicles(lov)has attracted great research interests with the goal of enabling smart transportation and traffic management.Meanwhile,concerns have been raised over the security and privacy of the tons of traffic and vehicle data.In this regard,Federated Learning(FL)with privacy protection features is considered a highly promising solution.However,in the FL process,the server side may take advantage of its dominant role in model aggregation to steal sensitive information of users,while the client side may also upload malicious data to compromise the training of the global model.Most existing privacy-preserving FL schemes in IoV fail to deal with threats from both of these two sides at the same time.In this paper,we propose a Blockchain based Privacy-preserving Federated Learning scheme named BPFL,which uses blockchain as the underlying distributed framework of FL.We improve the Multi-Krum technology and combine it with the homomorphic encryption to achieve ciphertext-level model aggregation and model filtering,which can enable the verifiability of the local models while achieving privacy-preservation.Additionally,we develop a reputation-based incentive mechanism to encourage users in IoV to actively participate in the federated learning and to practice honesty.The security analysis and performance evaluations are conducted to show that the proposed scheme can meet the security requirements and improve the performance of the FL model. 展开更多
关键词 Federated learning Blockchain Privacy-preservation Homomorphic encryption Internetof vehicles
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Distributed Platooning Control of Automated Vehicles Subject to Replay Attacks Based on Proportional Integral Observers 被引量:1
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作者 Meiling Xie Derui Ding +3 位作者 Xiaohua Ge Qing-Long Han Hongli Dong Yan Song 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第9期1954-1966,共13页
Secure platooning control plays an important role in enhancing the cooperative driving safety of automated vehicles subject to various security vulnerabilities.This paper focuses on the distributed secure control issu... Secure platooning control plays an important role in enhancing the cooperative driving safety of automated vehicles subject to various security vulnerabilities.This paper focuses on the distributed secure control issue of automated vehicles affected by replay attacks.A proportional-integral-observer(PIO)with predetermined forgetting parameters is first constructed to acquire the dynamical information of vehicles.Then,a time-varying parameter and two positive scalars are employed to describe the temporal behavior of replay attacks.In light of such a scheme and the common properties of Laplace matrices,the closed-loop system with PIO-based controllers is transformed into a switched and time-delayed one.Furthermore,some sufficient conditions are derived to achieve the desired platooning performance by the view of the Lyapunov stability theory.The controller gains are analytically determined by resorting to the solution of certain matrix inequalities only dependent on maximum and minimum eigenvalues of communication topologies.Finally,a simulation example is provided to illustrate the effectiveness of the proposed control strategy. 展开更多
关键词 Automated vehicles platooning control proportional-integral-observers(PIOs) replay attacks TIME-DELAYS
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A credibility-aware swarm-federated deep learning framework in internet of vehicles 被引量:1
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作者 Zhe Wang Xinhang Li +2 位作者 Tianhao Wu Chen Xu Lin Zhang 《Digital Communications and Networks》 SCIE CSCD 2024年第1期150-157,共8页
Although Federated Deep Learning(FDL)enables distributed machine learning in the Internet of Vehicles(IoV),it requires multiple clients to upload model parameters,thus still existing unavoidable communication overhead... Although Federated Deep Learning(FDL)enables distributed machine learning in the Internet of Vehicles(IoV),it requires multiple clients to upload model parameters,thus still existing unavoidable communication overhead and data privacy risks.The recently proposed Swarm Learning(SL)provides a decentralized machine learning approach for unit edge computing and blockchain-based coordination.A Swarm-Federated Deep Learning framework in the IoV system(IoV-SFDL)that integrates SL into the FDL framework is proposed in this paper.The IoV-SFDL organizes vehicles to generate local SL models with adjacent vehicles based on the blockchain empowered SL,then aggregates the global FDL model among different SL groups with a credibility weights prediction algorithm.Extensive experimental results show that compared with the baseline frameworks,the proposed IoV-SFDL framework reduces the overhead of client-to-server communication by 16.72%,while the model performance improves by about 5.02%for the same training iterations. 展开更多
