Suporte a gerenciamento do trânsito baseado em computação na névoa para os sistemas de transporte inteligentes

Orientadores: Leandro Aparecido Villas, Daniel Ludovico GuidoniTese (doutorado) ¿ Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: O trânsito nos grandes centros urbanos contribui com problemas que vão desde diminuição da qualidade de vida e segurança da população até o aumento de custos financeiros às pessoas, cidades e empresas. Um dos motivos para um maior tráfego de veículos é o vertiginoso crescimento populacional dos centros urbanos. Além disso, o fluxo de veículos é prejudicado por situações adversas recorrentes nas vias, como o aumento súbito do tráfego durante os horários de pico, gargalos nas infraestruturas de transporte, e acidentes de trânsito. Com o avanço das tecnologias de comunicação, processamento e sensoriamento, os Sistemas de Transporte Inteligentes (ITS) surgem como uma alternativa para mitigar esses problemas. A interoperabilidade dos ITS com novas tecnologias tais como as redes veiculares (VANETs) e computação em névoa, os tornam mais promissores e eficazes. As VANETs preveem que veículos possuam poder computacional e capacidade de comunicação sem fio com outros veículos e com as infraestruturas fixa de comunicação, assim, uma nova gama de serviços de segurança e entretenimento aos motoristas e passageiros podem ser desenvolvidas. Entretanto, estes tipos de serviços, em especial o de gerenciamento de trânsito, demandam uma análise contínua das condições de fluxo de veículos nas vias e um vasto recurso de rede e processamento, tornando o desenvolvimento de soluções para ITS mais complexo e de difícil escalabilidade. A computação em névoa é uma infraestrutura de computação descentralizada na qual dados, processamento, armazenamento e aplicações são distribuídos na borda da rede, assim, aumentando a escalabilidade do sistema. Na literatura, os sistemas de gerenciamento de tráfego não tratam de maneira adequada o problema de escalabilidade, implicando em problemas relacionados ao balanceamento de carga e tempo de resposta. Esta tese de doutorado propõe um sistema de gerenciamento de tráfego baseado no paradigma de computação em névoa, para detectar, classificar e controlar o congestionamento de tráfego. O sistema proposto apresenta um framework distribuído e escalável que reduz os problemas supracitados em relação ao estado da arte. Para tanto, utilizando da natureza distribuída da computação em névoa, a solução implementa um algoritmo de roteamento probabilístico que faz o balanceamento do tráfego e evita o problema de deslocamento de congestionamentos para outras regiões. Utilizando às características da computação em névoa, foi desenvolvida uma metodologia distribuída baseada em regiões que faz a coleta de dados e classificação das vias em relação às condições do trânsito compartilhadas pelos veículos. Finalmente, foi desenvolvido um conjunto de algoritmos/protocolos de comunicação que comparado com outras soluções da literatura, reduz a perda de pacotes e o número de mensagens transmitidas. O serviço proposto foi comparado extensivamente com outras soluções da literatura em relação às métricas de trânsito, onde o sistema proposto foi capaz de reduzir em até 70% o tempo parado e em até 49% o planning time index. Considerando as métricas de comunicação, o serviço proposto é capaz de reduzir em até 12% a colisão de pacotes alcançando uma cobertura de 98% do cenário. Os resultados mostram que o framework baseado em computação em névoa desenvolvido, melhora o fluxo de veículos de forma eficiente e escalávelAbstract: Traffic in large urban centers contributes to problems that range from decreasing the population¿s quality of life and security to increasing financial costs for people, cities, and companies. One of the reasons for increased vehicle traffic is the population growth in urban centers. Moreover, vehicle flow is hampered by recurring adverse situations on roads, such as the sudden increase in vehicle traffic during peak hours, bottlenecks in transportation infrastructure, and traffic accidents. Considering the advance of communication, processing, and sensing technologies, Intelligent Transport Systems (ITS) have emerged as an alternative to mitigate these problems. The interoperability of ITS with new technologies, such as vehicular networks (VANETs) and Fog computing, make them more promising and effective. VANETs ensure that vehicles have the computing power and wireless communication capabilities with other vehicles and with fixed communication infrastructures; therefore, a new range of security and entertainment services for drivers and passengers can be developed. However, these types of services, especially traffic management, demand a continuous analysis of vehicle flow conditions on roads and a huge network and processing resource, making the development of ITS solutions more complex and difficult to scale. Fog computing is a decentralized computing infrastructure in which data, processing, storage, and applications are distributed at the network edge, thereby increasing the system¿s scalability. In the literature, traffic management systems do not adequately address the scalability problem, resulting in load balancing and response time problems. This doctoral thesis proposes a traffic management system based on the Fog computing paradigm to detect, classify, and control traffic congestion. The proposed system presents a distributed and scalable framework that reduces the aforementioned problems in relation to state of the art. Therefore, using Fog computing¿s distributed nature, the solution implements a probabilistic routing algorithm that balances traffic and avoids the problem of congestion displacement to other regions. Using the characteristics of Fog computing, a distributed methodology was developed based on regions that collect data and classify the roads concerning the traffic conditions shared by the vehicles. Finally, a set of communication algorithms/protocols was developed which, compared with other literature solutions, reduces packet loss and the number of messages transmitted. The proposed service was compared extensively with other solutions in the literature regarding traffic metrics, where the proposed system was able to reduce downtime by up to 70% and up to 49% of the planning time index. Considering communication metrics, the proposed service can reduce packet collision by up to 12% reaching 98% coverage of the scenario. The results show that the framework based on Fog computing developed improves the vehicles¿ flow efficiently and in a scalable wayDoutoradoCiência da ComputaçãoDoutor em Ciência da Computaçã

