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In the last decade, with the arrival of the 5G communication technology and the increasing numbers of vehicles being connected to the internet, conventional vehicle ad-hoc networks (VANETs) are evolving towards the internet of vehicles (IoV), which makes the co-existence of IEEE 802.11p and 5G-based technologies very important for the design of a heterogeneous IoV system that takes advantage of both. The IEEE 802.11p standard is still the best candidate to support direct communications for safety critical services. In fact, both the ETSI ITS-G5 and the IEEE 1609 standard families adopt the IEEE 802.11p standard as a medium access control (MAC) mechanism, and they require vehicles to exchange periodic awareness messages to avoid dangerous situations. When the density of vehicles increases, the MAC layer will suffer from radio channel congestion problems, and this may affect the various VANET applications, especially safety applications. Therefore, the decentralized congestion control (DCC) mechanism has been specified by ETSI to mitigate the channel congestion; this was achieved by adapting the transmission parameters, such as the transmit power and data-rate. However, many research studies have demonstrated limitations and a low performance of DCC, especially when the channel load is extremely high. To deal with this, in this paper, we investigate a new promising technique, called the transmission timing control (TTC), to control the channel load for periodic cooperative awareness. It consists of spreading the transmissions over time in order to avoid contention on the transmission channel. The objective of the paper is to propose an analytical study to calculate the probability of successful transmission using TTC. The demonstrated results show the efficiency of our timing control-enabled scheme to deal with the channel load on top of different conditions.

