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Security threats to cyber-physical systems are targeting institutions and infrastructure around the world, and the frequency and severity of attacks are on the rise. Healthcare manufacturing, financial services, education, government, and transportation are among the industries that are the most lucrative targets for adversaries. Hacking is not just about companies, organizations, or banks; it also includes critical infrastructure. Wireless Sensors Networks, Vehicle-to-everything communication (V2X), Dynamic Message Signs (DMS), and Traffic Signal Controllers are among major Intelligent Transportation Systems (ITS) infrastructure that has already been attacked or remain vulnerable to hacking. ITS has been deployed with a focus on increasing efficiency and safety in the face of dramatic increases in travel demand. Although many studies have been performed and many security primitives have been proposed, there are significant concerns about flawless performance in a dynamic environment. A holistic security approach, in which all infrastructure performs within the satisfactory level of security remains undiscovered. Previously, hacking of road infrastructure was a rare event, however, in recent years, field devices such as DMS are hacked with higher frequency. The primary reason that transportation assets are vulnerable to cyber-attacks is due to their location. A more dramatic scenario occurs when hackers attempt to convey tampered instructions to the public. Analyzing traveler behavior in response to the hacked messages sign on the basis of empirical data is a vital step toward operating a secure and reliable transportation system. There may be room for improvement by policymakers and program managers when considering critical infrastructure vulnerabilities. With cybersecurity issues escalating every day, road users' safety has been neglected. This dissertation overcomes these challenges and contributes to the nascent but growing literature of Intelligent Transportation System (ITS) security impact-oriented risk assessment in threefold. • First, I employ a risk-based approach to conduct a threat assessment. This threat assessment performs a qualitative vulnerability-oriented threat analysis. The objective is to scrutinize safety, security, reliability, and operation issues that are prompted by a compromised Dynamic Message Signs (DMS). • Second, I examine the impact of drivers' attitudes and behaviors on compliance, route diversion behavior, and speed change behavior, under a compromised DMS. We aim to assess the determinants that are likely to contribute to drivers' compliance with forged information. To this extent, this dissertation evaluates drivers' behavior under different unauthentic messages to assess in-depth the impact of an adversarial attack on the transportation network. • Third, I evaluate distracted driving under different scenarios to assess the in-depth impact of an adversarial attack on the transportation network. To this extent, this dissertation examines factors that are contributing to the manual, visual, and cognitive distractions when drivers encountering fabricated advisory information at a compromised DMS. The results of this dissertation support the original hypothesis and indicate that with respect to the forged information drivers tend to (1) change their planned route, (2) become involved in distracting activities, and (3) change their choice speed at the presence of a compromised DMS. The main findings of this dissertation are outlined below: 1. The DMS security vulnerabilities and predisposing conditions allow adversaries to compromise ITS functionality. The risk-based approach of this study delivers the impact-likelihood matrix, which maps the adverse impacts of the threat events onto a meaningful, visual, matrix. DMS hacking adverse impacts can be categorized mainly as high-risk and medium-risk clusters. The safety, operational (i.e., monetary losses) and behavioral impacts are associated with a high-risk cluster. While the security, reliability, efficiency, and operational (i.e., congestion) impacts are associated with the medium-risk cluster. 2. Tech friendly drivers are more likely to change their route under a compromised DMS. At the same time, while they are acquiring new information, they need to lowering their speed to respond to the higher information load. Under realistic-fabricated information, about 65% of the subjects would depart from their current route. The results indicate that females and subjects with a higher driving experience are more likely to change their route. In addition, those subjects who are more sensitive to the DMS's traffic-related messages and those who use DMS under congested traffic condition are more likely to divert. Interestingly, individuals with lower education level, Asians, those who live in urban areas, and those with trouble finding their direction in new routes are less likely to pick another route rather the one they planned for. 3. Regardless of the DMS hacking scenarios, drivers would engage in at least one of the distractive activities. Among the distractive activities, cognitive distraction has the highest impact on the distracted driving likelihood. Meaning, there is a high chance that drivers think of something other than driving, look at surrounding traffic and scenery, or talk to other passengers regarding the forged information they saw on the DMS. Drivers who rely and trust in technology, and those who check traffic condition before starting their trips tend to become distracted. In addition, the result identified that at the presence of bogus information, drivers tend to slow down or stop in order to react to the DMS. That is, they would either (1) become involved in activities through the means of their phone, (2) they would mind wander, look around, and talk to a passenger about the sign, and (3) search for extra information by means of their vehicle's radio or internet. 