Synergizing Roadway Infrastructure Investment with Digital Infrastructure for Infrastructure-Based Connected Vehicle Applications: Review of Current Status and Future Directions

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The safety, mobility, environmental and economic benefits of Connected and Autonomous Vehicles (CAVs) are potentially dramatic. However, realization of these benefits largely hinges on the timely upgrading of the existing transportation system. CAVs must be enabled to send and receive data to and from other vehicles and drivers (V2V communication) and to and from infrastructure (V2I communication). Further, infrastructure and the transportation agencies that manage it must be able to collect, process, distribute and archive these data quickly, reliably, and securely. This paper focuses on current digital roadway infrastructure initiatives and highlights the importance of including digital infrastructure investment alongside more traditional infrastructure investment to keep up with the auto industry's push towards this real time communication and data processing capability. Agencies responsible for transportation infrastructure construction and management must collaborate, establishing national and international platforms to guide the planning, deployment and management of digital infrastructure in their jurisdictions. This will help create standardized interoperable national and international systems so that CAV technology is not deployed in a haphazard and uncoordinated manner

AIM in-vehicle platform for ITS services

The application platform for intelligent mobility (AIM) is a large scale research infrastructure operated by the Institute of Transportation System of the German Aerospace Center (DLR) in the city and region of Braunschweig. The in-vehicle platform for ITS services (ITS, Intelligent Transportation Systems) is an integral part of this large-scale research facility. The in-vehicle platform for ITS services can be seen as a modular kit which enables up to 50 vehicles to take part in a Vehicle-to-Vehicle and Vehicle-to-Infrastructure (V2X) communications in test sites like the V2X reference track in the city of Braunschweig. The in-vehicle platform for ITS services along with its integration into the AIM test field provides answers to a broad set of research questions in the Field of V2X communications on public roads. For example effects can be analyzed, which take place when vehicles with mixed equipped communication technologies are sharing one road