关键词 Swarm learning Federated deep learning Internet of vehicles PRIVACY EFFICIENCY
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Ensuring Secure Platooning of Constrained Intelligent and Connected Vehicles Against Byzantine Attacks:A Distributed MPC Framework 被引量:1
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作者 Henglai Wei Hui Zhang +1 位作者 Kamal AI-Haddad Yang Shi 《Engineering》 SCIE EI CAS CSCD 2024年第2期35-46,共12页
This study investigates resilient platoon control for constrained intelligent and connected vehicles(ICVs)against F-local Byzantine attacks.We introduce a resilient distributed model-predictive platooning control fram... This study investigates resilient platoon control for constrained intelligent and connected vehicles(ICVs)against F-local Byzantine attacks.We introduce a resilient distributed model-predictive platooning control framework for such ICVs.This framework seamlessly integrates the predesigned optimal control with distributed model predictive control(DMPC)optimization and introduces a unique distributed attack detector to ensure the reliability of the transmitted information among vehicles.Notably,our strategy uses previously broadcasted information and a specialized convex set,termed the“resilience set”,to identify unreliable data.This approach significantly eases graph robustness prerequisites,requiring only an(F+1)-robust graph,in contrast to the established mean sequence reduced algorithms,which require a minimum(2F+1)-robust graph.Additionally,we introduce a verification algorithm to restore trust in vehicles under minor attacks,further reducing communication network robustness.Our analysis demonstrates the recursive feasibility of the DMPC optimization.Furthermore,the proposed method achieves exceptional control performance by minimizing the discrepancies between the DMPC control inputs and predesigned platoon control inputs,while ensuring constraint compliance and cybersecurity.Simulation results verify the effectiveness of our theoretical findings. 展开更多
关键词 Model predictive control Resilient control Platoon control Intelligent and connected vehicle Byzantine attacks
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Low-Cost Federated Broad Learning for Privacy-Preserved Knowledge Sharing in the RIS-Aided Internet of Vehicles 被引量:1
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作者 Xiaoming Yuan Jiahui Chen +4 位作者 Ning Zhang Qiang(John)Ye Changle Li Chunsheng Zhu Xuemin Sherman Shen 《Engineering》 SCIE EI CAS CSCD 2024年第2期178-189,共12页
High-efficiency and low-cost knowledge sharing can improve the decision-making ability of autonomous vehicles by mining knowledge from the Internet of Vehicles(IoVs).However,it is challenging to ensure high efficiency... High-efficiency and low-cost knowledge sharing can improve the decision-making ability of autonomous vehicles by mining knowledge from the Internet of Vehicles(IoVs).However,it is challenging to ensure high efficiency of local data learning models while preventing privacy leakage in a high mobility environment.In order to protect data privacy and improve data learning efficiency in knowledge sharing,we propose an asynchronous federated broad learning(FBL)framework that integrates broad learning(BL)into federated learning(FL).In FBL,we design a broad fully connected model(BFCM)as a local model for training client data.To enhance the wireless channel quality for knowledge sharing and reduce the communication and computation cost of participating clients,we construct a joint resource allocation and reconfigurable intelligent surface(RIS)configuration optimization framework for FBL.The problem is decoupled into two convex subproblems.Aiming to improve the resource scheduling efficiency in FBL,a double Davidon–Fletcher–Powell(DDFP)algorithm is presented to solve the time slot allocation and RIS configuration problem.Based on the results of resource scheduling,we design a reward-allocation algorithm based on federated incentive learning(FIL)in FBL to compensate clients for their costs.The simulation results show that the proposed FBL framework achieves better performance than the comparison models in terms of efficiency,accuracy,and cost for knowledge sharing in the IoV. 展开更多
关键词 Knowledge sharing Internet of vehicles Federated learning Broad learning Reconfigurable intelligent surfaces Resource allocation
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Path-Following Control With Obstacle Avoidance of Autonomous Surface Vehicles Subject to Actuator Faults 被引量:1
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作者 Li-Ying Hao Gege Dong +1 位作者 Tieshan Li Zhouhua Peng 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第4期956-964,共9页