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

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

A comprehensive survey on cooperative intersection management for heterogeneous connected vehicles

Nowadays, with the advancement of technology, world is trending toward high mobility and dynamics. In this context, intersection management (IM) as one of the most crucial elements of the transportation sector demands high attention. Today, road entities including infrastructures, vulnerable road users (VRUs) such as motorcycles, moped, scooters, pedestrians, bicycles, and other types of vehicles such as trucks, buses, cars, emergency vehicles, and railway vehicles like trains or trams are able to communicate cooperatively using vehicle-to-everything (V2X) communications and provide traffic safety, efficiency, infotainment and ecological improvements. In this paper, we take into account different types of intersections in terms of signalized, semi-autonomous (hybrid) and autonomous intersections and conduct a comprehensive survey on various intersection management methods for heterogeneous connected vehicles (CVs). We consider heterogeneous classes of vehicles such as road and rail vehicles as well as VRUs including bicycles, scooters and motorcycles. All kinds of intersection goals, modeling, coordination architectures, scheduling policies are thoroughly discussed. Signalized and semi-autonomous intersections are assessed with respect to these parameters. We especially focus on autonomous intersection management (AIM) and categorize this section based on four major goals involving safety, efficiency, infotainment and environment. Each intersection goal provides an in-depth investigation on the corresponding literature from the aforementioned perspectives. Moreover, robustness and resiliency of IM are explored from diverse points of view encompassing sensors, information management and sharing, planning universal scheme, heterogeneous collaboration, vehicle classification, quality measurement, external factors, intersection types, localization faults, communication anomalies and channel optimization, synchronization, vehicle dynamics and model mismatch, model uncertainties, recovery, security and privacy

Cooperative Caching in Vehicular Networks - Distributed Cache Invalidation Using Information Freshness

Recent advances in vehicular communications has led to significant opportunities to deploy variety of applications and services improving road safety and traffic efficiency to road users. In regard to traffic management services in distributed vehicular networks, this thesis work evaluates managing storage at vehicles efficiently as cache for moderate cellular transmission costs while still achieving correct routing decision. Road status information was disseminated to oncoming traffic in the form of cellular notifications using a reporting mechanism. High transmission costs due to redundant notifications published by all vehicles following a basic reporting mechanism: Default-approach was overcome by implementing caching at every vehicle. A cooperative based reporting mechanism utilizing cache: Cooperative-approach, was proposed to notify road status while avoiding redundant notifications. In order to account those significantly relevant vehicles for decision-making process which did not actually publish, correspondingly virtual cache entries were implemented. To incorporate the real-world scenario of varying vehicular rate observed on any road, virtual cache entries based on varying vehicular rate was modeled as Adaptive Cache Management mechanism. The combinations of proposed mechanisms were evaluated for cellular transmission costs and accuracy achieved for making correct routing decision. Simulation case studies comprising varying vehicular densities and different false detection rates were conducted to demonstrate the performance of these mechanisms. Additionally, the proposed mechanisms were evaluated in different decision-making algorithms for both information freshness in changing road conditions and for robustness despite false detections. The simulation results demonstrated that the combination of proposed mechanisms was capable of achieving realistic information accuracy enough to make correct routing decision despite false readings while keeping network costs significantly low. Furthermore, using QoI-based decision algorithm in high density vehicular networks, fast adaptability to frequently changing road conditions as well as quick recovery from false notifications by invalidating them with correct notifications were indicated