4. Females, black individuals, subjects with a disability, older, and those with high trust in DMS are less likely to ignore the fabricated messages. In contrary, white, those who drive long hours, and those who see driving as a tedious task are more likely to ignore the bogus messages. Drivers who comply with traffic regulations and have a good driving record are likely to slow down under the tampered messages. Furthermore, female drivers and those who live in rural areas are more likely to slow down under fabricated advisory information. Furthermore, this dissertation identifies that planning for alternative route and involvement in distractive activities cause speed variation behaviors under the compromised DMS. This dissertation is the first to investigate the adverse impact of a compromised DMS on the road users and operators. I attempt to address the current gap in the literature by assessing and evaluating the impact of ITS security vulnerabilities. Broader impacts of this study include (1) to systematically raising awareness among policy-makers and engineers, (2) motivating further simulations and real-world experiments to investigate this matter further, (3) to systematically assessing the adverse impact of a security breach on transportation reliability and safety, and drivers' behavior, and (4) providing insights for system operators and decision-makers to prioritize the risk of a compromised DMS. Additionally, the outcome can be integrated with the nationwide connected vehicle and V2X implementations and security design. / Doctor of Philosophy / Security threats are targeting institutions and infrastructure around the world, and the frequency and severity of security attacks are on the rise. Healthcare manufacturing, financial services, education, government, and transportation are among the industries that are the most lucrative targets for adversaries. Hacking is not just about companies, organizations, or banks; it also includes critical infrastructure. Intelligent Transportation Systems have been deployed with a focus on increasing efficiency and safety in the face of dramatic increases in traffic volume. Although many studies have been performed and many security primitives have been proposed, there are significant concerns about flawless performance in a dynamic environment. A holistic security approach, in which all infrastructure performs within the satisfactory level of security remains undiscovered. Previously, hacking of road infrastructure was a rare event, however, in recent years, field devices, such as dynamic message signs, are hacked with higher frequency. The primary reason that transportation assets are vulnerable to cyber-attacks is that of their location in public. A more dramatic scenario occurs when hackers attempt to convey tampered instructions to the public. Analyzing traveler behavior in response to the hacked messages sign on the basis of empirical data is a vital step toward operating a secure and reliable transportation system. This study is the first to investigate the adversarial impact of a compromised message sign on the road users and operators. I attempt to address the current gap in the literature by assessing and evaluating the impact of ITS security vulnerabilities.

The rapid growth of population and the permanent increase in the number of vehicles engender several issues in transportation systems, which in turn call for an intelligent and cost-effective approach to resolve the problems in an efficient manner. A cost-effective approach for improving and optimizing transportation-related problems is to unlock hidden knowledge in ever-increasing spatiotemporal and crowdsourced information collected from various sources such as mobile phone sensors (e.g., GPS sensors) and social media networks (e.g., Twitter). Data mining and machine learning techniques are the major tools for analyzing the collected data and extracting useful knowledge on traffic conditions and mobility behaviors. Deep learning is an advanced branch of machine learning that has enjoyed a lot of success in computer vision and natural language processing fields in recent years. However, deep learning techniques have been applied to only a small number of transportation applications such as traffic flow and speed prediction. Accordingly, my main objective in this dissertation is to develop state-of-the-art deep learning architectures for resolving the transport-related applications that have not been treated by deep learning architectures in much detail, including (1) travel mode detection, (2) vehicle classification, and (3) traffic information system. To this end, an efficient representation for spatiotemporal and crowdsourced data (e.g., GPS trajectories) is also required to be designed in such a way that not only be adaptable with deep