This paper investigates the path-following control problem with obstacle avoidance of autonomous surface vehicles in the presence of actuator faults,uncertainty and external disturbances.Autonomous surface vehicles in... This paper investigates the path-following control problem with obstacle avoidance of autonomous surface vehicles in the presence of actuator faults,uncertainty and external disturbances.Autonomous surface vehicles inevitably suffer from actuator faults in complex sea environments,which may cause existing obstacle avoidance strategies to fail.To reduce the influence of actuator faults,an improved artificial potential function is constructed by introducing the lower bound of actuator efficiency factors.The nonlinear state observer,which only depends on measurable position information of the autonomous surface vehicle,is used to address uncertainties and external disturbances.By using a backstepping technique and adaptive mechanism,a path-following control strategy with obstacle avoidance and fault tolerance is designed which can ensure that the tracking errors converge to a small neighborhood of zero.Compared with existing results,the proposed control strategy has the capability of obstacle avoidance and fault tolerance simultaneously.Finally,the comparison results through simulations are given to verify the effectiveness of the proposed method. 展开更多
关键词 Actuator faults autonomous surface vehicle(ASVs) improved artificial potential function nonlinear state observer obstacle avoidance
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Integrated Active Suspension and Anti-Lock Braking Control for Four-Wheel-Independent-Drive Electric Vehicles
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作者 Ze Zhao Lei Zhang +3 位作者 Xiaoling Ding Zhiqiang Zhang Shaohua Li Liang Gu 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2024年第1期87-98,共12页
This paper presents an integrated control scheme for enhancing the ride comfort and handling performance of a four-wheel-independent-drive electric vehicle through the coordination of active suspension system(ASS)and ... This paper presents an integrated control scheme for enhancing the ride comfort and handling performance of a four-wheel-independent-drive electric vehicle through the coordination of active suspension system(ASS)and anti-lock braking system(ABS).First,a longitudinal-vertical coupled vehicle dynamics model is established by integrating a road input model.Then the coupling mechanisms between longitudinal and vertical vehicle dynamics are analyzed.An ASS-ABS integrated control system is proposed,utilizing an H∞controller for ASS to optimize load transfer effect and a neural network sliding mode control for ABS implementation.Finally,the effectiveness of the proposed control scheme is evaluated through comprehensive tests conducted on a hardware-in-loop(HIL)test platform.The HIL test results demonstrate that the proposed control scheme can significantly improve the braking performance and ride comfort compared to conventional ABS control methods. 展开更多
关键词 Four-wheel-independent-drive electric vehicles Active suspension system(ASS) Anti-lock braking system(ABS) Vertical-longitudinal vehicle dynamics
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The Future Trend of E-Mobility in Terms of Battery Electric Vehicles and Their Impact on Climate Change: A Case Study Applied in Hungary
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作者 Mohamad Ali Saleh Saleh 《American Journal of Climate Change》 2024年第2期83-102,共20页
The transportation sector is responsible for 25% of the total Carbon dioxide (CO2) emissions, whereas 60.6% of this sector represents small and medium passenger cars. However, as noted by the European Union Long-term ... The transportation sector is responsible for 25% of the total Carbon dioxide (CO2) emissions, whereas 60.6% of this sector represents small and medium passenger cars. However, as noted by the European Union Long-term strategy, there are two ways to reduce the amount of CO2 emissions in the transportation sector. The first way is characterized by creating more efficient vehicles. In contrast, the second way is characterized by changing the fuel used. The current study addressed the second way, changing the fuel type. The study examined the potential of battery electric vehicles (BEVs) as an alternative fuel type to reduce CO2 emissions in Hungarys transportation sector. The study used secondary data retrieved from Statista and stata.com to analyze the future trends of BEVs in Hungary. The results showed that the percentage of BEVs in Hungary in 2022 was 0.4% compared to the total number of registered passenger cars, which is 3.8 million. The simple exponential smoothing (SES) time series forecast revealed that the number of BEVs is expected to reach 84,192 in 2030, indicating a percentage increase of 2.21% in the next eight years. The study suggests that increasing the number of BEVs is necessary to address the negative impact of CO2 emissions on society. The Hungarian Ministry of Innovation and Technologys strategy to reduce the cost of BEVs may increase the percentage of BEVs by 10%, resulting in a potential average reduction of 76,957,600 g/km of CO2 compared to gasoline, diesel, hybrid electric vehicles (HEVs), and plug-in hybrid vehicles (PHEVs). 展开更多
