54 research outputs found

    Distributed Decision Making for V2v Charge Sharing in Intelligent Transportation Systems

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    Electric vehicles (EVs) have emerged in the intelligent transportation system (ITS) to meet the increasing environmental concerns. To facilitate on-demand requirement of EV charging, vehicle-to-vehicle (V2V) charge transfer can be employed. However, most of the existing approaches to V2V charge sharing are centralized or semi-centralized, incurring huge message overhead, long waiting time, and infrastructural cost. In this paper, we propose novel distributed heuristic algorithms for V2V charge sharing based on the multi-criteria decision-making policy. The problem is mapped to an alias classical problem (i.e., optimum matching in weighted bipartite graphs), where the goal is to maximize the matching cardinality while minimizing the matching cost. An integer linear programming (ILP)-based problem formulation cannot achieve optimum matching because the global network topology is not available with the EVs due to their limited communication range. Our proposed heuristics can yield an almost stable matching with lesser computational, and message overhead compared to other existing distributed approaches. An average case matching probability is also calculated. Simulation experiments are conducted to measure the performance of our heuristics in terms of message overhead, matching percentage, and matching preference. The proposed solution outperforms the existing distributed approaches and shows comparable result with respect to standard centralized stable matching algorithm

    A Reservation-Based Vehicle-to-Vehicle Charging Service Under Constraint of Parking Duration

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    Electric vehicle (EV) has been applied as the main transportation tool recently. However, EVs still require a long charging time and, thus, inevitably cause charging congestion. The traditional plug-in charging mode is limited by fixed location and peak hours. Therefore, a flexible vehicle-to-vehicle (V2V) charging mode is considered in this article. Here, parking lots (PLs) widely dispersed in cities are reused as a common place for V2V charging. EVs are divided into EVs as energy consumers and EVs as energy providers to form as vehicle-to-vehicle charging pairs (V2V-Pairs). In this article, we propose a V2V charging management scheme, which includes a distance-based V2V-Pair matching algorithm and a PL-selection scheme. As the occupation status at PLs is difficult to predict, to achieve high PL utilization and evenly PL selection, V2V charging reservation is introduced. Meanwhile, since EV drivers usually park at PLs within a limited duration, our proposed V2V charging scheme introduces the parking duration to optimize V2V charging under a temporal constraint. We simulate this V2V charging scheme under the Helsinki city scenario. The results prove that our proposed V2V charging scheme achieves great charging efficiency (minimized charging waiting time and maximized fully charging times)

    A Privacy Framework for Decentralized Applications using Blockchains and Zero Knowledge Proofs

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    With the increasing interest in connected vehicles along with electrification opportunities, there is an ongoing effort to automate the charging process of electric vehicles (EVs) through their capabilities to communicate with the infrastructure and each other. However, charging EVs takes time and thus in-advance scheduling is needed. As this process is done frequently due to limited mileage of EVs, it may expose the locations and charging pattern of the EV to the service providers, raising privacy concerns for their users. Nevertheless, the EV still needs to be authenticated to charging providers, which means some information will need to be provided anyway. While there have been many studies to address the problem of privacy-preserving authentication for vehicular networks, such solutions will be void if charging payments are made through traditional means. In this thesis, we tackle this problem by utilizing distributed applications enabled by Blockchain and smart contracts. We adapt zero-knowledge proofs to Blockchain for enabling privacy-preserving authentication while removing the need for a central authority. We introduce two approaches, one using a token-based mechanism and another utilizing the Pederson Commitment scheme to realize anonymous authentication. We also describe a protocol for the whole process which includes scheduling and charging operations. The evaluation of the proposed approaches indicates that the overhead of this process is affordable to enable real-time charging operations for connected EVs

    Shaping future low-carbon energy and transportation systems: Digital technologies and applications

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    Digitalization and decarbonization are projected to be two major trends in the coming decades. As the already widespread process of digitalization continues to progress, especially in energy and transportation systems, massive data will be produced, and how these data could support and promote decarbonization has become a pressing concern. This paper presents a comprehensive review of digital technologies and their potential applications in low-carbon energy and transportation systems from the perspectives of infrastructure, common mechanisms and algorithms, and system-level impacts, as well as the application of digital technologies to coupled energy and transportation systems with electric vehicles. This paper also identifies corresponding challenges and future research directions, such as in the field of blockchain, digital twin, vehicle-to-grid, low-carbon computing, and data security and privacy, especially in the context of integrated energy and transportation systems