Quality of service aware data dissemination in vehicular Ad Hoc networks

Des systèmes de transport intelligents (STI) seront éventuellement fournis dans un proche avenir pour la sécurité et le confort des personnes lors de leurs déplacements sur les routes. Les réseaux ad-hoc véhiculaires (VANETs) représentent l'élément clé des STI. Les VANETs sont formés par des véhicules qui communiquent entre eux et avec l'infrastructure. En effet, les véhicules pourront échanger des messages qui comprennent, par exemple, des informations sur la circulation routière, les situations d'urgence et les divertissements. En particulier, les messages d'urgence sont diffusés par des véhicules en cas d'urgence (p.ex. un accident de voiture); afin de permettre aux conducteurs de réagir à temps (p.ex., ralentir), les messages d'urgence doivent être diffusés de manière fiable dans un délai très court. Dans les VANETs, il existe plusieurs facteurs, tels que le canal à pertes, les terminaux cachés, les interférences et la bande passante limitée, qui compliquent énormément la satisfaction des exigences de fiabilité et de délai des messages d'urgence. Dans cette thèse, en guise de première contribution, nous proposons un schéma de diffusion efficace à plusieurs sauts, appelé Dynamic Partitioning Scheme (DPS), pour diffuser les messages d'urgence. DPS calcule les tailles de partitions dynamiques et le calendrier de transmission pour chaque partition; à l'intérieur de la zone arrière de l'expéditeur, les partitions sont calculées de sorte qu'en moyenne chaque partition contient au moins un seul véhicule; l'objectif est de s'assurer que seul un véhicule dans la partition la plus éloignée (de l'expéditeur) est utilisé pour diffuser le message, jusqu'au saut suivant; ceci donne lieu à un délai d'un saut plus court. DPS assure une diffusion rapide des messages d'urgence. En outre, un nouveau mécanisme d'établissement de liaison, qui utilise des tonalités occupées, est proposé pour résoudre le problème du problème de terminal caché. Dans les VANETs, la Multidiffusion, c'est-à-dire la transmission d'un message d'une source à un nombre limité de véhicules connus en tant que destinations, est très importante. Par rapport à la diffusion unique, avec Multidiffusion, la source peut simultanément prendre en charge plusieurs destinations, via une arborescence de multidiffusion, ce qui permet d'économiser de la bande passante et de réduire la congestion du réseau. Cependant, puisque les VANETs ont une topologie dynamique, le maintien de la connectivité de l'arbre de multidiffusion est un problème majeur. Comme deuxième contribution, nous proposons deux approches pour modéliser l'utilisation totale de bande passante d'une arborescence de multidiffusion: (i) la première approche considère le nombre de segments de route impliqués dans l'arbre de multidiffusion et (ii) la seconde approche considère le nombre d'intersections relais dans l'arbre de multidiffusion. Une heuristique est proposée pour chaque approche. Pour assurer la qualité de service de l'arbre de multidiffusion, des procédures efficaces sont proposées pour le suivi des destinations et la surveillance de la qualité de service des segments de route. Comme troisième contribution, nous étudions le problème de la congestion causée par le routage du trafic de données dans les VANETs. Nous proposons (1) une approche de routage basée sur l’infonuagique qui, contrairement aux approches existantes, prend en compte les chemins de routage existants qui relaient déjà les données dans les VANETs. Les nouvelles demandes de routage sont traitées de sorte qu'aucun segment de route ne soit surchargé par plusieurs chemins de routage croisés. Au lieu d'acheminer les données en utilisant des chemins de routage sur un nombre limité de segments de route, notre approche équilibre la charge des données en