1,746 research outputs found

    High Accuracy Distributed Target Detection and Classification in Sensor Networks Based on Mobile Agent Framework

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    High-accuracy distributed information exploitation plays an important role in sensor networks. This dissertation describes a mobile-agent-based framework for target detection and classification in sensor networks. Specifically, we tackle the challenging problems of multiple- target detection, high-fidelity target classification, and unknown-target identification. In this dissertation, we present a progressive multiple-target detection approach to estimate the number of targets sequentially and implement it using a mobile-agent framework. To further improve the performance, we present a cluster-based distributed approach where the estimated results from different clusters are fused. Experimental results show that the distributed scheme with the Bayesian fusion method have better performance in the sense that they have the highest detection probability and the most stable performance. In addition, the progressive intra-cluster estimation can reduce data transmission by 83.22% and conserve energy by 81.64% compared to the centralized scheme. For collaborative target classification, we develop a general purpose multi-modality, multi-sensor fusion hierarchy for information integration in sensor networks. The hierarchy is com- posed of four levels of enabling algorithms: local signal processing, temporal fusion, multi-modality fusion, and multi-sensor fusion using a mobile-agent-based framework. The fusion hierarchy ensures fault tolerance and thus generates robust results. In the meanwhile, it also takes into account energy efficiency. Experimental results based on two field demos show constant improvement of classification accuracy over different levels of the hierarchy. Unknown target identification in sensor networks corresponds to the capability of detecting targets without any a priori information, and of modifying the knowledge base dynamically. In this dissertation, we present a collaborative method to solve this problem among multiple sensors. When applied to the military vehicles data set collected in a field demo, about 80% unknown target samples can be recognized correctly, while the known target classification ac- curacy stays above 95%

    Visible Light Communication Survey

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    Rail freight automation in Shift2Rail – Development of prototypes

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    The Shift2Rail pillar “Technologies for attractive and sustainable European Freight” (IP5) has a clear target vision, which can be summarized in two words: Digitization & Automation. The IP5 members want to speed up the digital transformation and automation of rail freight to ultimately gain market share in the competitive race with other modes of transport. In order to advance automation, multiple projects have been launched under funding. Two key technology demonstrators are presented in this paper: 1. Semi-Automated Operation with Distributed Power Systems (DPS) for efficient Master-Slave Operation, e.g. push-pull operation or in long and heavy trains up to 1,500 m 2. Automatic Train Operation (ATO) with Obstacle Detection (OD) on network sections with European Train Control System (ETCS) from Level 2 upward

    Internal report cluster 1: Urban freight innovations and solutions for sustainable deliveries (2/4)

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    Technical report about sustainable urban freight solutions, part 2 of

    MAVEN Deliverable 7.2: Impact Assessment - Technical Report

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    This deliverable focuses on an important topic within the MAVEN project - evaluation of the project impact. This is an important step that will allow us to say what the results and impact of the different technologies, functionalities as well as assumptions are. It covers different dimensions of the impact assessment as stated in the Deliverable D7.1 - Impact assessment plan [10]. The field tests proved that the technology in the vehicle works together with the infrastructure and the solution is technically feasible. This was demonstrated also during particular events and is reported in the attached test protocols. At the same time, the emulation and simulation in Dominion software proved the functionality, for example with respect to the cooperative perception or safety indicators. The tests also proved that the key performance indicator "minimum time to the collision" decreases when applying the cooperative sensing. Also, the number of human interventions needed was zero in all the tests. This deliverable also discussed selected results of a detailed user survey aiming at understanding the expected impacts and transition of automated vehicles. The overall number of respondents reached 209. The responses have revealed some interesting facts. For example, over 80% of the respondents believe that CAVs will decrease the number of traffic accidents. Similarly, about 70% of the respondents expect improvements in traffic congestions. Over 82% of respondents declared that they would accept some detour when driving if it helps the overall traffic situation. The literature review, however, indicated that autonomous vehicles will have either a positive or a negative effect on the environment, depending on the policies. For example, opening cars as a mode of transport to new user groups (seniors, children etc.) together with improvements of the traffic, flow parameters can increase the traffic volume on roads. Policy makers shall focus on the integration of the CAVs into a broader policy concept including car or ride-sharing, electromobility and others. In order to evaluate the transition, for example, the influence of different penetration rates of CAVs on the performance, a microscopic traffic simulation was performed. Here the particular MAVEN use cases, as well as their combination, was addressed. The results of the simulation are rather promising. The potential for improvements in traffic performance is clearly there. It was demonstrated that a proper integration of CAVs into city traffic management can, for example, help with respect to the environmental goals (Climate Action of the European Commission) and reduce CO2 emissions by up to 12 % (a combination of GLOSA and signal optimization). On corridors with a green wave, a capacity increase of up to 34% was achieved. The conclusions from this project can be used not only by other researchers but mainly by traffic managers and decision-makers in cities. The findings can get a better idea about the real impacts of particular use cases (such as green wave, GLOSA and others) in the cities. An important added value is also the focus on the transition phase. It was demonstrated that already for lower penetration rates (even 20% penetration of automated vehicles), there are significant improvements in traffic performance. For example, the platooning leads to a decrease of CO2 emissions of 2,6% or the impact indicator by 17,7%

    The Critical Role of Public Charging Infrastructure

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    Editors: Peter Fox-Penner, PhD, Z. Justin Ren, PhD, David O. JermainA decade after the launch of the contemporary global electric vehicle (EV) market, most cities face a major challenge preparing for rising EV demand. Some cities, and the leaders who shape them, are meeting and even leading demand for EV infrastructure. This book aggregates deep, groundbreaking research in the areas of urban EV deployment for city managers, private developers, urban planners, and utilities who want to understand and lead change