Our modern society is in constant change. The significant technological advances of the past decades have led to unprecedented prosperity but have also come along with great new challenges. A high demand for mobility and the vast deployment of transportation systems have made traffic accidents the most likely cause of death for children and young adults worldwide. To counteract this, traffic authorities around the world place their hopes in the development of Connected Intelligent Transportation Systems (C-ITS). Vehicle-to-Everything (V2X) communication is currently being introduced to enable road users and infrastructure to exchange relevant information to provide the required basis for decision-making. The rapidly growing amount of data managed by V2X services, e.g., for improved satellite navigation, warning of critical traffic situations, sharing of sensor-detected objects, and maneuver coordination, however, pushes the resilience of the wireless communication channel to its limits. Current approaches allocating communication resources within the network are either channel-load agnostic or message-content agnostic, leading to relevant performance impairments. In the scope of this doctoral work, the underlying decentralized resource allocation problem is formalized, and a comprehensive solution is proposed with application examples for the cutting-edge V2X services Collective Perception, Collaborative Localization, and Maneuver Co-ordination: The VALue of INFormation driven Distributed Resource Allocation protocol VALINDRA. It allows to maximize the value of information effectively disseminated within the network. After a thorough analytical examination and a comparison with state-of-the-art V2X protocols, VALINDRA is investigated in simulation and with real-world data for urban and highway scenarios. Both the comparison with the prior art and the simulative investigation evidence considerable improvements in terms of V2X channel utilization, achieved localization and object-tracking accuracies, environmental perception, and traffic safety, among others., Unsere Gesellschaft ist in ständigem Wandel. Insbesondere die zahlreichen technologischen Fortschritte der vergangenen Jahrzehnte führten zu niemals dagewesenem Wohlstand, sind aber auch mit neuen großen Herausforderungen verbunden. So ist die wahrscheinlichste Todesursache für Kinder und junge Erwachsene weltweit, aufgrund des massiven Ausbaus moderner Verkehrssysteme, mit großem Abstand ein Verkehrsunfall. Die größte Hoffnung etablierter Verkehrsbehörden weltweit sind die intelligente Vernetzung und die Automatisierung des Verkehrs. Mittels Fahrzeug-zu-Alles (V2X; engl. Vehicle-to-Everything) Kommunikation sollen Verkehrsteilnehmer und Infrastruktur relevante Informationen austauschen können, um eine solide Entscheidungsgrundlage zu schaffen. Die rasant wachsende Anzahl mittels V2X Diensten ausgetauschter Daten, u.A. zur verbesserten Satelliten-gestützten Navigation, Warnung vor kritischen Verkehrssituationen, dem Teilen von Sensor-detektierten Objekten und der Manöverabstimmung, bringt die Belastbarkeit des drahtlosen Kommunikations-kanals jedoch an ihre Grenzen. Gegenwärtige Ansätze zum Zuweisen von Kommunikationsressourcen innerhalb der Fahrzeugnetzwerke sind entweder unabhängig von der Anzahl verfügbarer Ressourcen oder vom Wert der zu übermittelnden Informationen, was zu erheblichen Leistungsverlusten führt. Im Rahmen dieses Promotionsvorhabens wird das zugrundeliegende dezentrale Ressourcenallokationsproblem formalisiert und eine umfassende Lösung mit Anwendungsbeispielen für die wegweisenden V2X-Dienste Collective Perception, Collaborative Localization und Maneuver Coordination vorgeschlagen: VALINDRA (engl. „The VALue of INFormation driven Distributed Resource Allocation protocol”). Nach einer gründlichen analytischen Untersuchung und einem Vergleich mit etablierten V2X-Protokollen wird VALINDRA simulativ und mit realen Daten in Stadt- und Autobahnumgebungen untersucht. Sowohl der Vergleich mit dem Stand der Technik als auch die simulative Untersuchung offenbaren deutliche Verbesserungen in Bezug auf die erreichte Kanalauslastung, Umgebungs-wahrnehmung, Navigations- und Objekttrackinggenauigkeiten, und Verkehrs-sicherheit unter anderem., 我们的现代社会在不断变化。过去几十年的巨大技术进步带来了前所未有的繁荣，但也带来了巨大的新挑战。对流动性的高需求和交通系统的广泛部署使交通事故成为全球儿童和年轻人最可能的死亡原因。为了解决这个问题，世界各地的交通当局部门都寄希望于互联智能交通系统 (C-ITS) 的发展。目前正在被引入的车辆对一切 (V2X) 通信，以使道路使用者和基础设施能够交换相关信息，为决策提供所需的基础。然而，来自 V2X 服务的数据量迅速增长，例如用于改进卫星导航、危急交通情况警告、传感器检测对象的共享以及机动协调，将无线通信信道的弹性推到了极限。当前在网络内分配通信资源的方法要么与信道负载无关，要么与消息内容无关，从而导致相关的性能损失。在本博士工作的范围内，对底层的分散资源分配问题进行了形式化，并提出了一个综合解决方案，同时并提供了尖端 V2X 服务集体感知、协作定位和机动协调的应用示例：VALINDRA (英语 „The VALue of INFormation driven Distributed Resource Allocation protocol”）。经过彻底的分析检查并与最先进的 V2X 协议进行比较后，使用在城市和高速公路场景中的模拟数据以及真实数据对VALINDRA 在模拟和城市和高速公路场景的真实世界数据中进行了研究。与现有技术的比较和模拟研究调查都证明了其在 V2X 通道利用方面非常有希望的结果，提供了定位和对象跟踪的准确性、环境感知和交通安全等。V2X通道的利用，提供的定位和物体追踪的准确性，环境感知和交通安全上有非常好的结果。

This paper addresses collective perception for connected and automated driving. It proposes the adaptation of filtering rules based on the currently available channel resources, referred to as Enhanced DCC-Aware Filtering (EDAF)., Electronic Communications of the EASST, Volume 80: Conference on Networked Systems 2021 (NetSys 2021)

Vehicular networking enables a wide range of emerging Cooperative Intelligent Transportation System (C-ITS) applications, from safety to traffic efficiency and infotainment. Many of these applications depend on the reliability and timeliness of status information periodically exchanged among vehicles on the same wireless communication channel. A major effort has been spent, especially by standardization bodies, to define congestion control algorithms for the vehicular networking environment. The picture is, however, more complex than simply controlling the load level on the channel, given the non-trivial interplay of delivery reliability, system throughput, and timeliness of updates. In this paper, we provide a comprehensive performance evaluation of the main state-of- the-art broadcast rate control algorithms from the point of view of channel load, utilization efficiency, and information freshness. We evaluate these algorithms in a realistic simulation environment and describe a centralized approach to define a bound on the performance. We show that controlling the congestion based on either channel load or information freshness only leads to sub-optimal performance.