utilisant des chemins de routage sur l'ensemble des tronçons routiers urbains, dans le but d'empêcher, dans la mesure du possible, les congestions locales dans les VANETs; et (2) une approche basée sur le réseau défini par logiciel (SDN) pour surveiller la connectivité VANET en temps réel et les délais de transmission sur chaque segment de route. Les données de surveillance sont utilisées en entrée de l'approche de routage.Intelligent Transportation Systems (ITS) will be eventually provided in the near future for both safety and comfort of people during their travel on the roads. Vehicular ad-hoc Networks (VANETs), represent the key component of ITS. VANETs consist of vehicles that communicate with each other and with the infrastructure. Indeed, vehicles will be able to exchange messages that include, for example, information about road traffic, emergency situations, and entertainment. Particularly, emergency messages are broadcasted by vehicles in case of an emergency (e.g., car accident); in order to allow drivers to react in time (e.g., slow down), emergency messages must be reliably disseminated with very short delay. In VANETs, there are several factors, such as lossy channel, hidden terminals, interferences and scarce bandwidth, which make satisfying reliability and delay requirements of emergency messages very challenging. In this thesis, as the first contribution, we propose a reliable time-efficient and multi-hop broadcasting scheme, called Dynamic Partitioning Scheme (DPS), to disseminate emergency messages. DPS computes dynamic partition sizes and the transmission schedule for each partition; inside the back area of the sender, the partitions are computed such that in average each partition contains at least a single vehicle; the objective is to ensure that only a vehicle in the farthest partition (from the sender) is used to disseminate the message, to next hop, resulting in shorter one hop delay. DPS ensures fast dissemination of emergency messages. Moreover, a new handshaking mechanism, that uses busy tones, is proposed to solve the problem of hidden terminal problem. In VANETs, Multicasting, i.e. delivering a message from a source to a limited known number of vehicles as destinations, is very important. Compared to Unicasting, with Multicasting, the source can simultaneously support multiple destinations, via a multicast tree, saving bandwidth and reducing overall communication congestion. However, since VANETs have a dynamic topology, maintaining the connectivity of the multicast tree is a major issue. As the second contribution, we propose two approaches to model total bandwidth usage of a multicast tree: (i) the first approach considers the number of road segments involved in the multicast tree and (ii) the second approach considers the number of relaying intersections involved in the multicast tree. A heuristic is proposed for each approach. To ensure QoS of the multicasting tree, efficient procedures are proposed for tracking destinations and monitoring QoS of road segments. As the third contribution, we study the problem of network congestion in routing data traffic in VANETs. We propose (1) a Cloud-based routing approach that, in opposition to existing approaches, takes into account existing routing paths which are already relaying data in VANETs. New routing requests are processed such that no road segment gets overloaded by multiple crossing routing paths. Instead of routing over a limited set of road segments, our approach balances the load of communication paths over the whole urban road segments, with the objective to prevent, whenever possible, local congestions in VANETs; and (2) a Software Defined Networking (SDN) based approach to monitor real-time VANETs connectivity and transmission delays on each road segment. The monitoring data is used as input to the routing approach