    Low-carbon Energy Transition and Planning for Smart Grids

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    With the growing concerns of climate change and energy crisis, the energy transition from fossil-based systems to a low-carbon society is an inevitable trend. Power system planning plays an essential role in the energy transition of the power sector to accommodate the integration of renewable energy and meet the goal of decreasing carbon emissions while maintaining the economical, secure, and reliable operations of power systems. In this thesis, a low-carbon energy transition framework and strategies are proposed for the future smart grid, which comprehensively consider the planning and operation of the electricity networks, the emission control strategies with the carbon response of the end-users, and carbon-related trading mechanisms. The planning approach considers the collaborative planning of different types of networks under the smart grid context. Transportation electrification is considered as a key segment in the energy transition of power systems, so the planning of charging infrastructure for electric vehicles (EVs) and hydrogen refueling infrastructure for fuel cell electric vehicles is jointly solved with the electricity network expansion. The vulnerability assessment tools are proposed to evaluate the coupled networks towards extreme events. Based on the carbon footprint tracking technologies, emission control can be realized from both the generation side and the demand side. The operation of the low-carbon oriented power system is modeled in a combined energy and carbon market, which fully considers the carbon emission right trading and renewable energy certificates trading of the market participants. Several benchmark systems have been used to demonstrate the effectiveness of the proposed planning approach. Comparative studies to existing approaches in the literature, where applicable, have also been conducted. The simulation results verify the practical applicability of this method

    Robust distributed resource allocation for cellular vehicle-to-vehicle communication

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    Mit Release 14 des LTE Standards unterstützt dieser die direkte Fahrzeug-zu-Fahrzeug-Kommunikation über den Sidelink. Diese Dissertation beschäftigt sich mit dem Scheduling Modus 4, einem verteilten MAC-Protokoll ohne Involvierung der Basisstation, das auf periodischer Wiederverwendung von Funkressourcen aufbaut. Der Stand der Technik und eine eigene Analyse des Protokolls decken verschiedene Probleme auf. So wiederholen sich Kollisionen von Paketen, wodurch manche Fahrzeuge für längere Zeit keine sicherheitskritischen Informationen verbreiten können. Kollisionen entstehen vermehrt auch dadurch, dass Hidden-Terminal-Probleme in Kauf genommen werden oder veränderliche Paketgrößen und -raten schlecht unterstützt werden. Deshalb wird ein Ansatz namens "Scheduling based on Acknowledgement Feedback Exchange" vorgeschlagen. Zunächst wird eine Funkreservierung in mehrere ineinander verschachtelte Unter-Reservierungen mit verschiedenen Funkressourcen unterteilt, was die Robustheit gegenüber wiederholenden Kollisionen erhöht. Dies ist die Grundlage für eine verteilte Staukontrolle, die die Periodizitätseigenschaft nicht verletzt. Außerdem können so veränderliche Paketgrößen oder -raten besser abgebildet werden. Durch die periodische Wiederverwendung können Acknowledgements für Funkressourcen statt für Pakete ausgesendet werden. Diese können in einer Bitmap in den Padding-Bits übertragen werden. Mittels der Einbeziehung dieser Informationen bei der Auswahl von Funkressourcen können Hidden-Terminal-Probleme effizient vermieden werden, da die Acknowledgements auch eine Verwendung dieser Funkressource ankündigen. Kollisionen können nun entdeckt und eine Wiederholung vermieden werden. Die Evaluierung des neuen MAC-Protokolls wurde zum großen Teil mittels diskreter-Event-Simulationen durchgeführt, wobei die Bewegung jedes einzelnen Fahrzeuges simuliert wurde. Der vorgeschlagene Ansatz führt zu einer deutlich erhöhten Paketzustellrate. Die Verwendung einer anwendungsbezogenen Awareness-Metrik zeigt, dass die Zuverlässigkeit der Kommunikation durch den Ansatz deutlich verbessert werden kann. Somit zeigt sich der präsentierte Ansatz als vielversprechende Lösung für die erheblichen Probleme, die der LTE Modus 4 mit sich bringt.The LTE Standard added support for a direct vehicle-to-vehicle communication via the Sidelink with Release 14. This dissertation focuses on the scheduling Mode 4, a distributed MAC protocol without involvement of the base station, which requires the periodic reuse of radio resources. The state of the art and a own analysis of this protocol unveil multiple problems. For example, packet collisions repeat in time, so that some vehicles are unable to distribute safety-critical information for extended periods of time. Collisions also arise due to the hidden-terminal problem, which is simply put up with in Mode 4. Additionally, varying packet sizes or rates can hardly be supported. Consequently, an approach called "Scheduling based on Acknowledgement Feedback Exchange" is proposed. Firstly, a reservation of radio resources is split into multiple, interleaved sub-reservations that use different radio resources. This increases the robustness against repeating collisions. It is also the basis for a distributed congestion control that does not violate the periodicity. Moreover, different packet rates or sizes can be supported. The periodic reuse of radio resources enables the transmission of acknowledgements for radio resources instead of packets. These can be transmitted in a bitmap inside the padding bits. Hidden-terminal problems can be mitigated by considering the acknowledgements when selecting radio resources as they announce the use of these radio resources. Collisions can also be detected and prevented from re-occurring. The evaluation of the MAC protocol is mostly performed using discrete-event simulations, which model the movement of every single vehicle. The presented approach leads to a clear improvement of the packet delivery rate. The use of an application-oriented metric shows that the communication robustness can be improved distinctly. The proposed approach hence presents itself as a promising solution for the considerable problems of LTE Mode 4

