Fine-Grained Reliability for V2V Communications around Suburban and Urban Intersections

Safe transportation is a key use-case of the 5G/LTE Rel.15+ communications, where an end-to-end reliability of 0.99999 is expected for a vehicle-to-vehicle (V2V) transmission distance of 100-200 m. Since communications reliability is related to road-safety, it is crucial to verify the fulfillment of the performance, especially for accident-prone areas such as intersections. We derive closed-form expressions for the V2V transmission reliability near suburban corners and urban intersections over finite interference regions. The analysis is based on plausible street configurations, traffic scenarios, and empirically-supported channel propagation. We show the means by which the performance metric can serve as a preliminary design tool to meet a target reliability. We then apply meta distribution concepts to provide a careful dissection of V2V communications reliability. Contrary to existing work on infinite roads, when we consider finite road segments for practical deployment, fine-grained reliability per realization exhibits bimodal behavior. Either performance for a certain vehicular traffic scenario is very reliable or extremely unreliable, but nowhere in relatively proximity to the average performance. In other words, standard SINR-based average performance metrics are analytically accurate but can be insufficient from a practical viewpoint. Investigating other safety-critical point process networks at the meta distribution-level may reveal similar discrepancies.Comment: 27 pages, 6 figures, submitted to IEEE Transactions on Wireless Communication

Advanced Biomedical Laboratory (ABL) Synergy with Communication, Robotics, and IoT

This paper proposes a framework for integrating IoT and automation in a biomedical laboratory to improve safety, optimize processes, and enhance students\u27 learning experience. The framework incorporates a centralized control unit and distributed subsystems to control equipment and machinery and includes autonomous robotics and intelligent monitoring systems. The paper presents the results of undergraduate students\u27 work on automating various biomedical processes, including developing an Intelligent Autonomous Monitoring (IAM) device. IAM utilizes machine learning algorithms to identify outliers in processes and safety hazards. Moreover, IAM autonomously detects and localizes biomedical tools and equipment. Results show the feasibility of delivering real-time results for localizing specific tools necessary within a biomedical laboratory. This framework offers a systemic approach toward process automation, aiding researchers in developing new equipment and automating existing processes. Furthermore, it assists students in gaining a fundamental understanding of the theory behind biomedical principles while providing a repeatable experimental environment through more accurate data and event collection

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

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

Artificial Intelligence-based Cybersecurity for Connected and Automated Vehicles

The damaging effects of cyberattacks to an industry like the Cooperative Connected and Automated Mobility (CCAM) can be tremendous. From the least important to the worst ones, one can mention for example the damage in the reputation of vehicle manufacturers, the increased denial of customers to adopt CCAM, the loss of working hours (having direct impact on the European GDP), material damages, increased environmental pollution due e.g., to traffic jams or malicious modifications in sensors’ firmware, and ultimately, the great danger for human lives, either they are drivers, passengers or pedestrians. Connected vehicles will soon become a reality on our roads, bringing along new services and capabilities, but also technical challenges and security threats. To overcome these risks, the CARAMEL project has developed several anti-hacking solutions for the new generation of vehicles. CARAMEL (Artificial Intelligence-based Cybersecurity for Connected and Automated Vehicles), a research project co-funded by the European Union under the Horizon 2020 framework programme, is a project consortium with 15 organizations from 8 European countries together with 3 Korean partners. The project applies a proactive approach based on Artificial Intelligence and Machine Learning techniques to detect and prevent potential cybersecurity threats to autonomous and connected vehicles. This approach has been addressed based on four fundamental pillars, namely: Autonomous Mobility, Connected Mobility, Electromobility, and Remote Control Vehicle. This book presents theory and results from each of these technical directions

DIB - A Novel Optimized VANET Traffic Management Using a Deep Neural Network

The advancement of the Internet of Things (IoT) establishes the development of the Internet of Vehicles (IoV) and Intelligent Transportation Systems (ITS).  An integral part of ITS is the vehicular ad hoc network (VANET) with smart vehicles (SV).   In this research, a dynamic method of traffic regulation in VANET is presented using Deep Neural Networks (DNN) and Bat Algorithms (BA). With a reduced average delay, the former (DNN) is utilized to guide vehicles across very crowded routes to increase efficiency. In order to examine the traffic congestion status between network nodes, BA is integrated with the IoT and moved over VANETs. Experiments were conducted to test the effectiveness of the proposed method with various parameters such as average latency, packet delivery ratio (PDR) and throughput and the performance were compared with different machine learning (ML) algorithms.  The simulation outputs proved that the proposed technique supports real-time traffic circumstances with less energy usage and delay than existing methods

Towards reliable geographic broadcasting in vehicular networks

In Vehicular ad hoc Networks (VANETs), safety-related messages are broadcasted amongst cars, helping to improve drivers' awareness of the road situation. VANETs’ reliability are highly affected by channel contention. This thesis first addresses the issue of channel use efficiency in geographical broadcasts (geocasts). Constant connectivity changes inside a VANET make the existing routing algorithms unsuitable. This thesis presents a geocast algorithm that uses a metric to estimate the ratio of useful to useless packet received. Simulations showed that this algorithm is more channel-efficient than the farthest-first strategy. It also exposes a parameter, allowing it to adapt to channel load. Second, this thesis presents a method of estimating channel load for providing feedback to moderate the offered load. A theoretical model showing the relationship between channel load and the idle time between transmissions is presented and used to estimate channel contention. Unsaturated stations on the network were shown to have small but observable effects on this relationship. In simulations, channel estimators based on this model show higher accuracy and faster convergence time than by observing packet collisions. These estimators are also less affected by unsaturated stations than by observing packet collisions. Third, this thesis couples the channel estimator to the geocast algorithm, producing a closed-loop load-reactive system that allows geocasts to adapt to instantaneous channel conditions. Simulations showed that this system is not only shown to be more efficient in channel use and be able to adapt to channel contention, but is also able to self-correct suboptimal retransmission decisions. Finally, this thesis demonstrates that all tested network simulators exhibit unexpected behaviours when simulating broadcasts. This thesis describes in depth the error in ns-3, leading to a set of workarounds that allows results from most versions of ns-3 to be interpreted correctly