Distributed mobile platforms and applications for intelligent transportation systems

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 70-75).Smartphones are pervasive, and possess powerful processors, multi-faceted sensing, and multiple radios. However, networked mobile apps still typically use a client-server programming model, sending all shared data queries and uploads through the cellular network, incurring bandwidth consumption and unpredictable latencies. Leveraging the local compute power and device-to-device communications of modern smartphones can mitigate demand on cellular networks and improve response times. This thesis presents two systems towards this vision. First, we present DIPLOMA, which aids developers in achieving this vision by providing a programming layer to easily program a collection of smartphones connected over adhoc wireless. It presents a familiar shared data model to developers, while underneath, it implements a distributed shared memory system that provides coherent relaxed-consistency access to data across different smartphones and addresses the issues that device mobility and unreliable networking pose against consistency and coherence. We evaluated our prototype on 10 Android phones on both 3G (HSPA) and 4G (LTE) networks with a representative location-based photo-sharing service and a synthetic benchmark. We also simulated large scale scenarios up to 160 nodes on the ns-2 network simulator. Compared to a client-server baseline, our system shows response time improvements of 10x over 3G and 2x over 4G. We also observe cellular bandwidth reductions of 96%, comparable energy consumption, and a 95.3% request completion rate with coherent caching. With RoadRunner, we apply our vision to Intelligent Transportation Systems (ITS). RoadRunner implements vehicular congestion control as an in-vehicle smartphone app that judiciously harnesses onboard sensing, local computation, and short-range communications, enabling large-scale traffic congestion control without the need for physical infrastructure, at higher penetration across road networks, and at finer granularity. RoadRunner enforces a quota on the number of cars on a road by requiring vehicles to possess a token for entry. Tokens are circulated and reused among multiple vehicles as they move between regions. We implemented RoadRunner as an Android application, deployed it on 10 vehicles using 4G (LTE), 802.11p DSRC and 802.11n adhoc WiFi, and measured cellular access reductions up to 84%, response time improvements up to 80%, and effectiveness of the system in enforcing congestion control policies. We also simulated large-scale scenarios using actual traffic loop-detector counts from Singapore.by Jason Hao Gao.S.M

Intelligent Multi-Dimensional Resource Management in MEC-Assisted Vehicular Networks

Benefiting from advances in the automobile industry and wireless communication technologies, the vehicular network has been emerged as a key enabler of intelligent transportation services. Allowing real-time information exchanging between vehicle and everything, traffic safety and efficiency are significantly enhanced, and ubiquitous Internet access is enabled to support new data services and applications. However, with more and more services and applications, mobile data traffic generated by vehicles has been increasing and the issue on the overloaded computing task has been getting worse. Because of the limitation of spectrum and vehicles' on-board computing and caching resources, it is challenging to promote vehicular networking technologies to support the emerging services and applications, especially those requiring sensitive delay and diverse resources. To overcome these challenges, in this thesis, we propose a new vehicular network architecture and design efficient resource management schemes to support the emerging applications and services with different levels of quality-of-service (QoS) guarantee. Firstly, we propose a multi-access edge computing (MEC)-assisted vehicular network (MVNET) architecture that integrates the concepts of software-defined networking (SDN) and network function virtualization (NFV). With MEC, the interworking of multiple wireless access technologies can be realized to exploit the diversity gain over a wide range of radio spectrum, and at the same time, vehicle's computing/caching tasks can be offloaded to and processed by the MEC servers. By enabling NFV in MEC, different functions can be programmed on the server to support diversified vehicular applications, thus enhancing the server's flexibility. Moreover, by using SDN concepts in MEC, a unified control plane interface and global information can be provided, and by subsequently using this information, intelligent traffic steering and efficient resource management can be achieved. Secondly, under the proposed MVNET architecture, we propose a dynamic spectrum management framework to improve spectrum resource utilization while guaranteeing QoS requirements for different applications, in which, spectrum slicing, spectrum allocating, and transmit power controlling are jointly considered. Accordingly, three non-convex network utility maximization problems are formulated to slice spectrum among base stations (BSs), allocate spectrum among vehicles associated with the same BS, and control transmit powers of BSs, respectively. Via linear programming relaxation and first-order Taylor series approximation, these problems are transformed into tractable forms and then are jointly solved by a proposed alternate concave search algorithm. As a result, optimal spectrum slicing ratios among BSs, optimal BS-vehicle association patterns, optimal fractions of spectrum resources allocated to vehicles, and optimal transmit powers of BSs are obtained. Based on our simulation, a high aggregate network utility is achieved by the proposed spectrum management scheme compared with two existing schemes. Thirdly, we study the joint allocation of the spectrum, computing, and caching resources in MVNETs. To support different vehicular applications, we consider two typical MVNET architectures and formulate multi-dimensional resource optimization problems accordingly, which are usually with high computation complexity and overlong problem-solving time. Thus, we exploit reinforcement learning to transform the two formulated problems and solve them by leveraging the deep deterministic policy gradient (DDPG) and hierarchical learning architectures. Via off-line training, the network dynamics can be automatically learned and appropriate resource allocation decisions can be rapidly obtained to satisfy the QoS requirements of vehicular applications. From simulation results, the proposed resource management schemes can achieve high delay/QoS satisfaction ratios. Fourthly, we extend the proposed MVNET architecture to an unmanned aerial vehicle (UAV)-assisted MVNET and investigate multi-dimensional resource management for it. To efficiently provide on-demand resource access, the macro eNodeB and UAV, both mounted with MEC servers, cooperatively make association decisions and allocate proper amounts of resources to vehicles. Since there is no central controller, we formulate the resource allocation at the MEC servers as a distributive optimization problem to maximize the number of offloaded tasks while satisfying their heterogeneous QoS requirements, and then solve it with a multi-agent DDPG (MADDPG)-based method. Through centrally training the MADDPG model offline, the MEC servers, acting as learning agents, then can rapidly make vehicle association and resource allocation decisions during the online execution stage. From our simulation results, the MADDPG-based method can achieve a comparable convergence rate and higher delay/QoS satisfaction ratios than the benchmarks. In summary, we have proposed an MEC-assisted vehicular network architecture and investigated the spectrum slicing and allocation, and multi-dimensional resource allocation in the MEC- and/or UAV-assisted vehicular networks in this thesis. The proposed architecture and schemes should provide useful guidelines for future research in multi-dimensional resource management scheme designing and resource utilization enhancement in highly dynamic wireless networks with diversified data services and applications