关键词 Battery Electric vehicles (Bevs) GASOLINE DIESEL Hybrid Electric vehicles (Hevs) Plug-In Hybrid vehicles (PHevs) Climate Change Carbon Dioxide (CO2) Emissions
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Analysis for Effects of Temperature Rise of PV Modules upon Driving Distance of Vehicle Integrated Photovoltaic Electric Vehicles
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作者 Masafumi Yamaguchi Yasuyuki Ota +18 位作者 Taizo Masuda Christian Thiel Anastasios Tsakalidis Arnulf Jaeger-Waldau Kenji Araki Kensuke Nishioka Tatsuya Takamoto Takashi Nakado Kazumi Yamada Tsutomu Tanimoto Yosuke Tomita Yusuke Zushi Kenichi Okumura Takashi Mabuchi Akinori Satou Kyotaro Nakamura Ryo Ozaki Nobuaki Kojima Yoshio Ohshita 《Energy and Power Engineering》 2024年第4期131-150,共20页
The development of vehicle integrated photovoltaics-powered electric vehicles (VIPV-EV) significantly reduces CO<sub>2</sub> emissions from the transport sector to realize a decarbonized society. Although ... The development of vehicle integrated photovoltaics-powered electric vehicles (VIPV-EV) significantly reduces CO<sub>2</sub> emissions from the transport sector to realize a decarbonized society. Although long-distance driving of VIPV-EV without electricity charging is expected in sunny regions, driving distance of VIPV-EV is affected by climate conditions such as solar irradiation and temperature rise of PV modules. In this paper, detailed analytical results for effects of climate conditions such as solar irradiation and temperature rise of PV modules upon driving distance of the VIPV-EV were presented by using test data for Toyota Prius and Nissan Van demonstration cars installed with high-efficiency InGaP/GaAs/InGaAs 3-junction solar cell modules with a module efficiency of more than 30%. The temperature rise of some PV modules studied in this study was shown to be expressed by some coefficients related to solar irradiation, wind speed and radiative cooling. The potential of VIPV-EV to be deployed in 10 major cities was also analyzed. Although sunshine cities such as Phoenix show the high reduction ratio of driving range with 17% due to temperature rise of VIPV modules, populous cities such as Tokyo show low reduction ratio of 9%. It was also shown in this paper that the difference between the driving distance of VIPV-EV driving in the morning and the afternoon is due to PV modules’ radiative cooling. In addition, the importance of heat dissipation of PV modules and the development of high-efficiency PV modules with better temperature coefficients was suggested in order to expand driving range of VIPV-EV. The effects of air-conditioner usage and partial shading in addition to the effects of temperature rise of VIPV modules were suggested as the other power losses of VIPV-EV. 展开更多
关键词 Vehicle Integrated Photovoltaics (VIPV) VIPV-Powered Electric vehicles Driving Distance PV Modules Solar Irradiation Temperature Rise Radiative Cooling
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A Blockchain-Based Efficient Cross-Domain Authentication Scheme for Internet of Vehicles
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作者 Feng Zhao Hongtao Ding +3 位作者 Chunhai Li Zhaoyu Su Guoling Liang Changsong Yang 《Computers, Materials & Continua》 SCIE EI 2024年第7期567-585,共19页
The Internet of Vehicles(IoV)is extensively deployed in outdoor and open environments to effectively address traffic efficiency and safety issues by connecting vehicles to the network.However,due to the open and varia... The Internet of Vehicles(IoV)is extensively deployed in outdoor and open environments to effectively address traffic efficiency and safety issues by connecting vehicles to the network.However,due to the open and variable nature of its network topology,vehicles frequently engage in cross-domain interactions.During such processes,directly uploading sensitive information to roadside units for interaction may expose it to malicious tampering or interception by attackers,thus compromising the security of the cross-domain authentication process.Additionally,IoV imposes high real-time requirements,and existing cross-domain authentication schemes for IoV often encounter efficiency issues.To mitigate these challenges,we propose CAIoV,a blockchain-based efficient cross-domain authentication scheme for IoV.This scheme comprehensively integrates technologies such as zero-knowledge proofs,smart contracts,and Merkle hash tree structures.It divides the cross-domain process into anonymous cross-domain authentication and safe cross-domain authentication phases to ensure efficiency while maintaining a balance between efficiency and security.Finally,we evaluate the performance of CAIoV.Experimental results demonstrate that our proposed scheme reduces computational overhead by approximately 20%,communication overhead by around 10%,and storage overhead by nearly 30%. 展开更多