Improving Vehicular ad hoc Network Protocols to Support Safety Applications in Realistic Scenarios

La convergencia de las telecomunicaciones, la informática, la tecnología inalámbrica y los sistemas de transporte, va a facilitar que nuestras carreteras y autopistas nos sirvan tanto como plataforma de transporte, como de comunicaciones. Estos cambios van a revolucionar completamente cómo y cuándo vamos a acceder a determinados servicios, comunicarnos, viajar, entretenernos, y navegar, en un futuro muy cercano. Las redes vehiculares ad hoc (vehicular ad hoc networks VANETs) son redes de comunicación inalámbricas que no requieren de ningún tipo de infraestructura, y que permiten la comunicación y conducción cooperativa entre los vehículos en la carretera. Los vehículos actúan como nodos de comunicación y transmisores, formando redes dinámicas junto a otros vehículos cercanos en entornos urbanos y autopistas. Las características especiales de las redes vehiculares favorecen el desarrollo de servicios y aplicaciones atractivas y desafiantes. En esta tesis nos centramos en las aplicaciones relacionadas con la seguridad. Específicamente, desarrollamos y evaluamos un novedoso protocol que mejora la seguridad en las carreteras. Nuestra propuesta combina el uso de información de la localización de los vehículos y las características del mapa del escenario, para mejorar la diseminación de los mensajes de alerta. En las aplicaciones de seguridad para redes vehiculares, nuestra propuesta permite reducir el problema de las tormentas de difusión, mientras que se mantiene una alta efectividad en la diseminación de los mensajes hacia los vehículos cercanos. Debido a que desplegar y evaluar redes VANET supone un gran coste y una tarea dura, la metodología basada en la simulación se muestra como una metodología alternativa a la implementación real. A diferencia de otros trabajos previos, con el fin de evaluar nuestra propuesta en un entorno realista, en nuestras simulaciones tenemos muy en cuenta tanto la movilidad de los vehículos, como la transmisión de radio en entornos urbanos, especialmente cuando los edificios interfieren en la propagación de la señal de radio. Con este propósito, desarrollamos herramientas para la simulación de VANETs más precisas y realistas, mejorando tanto la modelización de la propagación de radio, como la movilidad de los vehículos, obteniendo una solución que permite integrar mapas reales en el entorno de simulación. Finalmente, evaluamos las prestaciones de nuestro protocolo propuesto haciendo uso de nuestra plataforma de simulación mejorada, evidenciando la importancia del uso de un entorno de simulación adecuado para conseguir resultados más realistas y poder obtener conclusiones más significativas.Martínez Domínguez, FJ. (2010). Improving Vehicular ad hoc Network Protocols to Support Safety Applications in Realistic Scenarios [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/9195Palanci

On the Security of the Automatic Dependent Surveillance-Broadcast Protocol

Automatic dependent surveillance-broadcast (ADS-B) is the communications protocol currently being rolled out as part of next generation air transportation systems. As the heart of modern air traffic control, it will play an essential role in the protection of two billion passengers per year, besides being crucial to many other interest groups in aviation. The inherent lack of security measures in the ADS-B protocol has long been a topic in both the aviation circles and in the academic community. Due to recently published proof-of-concept attacks, the topic is becoming ever more pressing, especially with the deadline for mandatory implementation in most airspaces fast approaching. This survey first summarizes the attacks and problems that have been reported in relation to ADS-B security. Thereafter, it surveys both the theoretical and practical efforts which have been previously conducted concerning these issues, including possible countermeasures. In addition, the survey seeks to go beyond the current state of the art and gives a detailed assessment of security measures which have been developed more generally for related wireless networks such as sensor networks and vehicular ad hoc networks, including a taxonomy of all considered approaches.Comment: Survey, 22 Pages, 21 Figure

Artificial Intelligence-based Cybersecurity for Connected and Automated Vehicles

The damaging effects of cyberattacks to an industry like the Cooperative Connected and Automated Mobility (CCAM) can be tremendous. From the least important to the worst ones, one can mention for example the damage in the reputation of vehicle manufacturers, the increased denial of customers to adopt CCAM, the loss of working hours (having direct impact on the European GDP), material damages, increased environmental pollution due e.g., to traffic jams or malicious modifications in sensors’ firmware, and ultimately, the great danger for human lives, either they are drivers, passengers or pedestrians. Connected vehicles will soon become a reality on our roads, bringing along new services and capabilities, but also technical challenges and security threats. To overcome these risks, the CARAMEL project has developed several anti-hacking solutions for the new generation of vehicles. CARAMEL (Artificial Intelligence-based Cybersecurity for Connected and Automated Vehicles), a research project co-funded by the European Union under the Horizon 2020 framework programme, is a project consortium with 15 organizations from 8 European countries together with 3 Korean partners. The project applies a proactive approach based on Artificial Intelligence and Machine Learning techniques to detect and prevent potential cybersecurity threats to autonomous and connected vehicles. This approach has been addressed based on four fundamental pillars, namely: Autonomous Mobility, Connected Mobility, Electromobility, and Remote Control Vehicle. This book presents theory and results from each of these technical directions