Design choices for agent-based control of AGVs in the dough making process

In this paper we consider a multi-agent system (MAS) for the logistics control of Automatic Guided Vehicles (AGVs) that are used in the dough making process at an industrial bakery. Here, logistics control refers to constructing robust schedules for all transportation jobs. The paper discusses how alternative MAS designs can be developed and compared using cost, frequency of messages between agents, and computation time for evaluating control rules as performance indicators. Qualitative design guidelines turn out to be insufficient to select the best agent architecture. Therefore, we also use simulation to support decision making, where we use real-life data from the bakery to evaluate several alternative designs. We find that architectures in which line agents initiate allocation of transportation jobs, and AGV agents schedule multiple jobs in advance, perform best. We conclude by discussing the benefits of our MAS systems design approach for real-life applications

Development and Performance Evaluation of a Connected Vehicle Application Development Platform (CVDeP)

Connected vehicle (CV) application developers need a development platform to build, test and debug real-world CV applications, such as safety, mobility, and environmental applications, in edge-centric cyber-physical systems. Our study objective is to develop and evaluate a scalable and secure CV application development platform (CVDeP) that enables application developers to build, test and debug CV applications in realtime. CVDeP ensures that the functional requirements of the CV applications meet the corresponding requirements imposed by the specific applications. We evaluated the efficacy of CVDeP using two CV applications (one safety and one mobility application) and validated them through a field experiment at the Clemson University Connected Vehicle Testbed (CU-CVT). Analyses prove the efficacy of CVDeP, which satisfies the functional requirements (i.e., latency and throughput) of a CV application while maintaining scalability and security of the platform and applications

Managing nonuniformities and uncertainties in vehicle-oriented sensor data over next generation networks

Detailed and accurate vehicle-oriented sensor data is considered fundamental for efficient vehicle-to-everything V2X communication applications, especially in the upcoming highly heterogeneous, brisk and agile 5G networking era. Information retrieval, transfer and manipulation in real-time offers a small margin for erratic behavior, regardless of its root cause. This paper presents a method for managing nonuniformities and uncertainties found on datasets, based on an elaborate Matrix Completion technique, with superior performance in three distinct cases of vehicle-related sensor data, collected under real driving conditions. Our approach appears capable of handling sensing and communication irregularities, minimizing at the same time the storage and transmission requirements of Multi-access Edge Computing applications

Artificial intelligence and UK national security: Policy considerations

RUSI was commissioned by GCHQ to conduct an independent research study into the use of artificial intelligence (AI) for national security purposes. The aim of this project is to establish an independent evidence base to inform future policy development regarding national security uses of AI. The findings are based on in-depth consultation with stakeholders from across the UK national security community, law enforcement agencies, private sector companies, academic and legal experts, and civil society representatives. This was complemented by a targeted review of existing literature on the topic of AI and national security. The research has found that AI offers numerous opportunities for the UK national security community to improve efficiency and effectiveness of existing processes. AI methods can rapidly derive insights from large, disparate datasets and identify connections that would otherwise go unnoticed by human operators. However, in the context of national security and the powers given to UK intelligence agencies, use of AI could give rise to additional privacy and human rights considerations which would need to be assessed within the existing legal and regulatory framework. For this reason, enhanced policy and guidance is needed to ensure the privacy and human rights implications of national security uses of AI are reviewed on an ongoing basis as new analysis methods are applied to data

Scenarios of Electromobility. Cross ferilisation and Dissemination of Best Practices and Researches within EU Policies Webinar proceedings

La pubblicazione riporta gli esiti del webinar incentrato sull'user center design dei veicoli elettrici, delle loro infrastrutture di ricarica e sulle sperimentazioni dei veicoli elettrici leggeri nei sistemi di trasporto urbano di Torino e Venaria Reale (IT), Villach (Austria) e Calvià (Spagna). La pubblicazione e il seminario sono parte del progetto STEVE, finanziato dal programma europeo Horizon2020, e incentrato sulla sperimentazione di modelli di mobilità elettrica leggera nelle aree urbane. Il progetto ha coinvolto città, piccole e medie imprese e università di sette paesi europei. Urban Lab ha collaborato con la Città di Torino a delineare le raccomandazioni rivolte ai decision makers in materia di pianificazione della mobilità urbana, emerse dai risultati dei tre anni di progetto

Named Data Networking in Vehicular Ad hoc Networks: State-of-the-Art and Challenges

International audienceInformation-Centric Networking (ICN) has been proposed as one of the future Internet architectures. It is poised to address the challenges faced by today's Internet that include, but not limited to, scalability, addressing, security, and privacy. Furthermore, it also aims at meeting the requirements for new emerging Internet applications. To realize ICN, Named Data Networking (NDN) is one of the recent implementations of ICN that provides a suitable communication approach due to its clean slate design and simple communication model. There are a plethora of applications realized through ICN in different domains where data is the focal point of communication. One such domain is Intelligent Transportation System (ITS) realized through Vehicular Ad hoc NETwork (VANET) where vehicles exchange information and content with each other and with the infrastructure. To date, excellent research results have been yielded in the VANET domain aiming at safe, reliable, and infotainment-rich driving experience. However, due to the dynamic topologies, host-centric model, and ephemeral nature of vehicular communication, various challenges are faced by VANET that hinder the realization of successful vehicular networks and adversely affect the data dissemination, content delivery, and user experiences. To fill these gaps, NDN has been extensively used as underlying communication paradigm for VANET. Inspired by the extensive research results in NDN-based VANET, in this paper, we provide a detailed and systematic review of NDN-driven VANET. More precisely, we investigate the role of NDN in VANET and discuss the feasibility of NDN architecture in VANET environment. Subsequently, we cover in detail, NDN-based naming, routing and forwarding, caching, mobility, and security mechanism for VANET. Furthermore, we discuss the existing standards, solutions, and simulation tools used in NDN-based VANET. Finally, we also identify open challenges and issues faced by NDN-driven VANET and highlight future research directions that should be addressed by the research community

The future roadmap of in-vehicle network processing: a HW-centric (R-)evolution

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The automotive industry is undergoing a deep revolution. With the race towards autonomous driving, the amount of technologies, sensors and actuators that need to be integrated in the vehicle increases exponentially. This imposes new great challenges in the vehicle electric/electronic (E/E) architecture and, especially, in the In-Vehicle Network (IVN). In this work, we analyze the evolution of IVNs, and focus on the main network processing platform integrated in them: the Gateway (GW). We derive the requirements of Network Processing Platforms that need to be fulfilled by future GW controllers focusing on two perspectives: functional requirements and structural requirements. Functional requirements refer to the functionalities that need to be delivered by these network processing platforms. Structural requirements refer to design aspects which ensure the feasibility, usability and future evolution of the design. By focusing on the Network Processing architecture, we review the available options in the state of the art, both in industry and academia. We evaluate the strengths and weaknesses of each architecture in terms of the coverage provided for the functional and structural requirements. In our analysis, we detect a gap in this area: there is currently no architecture fulfilling all the requirements of future automotive GW controllers. In light of the available network processing architectures and the current technology landscape, we identify Hardware (HW) accelerators and custom processor design as a key differentiation factor which boosts the devices performance. From our perspective, this points to a need - and a research opportunity - to explore network processing architectures with a strong HW focus, unleashing the potential of next-generation network processors and supporting the demanding requirements of future autonomous and connected vehicles.Peer ReviewedPostprint (published version