Decentralized Congestion Control (DCC) mechanisms are a crucial part of Intelligent Transport Systems (ITS) and Vehicular ad-hoc networks (VANETs). It is through the use of DCC that a network maximizes its throughput and efficiency by allocating resources (i.e., access to the medium) fairly in congestion situations. The ITS framework defined by the European Telecommunications Standards Institute (ETSI) considers the usage of DCC both in the Access layer and as part of a cross-layer architecture. This means that DCC mechanisms influence the performance of elements in different layers. One of the components that are directly influenced by DCC is the Cooperative Awareness (CA) basic service —the entity that keeps vehicles aware of the presence of each other on the road. In this thesis, we perform an analysis of the DCC mechanism defined by ETSI, particularly an analytical and experimental evaluation of the performance of the ETSI DCC Adaptive Approach algorithm, comparing it to related algorithms including our own proposal (Dual-alfa). Additionally, we present an evaluation of the effect of DCC on the end-to-end delay of the CA basic service, and propose Generate-on-Time (GoT), an addition to the standard that accounts for delays caused by DCC and the effects these delays bring on other metrics. Results from this thesis show that Dual-alfa is a valid addition to ETSI Adaptive DCC in order to account for transitory situations. Furthermore, the evaluation of Generate-on-Time showed that it improves the performance of Cooperative Awareness Messages (CAMs) when multiple types of traffic coexist. Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de Madrid Presidente: Pietro Manzoni.- Secretario: María Celeste Campo Vázquez.- Vocal: José Eugenio Naranjo Hernández