Radio resource management for V2X in cellular systems

The thesis focuses on the provision of cellular vehicle-to-everything (V2X) communications, which have attracted great interest for 5G due to the potential of improving traffic safety and enabling new services related to intelligent transportation systems. These types of services have strict requirements on reliability, access availability, and end-to-end (E2E) latency. V2X requires advanced network management techniques that must be developed based on the characteristics of the networks and traffic requirements. The integration of the Sidelink (SL), which enables the direct communication between vehicles (i.e., vehicle-to-vehicle (V2V)) without passing through the base station into cellular networks is a promising solution for enhancing the performance of V2X in cellular systems. In this thesis, we addressed some of the challenges arising from the integration of V2V communication in cellular systems and validated the potential of this technology by providing appropriate resource management solutions. Our main contributions have been in the context of radio access network slicing, mode selection, and radio resource allocation mechanisms. With regard to the first research direction that focuses on the RAN slicing management, a novel strategy based on offline Q-learning and softmax decision-making has been proposed as an enhanced solution to determine the adequate split of resources between a slice for eMBB communications and a slice for V2X. Then, starting from the outcome of the off-line Q-learning algorithm, a low-complexity heuristic strategy has been proposed to achieve further improvements in the use of resources. The proposed solution has been compared against proportional and fixed reference schemes. The extensive performance assessment have revealed the ability of the proposed algorithms to improve network performance compared to the reference schemes, especially in terms of resource utilization, throughput, latency and outage probability. Regarding the second research direction that focuses on the mode selection, two different mode selection solutions referred to as MSSB and MS-RBRS strategies have been proposed for V2V communication over a cellular network. The MSSB strategy decides when it is appropriate to use one or the other mode, i.e. sidelink or cellular, for the involved vehicles, taking into account the quality of the links between V2V users, the available resources, and the network traffic load situation. Moreover, the MS-RBRS strategy not only selects the appropriate mode of operation but also decides efficiently the amount of resources needed by V2V links in each mode and allows reusing RBs between different SL users while guaranteeing the minimum signal to interference requirements. The conducted simulations have revealed that the MS-RBRS and MSSB strategies are beneficial in terms of throughput, radio resource utilization, outage probability and latency under different offered loads comparing to the reference scheme. Last, we have focused on the resource allocation problem including jointly mode selection and radio resource scheduling. For the mode selection, a novel mode selection has been presented to decide when it is appropriate to select sidelink mode and use a distributed approach for radio resource allocation or cellular mode and use a centralized radio resource allocation. It takes into account three aspects: the quality of the links between V2V users, the available resources, and the latency. As for the radio resource allocation, the proposed approach includes a distributed radio resource allocation for sidelink mode and a centralized radio resource allocation for cellular mode. The proposed strategy supports dynamic assignments by allowing transmission over mini-slots. A simulation-based analysis has shown that the proposed strategies improved the network performance in terms of latency of V2V services, packet success rate and resource utilization under different network loads.La tesis se centra en la provisión de comunicaciones para vehículos sistemas celulares (V2X: Vehicle to Everything), que han atraído un gran interés en el contexto de 5G debido a su potencial de mejorar la seguridad del tráfico y habilitar nuevos servicios relacionados con los sistemas inteligentes de transporte. Estos tipos de servicios tienen requisitos estrictos en términos fiabilidad, disponibilidad de acceso y latencia de extremo a extremo (E2E). Para ello, V2X requiere técnicas avanzadas de gestión de red que deben desarrollarse en función de las características de las redes y los requisitos de tráfico. La integración del Sidelink (SL), que permite la comunicación directa entre vehículos (es decir, vehículo a vehículo (V2V)) sin pasar por la estación base de las redes celulares, es una solución prometedora para mejorar el rendimiento de V2X en el sistema celular. En esta tesis, abordamos algunos de los desafíos derivados de la integración de la comunicación V2V en los sistemas celulares y validamos el potencial de esta tecnología al proporcionar soluciones de gestión de recursos adecuadas. Nuestras principales contribuciones han sido en el contexto del denominado "slicing" de redes de acceso radio, la selección de modo y los mecanismos de asignación de recursos radio. Respecto a la primera dirección de investigación que se centra en la gestión del RAN slicing, se ha propuesto una estrategia novedosa basada en Q-learning y toma de decisiones softmax como una solución para determinar la división adecuada de recursos entre un slice para comunicaciones eMBB y un slice para V2X. Luego, a partir del resultado del algoritmo de Q-learning, se ha propuesto una estrategia heurística de baja complejidad para lograr mejoras adicionales en el uso de los recursos. La solución propuesta se ha comparado con esquemas de referencia proporcionales y fijos. La evaluación ha revelado la capacidad de los algoritmos propuestos para mejorar el rendimiento de la red en comparación con los esquemas de referencia, especialmente en términos de utilización de recursos, rendimiento, y latencia . Con respecto a la segunda dirección de investigación que se centra en la selección de modo, se han propuesto dos soluciones de diferentes llamadas estrategias MSSB y MS-RBRS para la comunicación V2V a través de una red celular. La estrategia MSSB decide cuándo es apropiado usar el modo SL o el modo celular, para los vehículos involucrados, teniendo en cuenta la calidad de los enlaces entre los usuarios de V2V, los recursos disponibles y la situación de carga de tráfico de la red. Además, la estrategia MS-RBRS no solo selecciona el modo de operación apropiado, sino que también decide eficientemente la cantidad de recursos que los enlaces V2V necesitan en cada modo, y permite que los RB se reutilicen entre diferentes usuarios de SL al tiempo que garantiza requisitos mínimos de señal a interferencia. Se ha presentado un análisis basado en simulación para evaluar el desempeño de las estrategias propuestas. Finalmente, nos hemos centrado en el problema conjunto de la selección de modo y la asignación de recursos de radio. Para la selección de modo, se ha presentado una nueva estrategia para decidir cuándo es apropiado seleccionar el modo SL y usar un enfoque distribuido para la asignación de recursos de radio o el modo celular y usar la asignación de recursos de radio centralizada. Tiene en cuenta tres aspectos: la calidad de los enlaces entre los usuarios de V2V, los recursos disponibles y la latencia. En términos de asignación de recursos de radio, el enfoque propuesto incluye una asignación de recursos de radio distribuida para el modo SL y una asignación de recursos de radio centralizada para el modo celular. La estrategia propuesta admite asignaciones dinámicas al permitir la transmisión a través de mini-slots. Los resultados muestran las mejoras en términos de latencia, tasa de recepción y la utilización de recursos bajo diferentes cargas de red.Postprint (published version