    Integrated wireless access and networking to support floating car data collection in vehicular networks

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    Collecting data from a large number of agents scattered over a region of interest is becoming an increasingly appealing paradigm to feed big data archives that lay the ground for a vast array of applications. Vehicular Floating Car Data (FCD) collection, a major representative of this paradigm, is a key enabler for a wide range of Intelligent Transportation Systems (ITS) services and applications aiming at enhancing safety, efficiency and sustainability. Obtaining real time, high spacial and temporal resolution vehicular FCD information is becoming a reality thanks to the variety of communication platforms that are being deployed. Dedicated Short-Range Communication (DSRC) and Long Term Evolution (LTE) are the most prominent communication technologies able to support periodic and persistent FCD collection. DSRC technology was mainly proposed for safety applications and is specifically tailored for Vehicular Ad Hoc Networks (VANETs). The first parts of this work are dedicated to assessing the suitability of DSRC to support FCD collection in real urban scenarios. We first study the basic communication paradigm that takes place in VANETs to populate vehicles’ local data bases with FCD information, named beaconing, and the trade-off between the beaconing frequency and the congestion induced in the wireless shared channel used to exchange these beacons. The primary metric to measure the information freshness inside every vehicle’s local data base is the Age-of-Information (AoI). We define an analytical model to evaluate the AoI of a VANET, given the connectivity graph of the vehicles, and validate the model by comparing it with realistic simulations of an urban area. Then, we propose an integrated DSRC-based protocol that disseminates queries and collects FCD messages from vehicles roaming in a quite large city area efficiently and timely by using a single network structure, i.e., a multi-hop backbone network made up of only vehicle nodes. The proposed solution is distributed and adaptive to different traffic conditions, i.e., to different levels of vehicular traffic density. One of the main protocol advantages is that for the dissemination of queries it exploits an existing standardized data dissemination algorithm, namely the GeoNetworking Contention-Based Forwarding (CBF). The proposed protocol is evaluated with reference to a real urban environment. The main parameters are dimensioned and an insight into the protocol operation is given. One of the main outcomes of this part of the thesis is the confirmation of the fact that DSRC is suitable to support not only safety applications, but also periodic FCD collection. The main issue with DSRC is the low penetration rate. LTE on the other hand is pervasive and has been identified as a good candidate technology for non-safety applications. However, a high number of vehicles intermittently reporting their information via LTE can introduce a very high load on the LTE access network. The second part of this work addresses the design and performance evaluation of heterogeneous LTE-DSRC networking solutions to yield significant offloading of LTE – here, DSRC technology can support local data aggregation. We propose distributed clustering algorithms that use both LTE and DSRC networks in the cluster head selection process. We target robustness, optimizing the amount of data and the value of the collection period, keeping in mind the goals of autonomous node operation and minimal coordination effort. Our results clearly indicate that it is crucial to consider parameters drawn from both networking platforms for selecting the right forwarders. We demonstrate that our solutions are able to significantly reduce the LTE channel utilization with respect to other state-of-the-art approaches. The impact of the proposed protocols on the DSRC channels’ load is evaluated and proved to be quite small, so that it does not interfere with other VANET-specific messages

    Enabling 5G Edge Native Applications

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