Dynamic speed adaptive classified (D-SAC) data dissemination protocol for improving autonomous robot performance in VANETs

In robotics, mechanized and computer simulation for accurate and fast crash detection between general geometric models is a fundamental problem. The explanation of this problem will gravely improve driver safety and traffic efficiency, vehicular ad hoc networks (VANETs) have been employed in many scenarios to provide road safety and for convenient travel of the people. They offer self-organizing decentralized environments to disseminate traffic data, vehicle information and hazardous events. In order to avoid accidents during roadway travels, which are a major burden to the society, the data, such as traffic data, vehicle data and the road condition, play a critical role. VANET is employed for disseminating the data. Still the scalability issues occur when the communication happens under high-traffic regime where the vehicle density is high. The data redundancy and packet collisions may be high which cause broadcast storm problems. Here the traffic regime in the current state is obtained from the speed of the vehicle. Thus the data reduction is obtained. In order to suppress the redundant broadcast D-SAC data, dissemination protocol is presented in this paper. Here the data are classified according to its criticality and the probability is determined. The performance of the D-SAC protocol is verified through conventional methods with simulation

Threat vector analysis in autonomous driving

Σημείωση: διατίθεται συμπληρωματικό υλικό σε ξεχωριστό αρχείο

VANET-enabled eco-friendly road characteristics-aware routing for vehicular traffic

There is growing awareness of the dangers of climate change caused by greenhouse gases. In the coming decades this could result in numerous disasters such as heat-waves, flooding and crop failures. A major contributor to the total amount of greenhouse gas emissions is the transport sector, particularly private vehicles. Traffic congestion involving private vehicles also causes a lot of wasted time and stress to commuters. At the same time new wireless technologies such as Vehicular Ad-Hoc Networks (VANETs) are being developed which could allow vehicles to communicate with each other. These could enable a number of innovative schemes to reduce traffic congestion and greenhouse gas emissions. 1) EcoTrec is a VANET-based system which allows vehicles to exchange messages regarding traffic congestion and road conditions, such as roughness and gradient. Each vehicle uses the messages it has received to build a model of nearby roads and the traffic on them. The EcoTrec Algorithm then recommends the most fuel efficient route for the vehicles to follow. 2) Time-Ants is a swarm based algorithm that considers not only the amount of cars in the spatial domain but also the amoumt in the time domain. This allows the system to build a model of the traffic congestion throughout the day. As traffic patterns are broadly similar for weekdays this gives us a good idea of what traffic will be like allowing us to route the vehicles more efficiently using the Time-Ants Algorithm. 3) Electric Vehicle enhanced Dedicated Bus Lanes (E-DBL) proposes allowing electric vehicles onto the bus lanes. Such an approach could allow a reduction in traffic congestion on the regular lanes without greatly impeding the buses. It would also encourage uptake of electric vehicles. 4) A comprehensive survey of issues associated with communication centred traffic management systems was carried out