A Dynamic and Scalable User-Centric Route Planning Algorithm Based on Polychromatic Sets Theory

Li, Peisong; Wang, Xinheng; Gao, Honghao; Xu, Xiaolong; Iqbal, Muddesar; Dahal, Keshav

doi:10.1109/tits.2021.3085026

Cited by 26 publications

(7 citation statements)

References 25 publications

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“…The polychromatic sets theory uses the concept of "contour" to abstract and generalizes concepts such as properties, attributes, characteristics, and parameters of objects in actual systems [14]. As a mathematical tool for information processing, it has more advantages than other modeling tools such as Petri nets and unified modeling language (UML) [13], [15] . In addition, this theory is also widely used in the reverse design for remanufacturing (RDfRem) method [16], unmanned aerial vehicle (UAV) route planning application [17], product information model construction [18], the design improvement of the electric multiple unit (EMU) bogie system [19], and many other fields.…”

Section: B Flow Analysis Modelmentioning

confidence: 99%

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Research on Judgment and Solving Strategy of Flow Problems in Complex Engineering Systems

Zhang

et al. 2023

IEEE Access

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Frequent processes of mutual transfer and transformation generally take place between the material flow, the energy flow, and the information flow in complex engineering systems, and complex coupling relationships exist between the different flows. Abnormal coupling of flows will cause flow problems, which can easily lead to the failure of the system functions. To address these problems, in this study, the starting point has been taken as the change in the attributes and types of the study flow, the attributes of the flows have been categorized, and a flow transfer and transformation model, oriented to the flow problem analysis has been proposed. Secondly, based on the analysis of the effect of the attribute changes of flows in complex engineering systems on the generation of flow problems, an innovatively introduced information processing mathematical tool, the polychromatic sets theory, has been used to explore and determine the flow problems existing in complex engineering systems. Further, depending on the different manifestations of flow problems, three solution strategies have been proposed. Finally, the process model of the flow problem judgment and a solution strategy for complex engineering systems has been constructed. The feasibility of the process model has been verified by considering the engineering case of the tubular feeding machine (TFM) system of a large-scale integrated marine resource survey ship.INDEX TERMS Complex engineering system, polychromatic sets, flow problem judgment, solving strategy, tubular feeding machine (TFM) system.

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Section: B Flow Analysis Modelmentioning

confidence: 99%

“…The polychromatic sets theory has been formed by combining fuzzy mathematics, mathematical logic, and matrix knowledge on the basis of a traditional set [13], [15]- [19]. The polychromatic sets are mainly composed of six components, as given in Equation (1).…”

Section: ) Concepts Related To Polychromatic Setsmentioning

confidence: 99%

Research on Judgment and Solving Strategy of Flow Problems in Complex Engineering Systems

Zhang

et al. 2023

IEEE Access

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“…Security has always been an important research area, especially in the current era of Internet of Everything and big data [8–12]. As the core technology for security in the large‐scale multi‐node, mobile, dynamic wireless network environment, authentication plays a pivotal role.…”

Section: Related Workmentioning

confidence: 99%

“…Security has always been an important research area, especially in the current era of Internet of Everything and big data [8][9][10][11][12].…”

Section: Related Workmentioning

confidence: 99%

A PUF‐based lightweight authentication and key agreement protocol for smart UAV networks

Zhang

Obaidat

et al. 2021

IET Communications

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With the advancement of information technology and the reduction of costs, the application of unmanned aerial vehicle (UAV) has gradually expanded from the military field to the industrial field and civilian field. It brings great convenience to people in surveillance, detection, transportation, emergency rescue etc. However, UAVs usually work in harsh natural environments, and their communication security confronts various challenges. Due to UAVs' limited resources, such as computing capability, storage space, and energy, traditional security protection schemes based on complex cryptographic algorithms are not suitable for UAV systems directly. Therefore, a two‐stage lightweight identity authentication and key agreement protocol for UAV is proposed in this paper. The entire process only uses hash and XOR operations, which significantly improves the authentication efficiency. Simultaneously, the physical unclonable function (PUF) is introduced and embedded into the UAV hardware to ensure UAV network communication security when a UAV suffers a physical capture attack. In the paper, the security of the proposed protocol is proved with Burrows–Abadi–Needham (BAN) logic, Real‐or‐Random (ROR) model, and AVISPA simulation tools. An informal security analysis is also provided to illustrate that the protocol satisfies the security requirements of UAV networks. Finally, the protocol is compared with other existing protocols regarding function properties, computation cost, and communication cost, which shows that the proposed protocol has effectiveness and practicality.

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“…In particular, since the drivers have very diverse preferences when it comes to choosing charging stations, we take a driver-centric approach and are interested in using artificial intelligence (AI) tools to plan the drivers' stops over long distances, while taking into account their individual preferences (e.g., balancing cost, travel time, charging time, and facilities at charging stations). In spite of the fact that existing work [11,16,20] has examined personalised routing, it does not address dynamic preference elicitation.…”

Section: Introductionmentioning

confidence: 99%

Personalised Electric Vehicle Charging Stop Planning Through Online Estimators

Shafipour,

Stein,

Ahipasaoglu

2023

Preprint

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In this paper, we address the problem of finding charging stops while travelling in electric vehicles (EVs) using artificial intelligence (AI). Choosing a charging station is challenging, because drivers have very heterogeneous preferences in terms of how they trade off the features of various alternatives (for example, regarding the time spent driving, charging costs, waiting times at charging stations, and the facilities provided at the charging stations). The key problem here is eliciting the diverse preferences of drivers, assuming that these preferences are typically not fully known a priori, and then planning stops based on each driver's preferences. Our approach to solving this problem is to develop an intelligent personal agent that learns preferences gradually over multiple interactions. This study proposes a new technique that utilises a small-scale discrete choice experiment as a method of interacting with the driver in order to minimise the cognitive burden on the driver. Using this method, drivers are presented with a variety of routes with possible combinations of charging stops depending on the agent's latest belief about their preferences. In subsequent iterations, the personal agent will continue to learn and refine its belief about the driver's preferences, suggesting more personalised routes that are closer to the driver's preferences. Based on real preference data from EV drivers, we evaluate our novel algorithm and show that, after only a few queries, our method quickly converges to the optimal routes for EV drivers.

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A Dynamic and Scalable User-Centric Route Planning Algorithm Based on Polychromatic Sets Theory

Cited by 26 publications

References 25 publications

Research on Judgment and Solving Strategy of Flow Problems in Complex Engineering Systems

Research on Judgment and Solving Strategy of Flow Problems in Complex Engineering Systems

A PUF‐based lightweight authentication and key agreement protocol for smart UAV networks

Personalised Electric Vehicle Charging Stop Planning Through Online Estimators

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