5G evaluation platform for connected and autonomous vehicles

Connected vehicles are the next frontier in massive mobile communications. The field of vehicular communications has undergone a significant transformation and is interested in getting more vehicles connected to exchange essential information between vehicles and road infrastructure in order to improve traffic efficiency and safety. The introduction of the millimeter-wave (mmWave) region in 5G New Radio (NR), together with the latest release of 3rd Generation Partnership Project (3GPP) Release 16 (Rel. 16) to achieve higher data rates, autonomous vehicles are expected to push the limits of the cellular network by exploiting novel technologies, such as beamforming and massive MultipleInput Multiple-Output (MIMO). This potentially enables several Vehicle-to-Everything (V2X) use cases for cooperative automated driving and enhanced information services. The project proposes an approach of beam-based interference assessment for Vehicle-toVehicle (V2V) communications at mmWave. The perceived interference level is evaluated for a given beamset covering the full azimuthal range. This information provides useful insights on the quality of communications and the potential re-use rate of scheduled resources. In addition, the performance of 5G V2X physical-layer is evaluated by means of scheduling implementation

QoS-Balancing Algorithm for Optimal Relay Selection in Heterogeneous Vehicular Networks

Intelligent Transportation System (ITS) could facilitate communications among various road entities to improve the driver's safety and driving experience. These communications are called Vehicle-to-Everything (V2X) communications that can be supported by LTE-V2X protocols. Due to frequent changes of network topology in V2X, the source node (e.g., a vehicle) may have to choose a Device-to-Device(D2D) relay node to forward its packet to the destination node. In this paper, we propose a new method for choosing an optimal D2D relay node. The proposed method considers Quality of Service (QoS) requirements for selecting D2D relay nodes. It employs an Analytic Hierarchy Process (AHP) for making decisions. The decision criteria are linked with channel capacity, link stability and end-to-end delay. A number of simulations were performed considering various network scenarios to evaluate the performance of the proposed method. Simulation results show that the proposed method improves Packet Dropping Rate (PDR) by 30% and delivery ratio by 23% in comparison with the existing methods

Design Models for Trusted Communications in Vehicle-to-Everything (V2X) Networks

Intelligent transportation system is one of the main systems which has been developed to achieve safe traffic and efficient transportation. It enables the road entities to establish connections with other road entities and infrastructure units using Vehicle-to-Everything (V2X) communications. To improve the driving experience, various applications are implemented to allow for road entities to share the information among each other. Then, based on the received information, the road entity can make its own decision regarding road safety and guide the driver. However, when these packets are dropped for any reason, it could lead to inaccurate decisions due to lack of enough information. Therefore, the packets should be sent through a trusted communication. The trusted communication includes a trusted link and trusted road entity. Before sending packets, the road entity should assess the link quality and choose the trusted link to ensure the packet delivery. Also, evaluating the neighboring node behavior is essential to obtain trusted communications because some misbehavior nodes may drop the received packets. As a consequence, two main models are designed to achieve trusted V2X communications. First, a multi-metric Quality of Service (QoS)-balancing relay selection algorithm is proposed to elect the trusted link. Analytic Hierarchy Process (AHP) is applied to evaluate the link based on three metrics, which are channel capacity, link stability and end-to-end delay. Second, a recommendation-based trust model is designed for V2X communication to exclude misbehavior nodes. Based on a comparison between trust-based methods, weighted-sum is chosen in the proposed model. The proposed methods ensure trusted communications by reducing the Packet Dropping Rate (PDR) and increasing the end-to-end delivery packet ratio. In addition, the proposed trust model achieves a very low False Negative Rate (FNR) in comparison with an existing model