关键词 Blockchain cross-domain authentication internet of vehicle zero-knowledge proof
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Survey on digital twins for Internet of Vehicles:Fundamentals,challenges,and opportunities
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作者 Jiajie Guo Muhammad Bilal +3 位作者 Yuying Qiu Cheng Qian Xiaolong Xu Kim-Kwang Raymond Choo 《Digital Communications and Networks》 SCIE CSCD 2024年第2期237-247,共11页
As autonomous vehicles and the other supporting infrastructures(e.g.,smart cities and intelligent transportation systems)become more commonplace,the Internet of Vehicles(IoV)is getting increasingly prevalent.There hav... As autonomous vehicles and the other supporting infrastructures(e.g.,smart cities and intelligent transportation systems)become more commonplace,the Internet of Vehicles(IoV)is getting increasingly prevalent.There have been attempts to utilize Digital Twins(DTs)to facilitate the design,evaluation,and deployment of IoV-based systems,for example by supporting high-fidelity modeling,real-time monitoring,and advanced predictive capabilities.However,the literature review undertaken in this paper suggests that integrating DTs into IoV-based system design and deployment remains an understudied topic.In addition,this paper explains how DTs can benefit IoV system designers and implementers,as well as describes several challenges and opportunities for future researchers. 展开更多
关键词 Internet of vehicles Digital twin Simulation Traffic systems
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Blockchain-Enabled Federated Learning with Differential Privacy for Internet of Vehicles
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作者 Chi Cui Haiping Du +2 位作者 Zhijuan Jia Yuchu He Lipeng Wang 《Computers, Materials & Continua》 SCIE EI 2024年第10期1581-1593,共13页
The rapid evolution of artificial intelligence(AI)technologies has significantly propelled the advancement of the Internet of Vehicles(IoV).With AI support,represented by machine learning technology,vehicles gain the ... The rapid evolution of artificial intelligence(AI)technologies has significantly propelled the advancement of the Internet of Vehicles(IoV).With AI support,represented by machine learning technology,vehicles gain the capability to make intelligent decisions.As a distributed learning paradigm,federated learning(FL)has emerged as a preferred solution in IoV.Compared to traditional centralized machine learning,FL reduces communication overhead and improves privacy protection.Despite these benefits,FL still faces some security and privacy concerns,such as poisoning attacks and inference attacks,prompting exploration into blockchain integration to enhance its security posture.This paper introduces a novel blockchain-enabled federated learning(BCFL)scheme with differential privacy(DP)tailored for IoV.In order to meet the performance demanding IoV environment,the proposed methodology integrates a consortium blockchain with Practical Byzantine Fault Tolerance(PBFT)consensus,which offers superior efficiency over the conventional public blockchains.In addition,the proposed approach utilizes the Differentially Private Stochastic Gradient Descent(DP-SGD)algorithm in the local training process of FL for enhanced privacy protection.Experiment results indicate that the integration of blockchain elevates the security level of FL in that the proposed approach effectively safeguards FL against poisoning attacks.On the other hand,the additional overhead associated with blockchain integration is also limited to a moderate level to meet the efficiency criteria of IoV.Furthermore,by incorporating DP,the proposed approach is shown to have the(ε-δ)privacy guarantee while maintaining an acceptable level of model accuracy.This enhancement effectively mitigates the threat of inference attacks on private information. 展开更多
关键词 Blockchain federated learning differential privacy Internet of vehicles
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EVS系统在演播室体育赛事转播中的应用
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作者 祝焕东 《电视技术》 2024年第3期71-74,共4页
基于增强语音服务(Enhanced Voice Services, EVS)在体育赛事转播中的应用,对其系统组成、组织架构和应用场景等进行深入研究,以期提高演播室体育赛事转播的质量和效率。
关键词 增强语音服务(evs) 语音编解码 体育赛事转播 组织架构
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Toward Trustworthy Decision-Making for Autonomous Vehicles:A Robust Reinforcement Learning Approach with Safety Guarantees
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作者 Xiangkun He Wenhui Huang Chen Lv 《Engineering》 SCIE EI CAS CSCD 2024年第2期77-89,共13页