    The Pull Paradigm : foundations of user-centric advanced driver assistant systems based on bidirectional car2X communication

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    This thesis develops applications for vehicular ad-hoc networks that go far beyond the currently established areas of driving safety and traffic efficiency. The ad-hoc network is regarded as a dynamic information resource which is available to any vehicle at any time. In contrast to current state-of-the-art research, the proposed Pull Paradigm starts at the user\u27s vehicle rather than at an information source somewhere in the network, e.g. a braking car. To access information from highly dynamic ad-hoc networks, bidirectional communication and information discovery and retrieval play a vital role. Therefore, in the course of the work, the applicability of the Pull Paradigm to established vehicular ad-hoc networks is thoroughly examined and missing aspects are identified. It turns out that a number of enhancements to almost all layers of the network stack are necessary in order to apply the Pull Paradigm using existing technology. The central elements here are two novel algorithms for managing information flow and dissemination in ad-hoc networks, which are at first formulated from the abstract perspective of graph theory. Using the knowledge gained leads to the development of PADE, a platform that supports development of vehicular ad-hoc network applications. The designed algorithms are then implemented as a routing scheme, integrated and evaluated in large, simulated city scenarios. Furthermore, PADE combines real\u27\u27 and simulated communication technologies and abstracts from them, so that applications can be transferred from the lab into a test vehicle with minimal effort. In order to achieve this ambitious goal, PADE builds on a number of existing simulation and communication technologies. The practical applicability of the Pull approach is shown in two demonstrators that are integrated into a BMW 5 series test vehicle. The presentation module of the PADE platform was tested in the currently largest field operational test for vehicular ad-hoc communication. Over 400 drivers in 120 vehicles experienced the system on a daily basis.In dieser Doktorarbeit werden Anwendungen für Fahrzeug Ad-hoc Netzwerke erarbeitet, die weit über die derzeit etablierten Bereiche der Fahrsicherheit und Verkehrseffizienz hinausgehen. Das Ad-hoc Netzwerk wird dabei als dynamische Informationsressource angesehen, die jedem Fahrzeug zu jedem Zeitpunkt zur Verfügung steht. Im Gegensatz zum derzeitigen Stand der Forschung geht das vorgestellte Pull Paradigma vom Fahrzeug des Benutzers und nicht von der Informationsquelle aus, z.B. einem bremsenden Fahrzeug. Für den Zugriff auf Informationen aus hochdynamischen Ad-hoc Netzen, spielen bidirektionale Kommunikation, Informationssuche und -rücktransport eine entscheidende Rolle. Im Verlauf der Arbeit wird deshalb die Anwendbarkeit des Pull Paradigmas auf etablierte Fahrzeug Ad-hoc Netze untersucht und fehlende Aspekte identifiziert. Es zeigt sich, dass eine Reihe an Erweiterungen auf fast allen Ebenen des Netzwerkstapels nötig sind damit die bestehende Technologie um das Pull Paradigma erweitert werden kann. Zentraler Punkt hierbei sind zwei neuartige Algorithmen zur Informationsverwaltung und -verbreitung in Ad-hoc Netzwerken die zunächst abstrakt aus Sicht der Graphentheorie formuliert werden. Mit Hilfe der gewonnenen Erkenntnisse wird PADE, eine Plattform zur Entwicklung von Anwendungen für Fahrzeug Ad-hoc Netze, entwickelt. Die entworfenen Algorithmen werden dann als Routingverfahren im Netzwerkstapel realisiert, in diesen integriert und auf großflächigen Stadtszenarien im Simulator evaluiert. Des Weiteren vereint PADE echte\u27\u27 und simulierte Kommunikationstechnologien und abstrahiert von diesen, sodass Anwendungen mit minimalem Aufwand vom Labor in ein Testfahrzeug überführt werden können. Um dieses ambitionierte Ziel zu erreichen, wird auf einer Reihe bereits bestehender Simulations- und Kommunikationstechnologien aufgebaut. Die praktische Anwendbarkeit des Pull Paradigmas wird anschließend in zwei Demonstratoren implementiert und in ein BMW 5er Testfahrzeug integriert. Das Präsentationsmodul der PADE Plattform wurde im derzeit weltgrößten Feldversuch für Fahrzeug Ad-hoc Kommunikation von über 400 Fahrern in 120 Fahrzeugen im Alltag getestet

    Strategic and Tactical Guidance for the Connected and Autonomous Vehicle Future

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    Autonomous vehicle (AV) and Connected vehicle (CV) technologies are rapidly maturing and the timeline for their wider deployment is currently uncertain. These technologies are expected to have a number of significant societal benefits: traffic safety, improved mobility, improved road efficiency, reduced cost of congestion, reduced energy use, and reduced fuel emissions. State and local transportation agencies need to understand what this means for them and what they need to do now and in the next few years to prepare for the AV/CV future. In this context, the objectives of this research are as follows: Synthesize the existing state of practice and how other state agencies are addressing the pending transition to AV/CV environment Estimate the impacts of AV/CV environment within the context of (a) traffic operations—impact of headway distribution and traffic signal coordination; (b) traffic control devices; (c) roadway safety in terms of intersection crashes Provide a strategic roadmap for INDOT in preparing for and responding to potential issues This research is divided into two parts. The first part is a synthesis study of existing state of practice in the AV/CV context by conducting an extensive literature review and interviews with other transportation agencies. Based on this, we develop a roadmap for INDOT and similar agencies clearly delineating how they should invest in AV/CV technologies in the short, medium, and long term. The second part assesses the impacts of AV/CVs on mobility and safety via modeling in microsimulation software Vissim
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