Platooning has the potential to be a breakthrough in increasing road capacity and reducing fuel consumption, as it allows a chain of vehicles to closely follow each other on the road. When the number of vehicles increases, platoons will follow one another in what is referred to as multiplatooning. Many Cooperative Intelligent Transportation Systems (C-ITS) applications rely on periodically exchanged beacons among vehicles to improve traffic safety. However, as the number of connected vehicles increases, the network may become congested due to periodically exchanged beacons. Therefore, without some congestion control method, safety critical messages such as Cooperative Awareness Messages (CAMs) may not be delivered on time in high vehicle density scenarios. Both the European Telecommunications Standards Institute (ETSI) and the Institute of Electrical and Electronics Engineers (IEEE) have been working on different standards to support vehicular communication. ETSI dened the Decentralized Congestion Control (DCC) mechanism which adapts transmission parameters (message rate, transmit data rate, and transmit power, etc.) to keep channel load under control. ETSI DCC utilizes a three-state machine with RELAXED, ACTIVE, and RESTRICTIVE states. In this thesis, we implemented this three-state machine by adapting the message rate based on the channel busy ratio (CBR). We name this message-rate based three-state machine DCC-3. DCC-3 has the ability to control channel load; however, it has unfairness and instability problems due to the dramatic parameter changes between states. Therefore, we divided the ACTIVE state of DCC-3 into ve sub-states, and refer to this as DCC-7. We benchmarked DCC-3 against static beaconing (STB), dynamic beaconing (DynB), LInear MEssage Rate Integrated Control (LIMERIC), and DCC-7 using different evaluation metrics with different numbers of platoons. Our results from the Plexe simulator demonstrate that DCC-7 has the best performance when considering all evaluation metrics, including CBR, Inter-reception time (IRT), collisions, safe time ratio, and fairness. Furthermore, we found using transmit power control could greatly improve the performance of CBR and collision rates. Platooning (fordonskonvojer) har potential att bli ett genombrott i öka vägkapaciteten och minska bränsleförbrukning, eftersom det tillåter en kedja av fordon att noga följa varandra på vägen. När antalet fordon ökar, kommer att plutoner följa varandra i vad som benämns multiplatooning (konvoj av fordonskonvojer). Många kooperativ intelligenta transportsystem (C-ITS) tillämpningar förlitar sig på regelbundet utbytte beacons bland fordon att förbättra traffiksäkerheten. Dock som antalet uppkopplade fordon ökar, kan nätverket bli överbelastat på grund av regelbundet utbytte beacons. Utan någon trängsel kontrollmetod, får därför säkerhet kritiska meddelanden såsom kooperativ medvetenhet meddelanden (CAMs) inte levereras i tid i höga fordon densitet scenarier. Både Europeiska institutet för telekommunikationsstandarder (ETSI) och Institute el och elektroniska tekniker (IEEE) har arbetat på olika standarder för att stödja vehicular kommunikation. ETSI definieras den decentraliserade överbelastning kontroll (DCC) mekanism som anpassar överföring parametrar (meddelande hastighet, överföra datahastighet och sändningseffekt, etc.) för att hålla kanalen belastningen under kontroll. ETSI DCC använder en tre-state maskin med RELAXED, ACTIVE och RESTRICTIVE stater. I denna avhandling har genomfört vi denna tre-state maskin genom att anpassa meddelande hastighet baserat på kanal upptagen förhållandet (CBR). Vi nämna detta meddelande-hastighet baserat tre-state machine DCC-3. DCC-3 har förmågan att kontrollera kanal belastning; Det har dock otillbörlighet och instabilitet problem på grund av de dramatiska parameterändringar mellan stater. Därför vi indelat det ACTIVE tillståndet för DCC-3 i fem undertillstånd och hänvisar till detta som DCC-7. Vi benchmarkade DCC-3 mot statiska leda (STB), dynamisk leda (DynB), linjära MEssage Rate integrerad kontroll (LIMERIC) och DCC-7 med olika utvärdering statistik med olika antal plutoner. Våra resultat från Plexe simulator visar att DCC-7 har bästa prestanda när man överväger alla utvärdering statistik, inklusive CBR, mellan receptionen tid (IRT), kollisioner, säker tid baserat och rättvisa. Vi fann dessutom använda Sändareffektstyrning kan avsevärt förbättra prestanda för CBR och kollision priser.

Wireless access in vehicular environments (WAVE) is a vehicle to vehicle (V2V) communications technology which could help prevent up to 82% of non-impaired accidents, according to the US DOT. A 2013 study by the World Health Organization estimated 2,227 road fatalities in 2009 alone. Currently the channel that is responsible for a vehicle’s awareness of others suffers from congestion at moderate loads. In this paper we propose a novel method for adjusting the transmission power in a pattern which alternates between high and low powered transmissions. We modify one commonly used decentralized congestion control (DCC) algorithm, LIMERIC, and compare the power adaptation model against two controls. WAVE supports a 300 meter transmission radius, however, less than 200 vehicles can communicate at the target rate of 10 transmissions per second. We demonstrate that our algorithm reduces the number of packets received by distant vehicles, while maintaining a higher packet rate to the closer vehicles, for which a higher rate is more important.

The communication graph formed by vehicles is an abstract and dynamic graph that faces intermittent disconnections due to the high mobility of vehicles. This graph is governed by traffic signaling, urban planning and drivers behaviours. Even if Social Network Analysis (SNA) proved its benefits in the study of abstract social networks, it poses new challenges when applied to dynamic networks such as vehicular ad hoc networks (VANETs). This paper aims at studying how social centrality and community metrics, two important social properties in SNA can help to mitigate the poor performances in vehicular networks. This paper first explores the possible correlation that exists between performance degradation and social metrics in urban-like maps. After conducting an extensive quantitative analysis on the correlation between social and underlying networking properties of vehicular networks under different densities, space clustering coefficient, transmission range, we observed that closeness centrality, clustering coefficient and lobby index can help to identify special vehicles - those vehicles that have a higher opportunity to access the channel than others - and discuss the implications of such findings in the context of a dynamic backoff optimization for the IEEE 802.11p MAC layer.