While autonomous vehicles are vital components of intelligent transportation systems,ensuring the trustworthiness of decision-making remains a substantial challenge in realizing autonomous driving.Therefore,we present... While autonomous vehicles are vital components of intelligent transportation systems,ensuring the trustworthiness of decision-making remains a substantial challenge in realizing autonomous driving.Therefore,we present a novel robust reinforcement learning approach with safety guarantees to attain trustworthy decision-making for autonomous vehicles.The proposed technique ensures decision trustworthiness in terms of policy robustness and collision safety.Specifically,an adversary model is learned online to simulate the worst-case uncertainty by approximating the optimal adversarial perturbations on the observed states and environmental dynamics.In addition,an adversarial robust actor-critic algorithm is developed to enable the agent to learn robust policies against perturbations in observations and dynamics.Moreover,we devise a safety mask to guarantee the collision safety of the autonomous driving agent during both the training and testing processes using an interpretable knowledge model known as the Responsibility-Sensitive Safety Model.Finally,the proposed approach is evaluated through both simulations and experiments.These results indicate that the autonomous driving agent can make trustworthy decisions and drastically reduce the number of collisions through robust safety policies. 展开更多
关键词 Autonomous vehicle DECISION-MAKING Reinforcement learning Adversarial attack Safety guarantee
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FADSF:A Data Sharing Model for Intelligent Connected Vehicles Based on Blockchain Technology
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作者 Yan Sun Caiyun Liu +1 位作者 Jun Li Yitong Liu 《Computers, Materials & Continua》 SCIE EI 2024年第8期2351-2362,共12页
With the development of technology,the connected vehicle has been upgraded from a traditional transport vehicle to an information terminal and energy storage terminal.The data of ICV(intelligent connected vehicles)is ... With the development of technology,the connected vehicle has been upgraded from a traditional transport vehicle to an information terminal and energy storage terminal.The data of ICV(intelligent connected vehicles)is the key to organically maximizing their efficiency.However,in the context of increasingly strict global data security supervision and compliance,numerous problems,including complex types of connected vehicle data,poor data collaboration between the IT(information technology)domain and OT(operation technology)domain,different data format standards,lack of shared trust sources,difficulty in ensuring the quality of shared data,lack of data control rights,as well as difficulty in defining data ownership,make vehicle data sharing face a lot of problems,and data islands are widespread.This study proposes FADSF(Fuzzy Anonymous Data Share Frame),an automobile data sharing scheme based on blockchain.The data holder publishes the shared data information and forms the corresponding label storage on the blockchain.The data demander browses the data directory information to select and purchase data assets and verify them.The data demander selects and purchases data assets and verifies them by browsing the data directory information.Meanwhile,this paper designs a data structure Data Discrimination Bloom Filter(DDBF),making complaints about illegal data.When the number of data complaints reaches the threshold,the audit traceability contract is triggered to punish the illegal data publisher,aiming to improve the data quality and maintain a good data sharing ecology.In this paper,based on Ethereum,the above scheme is tested to demonstrate its feasibility,efficiency and security. 展开更多
关键词 Blockchain connected vehicles data sharing smart contracts credible traceability
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Multi-circular formation control with reinforced transient profiles for nonholonomic vehicles:A path-following framework
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作者 Jintao Zhang Xingling Shao +1 位作者 Wendong Zhang Zongyu Zuo 《Defence Technology(防务技术)》 SCIE EI CAS CSCD 2024年第1期278-287,共10页
This article investigates a multi-circular path-following formation control with reinforced transient profiles for nonholonomic vehicles connected by a digraph.A multi-circular formation controller endowed with the fe... This article investigates a multi-circular path-following formation control with reinforced transient profiles for nonholonomic vehicles connected by a digraph.A multi-circular formation controller endowed with the feature of spatial-temporal decoupling is devised for a group of vehicles guided by a virtual leader evolving along an implicit path,which allows for a circumnavigation on multiple circles with an anticipant angular spacing.In addition,notice that it typically imposes a stringent time constraint on time-sensitive enclosing scenarios,hence an improved prescribed performance control(IPPC)using novel tighter behavior boundaries is presented to enhance transient capabilities with an ensured appointed-time convergence free from any overshoots.The significant merits are that coordinated circumnavigation along different circles can be realized via executing geometric and dynamic assignments independently with modified transient profiles.Furthermore,all variables existing in the entire system are analyzed to be convergent.Simulation and experimental results are provided to validate the utility of suggested solution. 展开更多