Automotive applications of high precision GNSS

This thesis aims to show that Global Navigation Satellite Systems (GNSS) positioning can play a significant role in the positioning systems of future automotive applications. This is through the adoption of state-of-the-art GNSS positioning technology and techniques, and the exploitation of the rapidly developing vehicle-to-vehicle concept. The merging together of these two developments creates greater performance than can be achieved separately. The original contribution of this thesis comes from this combination: Through the introduction of the Pseudo-VRS concept. Pseudo-VRS uses the princples of Network Real Time Kinematic (N-RTK) positioning to share GNSS information between vehicles, which enables absolute vehicle positioning. Pseudo-VRS is shown to improve the performance of high precision GNSS positioning for road vehicles, through the increased availability of GNSS correction messages and the rapid resolution of the N-RTK fixed solution. Positioning systems in the automotive sector are dominated by satellite-based solutions provided by GNSS. This has been the case since May 2001, when the United States Department of Defense switched off Selective Availability, enabling significantly improved positioning performance for civilian users. The average person most frequently encounters GNSS when using electronic personal navigation devices. The Sat Nav or GPS Navigator is ubiquitous in modern societies, where versions can be found on nomadic devices such as smartphones and dedicated personal navigation devices, or built in to the dashboards of vehicles. Such devices have been hugely successful due to their intrinsic ability to provide position information anywhere in the world with an accuracy of approximately 10 metres, which has proved ideal for general navigation applications. There are a few well known limitations of GNSS positioning, including anecdotal evidence of incorrect navigation advice for personal navigation devices, but these are minor compared to the overall positioning performance. Through steady development of GNSS positioning devices, including the integration of other low cost sensors (for instance, wheel speed or odometer sensors in vehicles), and the development of robust map matching algorithms, the performance of these devices for navigation applications is truly incredible. However, when tested for advanced automotive applications, the performance of GNSS positioning devices is found to be inadequate. In particular, in the most advanced fields of research such as autonomous vehicle technology, GNSS positioning devices are relegated to a secondary role, or often not used at all. They are replaced by terrestrial sensors that provide greater situational awareness, such as radar and lidar. This is due to the high performance demand of such applications, including high positioning accuracy (sub-decimetre), high availability and continuity of solutions (100%), and high integrity of the position information. Low-cost GNSS receivers generally do not meet such requirements. This could be considered an enormous oversight, as modern GNSS positioning technology and techniques have significantly improved satellite-based positioning performance. Other non-GNSS techniques also have their limitations that GNSS devices can minimise or eliminate. For instance, systems that rely on situational awareness require accurate digital maps of their surroundings as a reference. GNSS positioning can help to gather this data, provide an input, and act as a fail-safe in the event of digital map errors. It is apparent that in order to deliver advanced automotive applications - such as semi- or fully-autonomous vehicles - there must be an element of absolute positioning capability. Positioning systems will work alongside situational awareness systems to enable the autonomous vehicles to navigate through the real world. A strong candidate for the positioning system is GNSS positioning. This thesis builds on work already started by researchers at the University of Nottingham, to show that N-RTK positioning is one such technique. N-RTK can provide sub-decimetre accuracy absolute positioning solutions, with high availability, continuity, and integrity. A key component of N-RTK is the availability of real-time GNSS correction data. This is typically delivered to the GNSS receiver via mobile internet (for a roving receiver). This can be a significant limitation, as it relies on the performance of the mobile communications network, which can suffer from performance degradation during dynamic operation. Mobile communications systems are expected to improve significantly over the next few years, as consumers demand faster download speeds and wider availability. Mobile communications coverage already covers a high percentage of the population, but this does not translate into a high percentage of a country's geography. Pockets of poor coverage, often referred to as notspots, are widespread. Many of these notspots include the transportation infrastructure. The vehicle-to-vehicle concept has made significant forward steps in the last few years. Traditionally promoted as a key component of future automotive safety applications, it is now driven primarily by increased demand for in-vehicle infotainment. The concept, which shares similarities with the Internet of Things and Mobile Ad-hoc Networks, relies on communication between road vehicles and other road agents (such as pedestrians and road infrastructure). N-RTK positioning can take advantage of this communication link to minimise its own communications-related limitations. Sharing GNSS information between local GNSS receivers enables better performance of GNSS positioning, based on the principles of differential GNSS and N-RTK positioning techniques. This advanced concept is introduced and tested in this thesis. The Pseudo VRS concept follows the protocols and format of sharing GNSS data used in N-RTK positioning. The technique utilises the latest GNSS receiver design, including multiple frequency measurements and high quality antennas