关键词 Multi-circular formation Reinforced transient profiles Nonholonomic vehicles Path following
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Alternating current heating techniques for lithium-ion batteries in electric vehicles:Recent advances and perspectives
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作者 Xinrong Huang Jinhao Meng +5 位作者 Wei Jiang Wenjie Liu Kailong Liu Yipu Zhang Daniel-Ioan Stroe Remus Teodorescu 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2024年第9期679-697,共19页
The significant decrease in battery performance at low temperatures is one of the critical challenges that electric vehicles(EVs)face,thereby affecting the penetration rate in cold regions.Alternating current(AC)heati... The significant decrease in battery performance at low temperatures is one of the critical challenges that electric vehicles(EVs)face,thereby affecting the penetration rate in cold regions.Alternating current(AC)heating has attracted widespread attention due to its low energy consumption and uniform heating advantages.This paper introduces the recent advances in AC heating from the perspective of practical EV applications.First,the performance degradation of EVs in low-temperature environments is introduced briefly.The concept of AC heating and its research methods are provided.Then,the effects of various AC heating methods on battery heating performance are reviewed.Based on existing studies,the main factors that affect AC heating performance are analyzed.Moreover,various heating circuits based on EVs are categorized,and their cost,size,complexity,efficiency,reliability,and heating rate are elaborated and compared.The evolution of AC heaters is presented,and the heaters used in brand vehicles are sorted out.Finally,the perspectives and challenges of AC heating are discussed.This paper can guide the selection of heater implementation methods and the optimization of heating effects for future EV applications. 展开更多
关键词 Lithium-ion battery Low temperature Alternating current heating HEATER Electric vehicle
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General Optimal Trajectory Planning:Enabling Autonomous Vehicles with the Principle of Least Action
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作者 Heye Huang Yicong Liu +4 位作者 Jinxin Liu Qisong Yang Jianqiang Wang David Abbink Arkady Zgonnikov 《Engineering》 SCIE EI CAS CSCD 2024年第2期63-76,共14页
This study presents a general optimal trajectory planning(GOTP)framework for autonomous vehicles(AVs)that can effectively avoid obstacles and guide AVs to complete driving tasks safely and efficiently.Firstly,we emplo... This study presents a general optimal trajectory planning(GOTP)framework for autonomous vehicles(AVs)that can effectively avoid obstacles and guide AVs to complete driving tasks safely and efficiently.Firstly,we employ the fifth-order Bezier curve to generate and smooth the reference path along the road centerline.Cartesian coordinates are then transformed to achieve the curvature continuity of the generated curve.Considering the road constraints and vehicle dynamics,limited polynomial candidate trajectories are generated and smoothed in a curvilinear coordinate system.Furthermore,in selecting the optimal trajectory,we develop a unified and auto-tune objective function based on the principle of least action by employing AVs to simulate drivers’behavior and summarizing their manipulation characteristics of“seeking benefits and avoiding losses.”Finally,by integrating the idea of receding-horizon optimization,the proposed framework is achieved by considering dynamic multi-performance objectives and selecting trajectories that satisfy feasibility,optimality,and adaptability.Extensive simulations and experiments are performed,and the results demonstrate the framework’s feasibility and effectiveness,which avoids both dynamic and static obstacles and applies to various scenarios with multi-source interactive traffic participants.Moreover,we prove that the proposed method can guarantee real-time planning and safety requirements compared to drivers’manipulation. 展开更多
关键词 Autonomous vehicle Trajectory planning Multi-performance objectives Principle of least action
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