learning architectures but also contains efficient information for solving the task-at-hand. Furthermore, since the good performance of a deep learning algorithm is primarily contingent on access to a large volume of training samples, efficient data collection and labeling strategies are developed for different data types and applications. Finally, the performance of the proposed representations and models are evaluated by comparing to several state-of-the-art techniques in literature. The experimental results clearly and consistently demonstrate the superiority of the proposed deep-learning based framework for each application. / PHD / The rapid growth of population and the permanent increase in the number of vehicles engender several issues in transportation systems, which in turn call for an intelligent and cost-effective approach to resolve the problems in an efficient manner. Furthermore, the recent advances in positioning tools (e.g., GPS sensors) and ever-popularity of social media networks have enabled generation of massive spatiotemporal and crowdsourced data. This dissertation aims to leverage the advances in artificial intelligence so as to unlock the rick knowledge in the recorded data and in turn, optimizing the transportation systems in a cost-effective way. In particular, this dissertation seeks for proposing end-to-end frameworks based on deep learning models, as an advanced branch of artificial intelligence, as well as spatiotemporal and crowdsourced datasets (e.g., GPS trajectory and social media) for improving three transportation problems. (1) Travel Mode Detection, which is defined as identifying users’ transportation mode(s) (e.g., walk, bike, bus, car, and train) when traveling around the traffic network. (2) Vehicle Classification, which is defined as identifying the vehicle’s type (e.g., passenger car and truck) while moving in a traffic network. (3) traffic information system based on social media networks, which is defined as detecting traffic events (e.g., crash) and capturing traffic information (e.g., traffic congestion) on a real-time basis from users’ tweets. The experimental results clearly and consistently demonstrate the superiority of the proposed deep-learning based framework for each application.

A pesar de que las medidas de seguridad en los sistemas de transporte cada vez son mayores, el aumento progresivo del número de vehículos que circulan por las ciudades y carreteras en todo el mundo aumenta, sin duda, la probabilidad de que ocurra un accidente. En este tipo de situaciones, el tiempo de respuesta de los servicios de emergencia es crucial, ya que está demostrado que cuanto menor sea el tiempo transcurrido entre el accidente y la atención hospitalaria de los heridos, mayores son sus probabilidades de supervivencia. Las redes vehiculares permiten la comunicación entre los vehículos, así como la comunicación entre los vehículos y la infraestructura [4], lo que da lugar a una plétora de nuevas aplicaciones y servicios en el entorno vehicular. Centrándonos en las aplicaciones relacionadas con la seguridad vial, mediante este tipo de comunicaciones, los vehículos podrían informar en caso de accidente al resto de vehículos (evitando así colisiones en cadena) y a los servicios de emergencia (dando información precisa y rápida, lo que sin duda facilitaría las tareas de rescate). Uno de los aspectos importantes a determinar sería saber qué información se debe enviar, quién será capaz de recibirla, y cómo actuar una vez recibida. Actualmente los vehículos disponen de una serie de sensores que les permiten obtener información sobre ellos mismos (velocidad, posición, estado de los sistemas de seguridad, número de ocupantes del vehículo, etc.), y sobre su entorno (información meteorológica, estado de la calzada, luminosidad, etc.). En caso de accidente, toda esa información puede ser estructurada y enviada a los servicios de emergencia para que éstos adecúen el rescate a las características específicas y la gravedad del accidente, actuando en consecuencia. Por otro lado, para que la información enviada por los vehículos accidentados pueda llegar correctamente a los servicios de emergencias, es necesario disponer de una infraestructura capaz de dar cobertura a todos los vehículos que circulan por una determinada área. Puesto que la instalación y el mantenimiento de dicha infraestructura conllevan un elevado coste, sería conveniente proponer, implementar y evaluar técnicas consistentes en dar cobertura a todos los vehículos, reduciendo el coste total de la infraestructura. Finalmente, una vez que la información ha sido recibida por las autoridades, es necesario elaborar un plan de actuación eficaz, que permita el rápido rescate de los heridos. Hay que tener en cuenta que, cuando ocurre un accidente de tráfico, el tiempo de personación de los servicios de emergencia en el lugar del accidente puede suponer la diferencia entre que los heridos sobrevivan o fallezcan. Además, es importante conocer si la calle o carretera por la que circulaban los vehículos accidentados ha dejado de ser transitable para el resto de vehículos, y en ese caso, activar los mecanismos necesarios que permitan evitar los atascos asociados. En esta Tesis, se pretende gestionar adecuadamente estas situaciones adversas, distribuyendo el tráfico de manera inteligente para reducir el tiempo de llegada de los servicios de emergencia al lugar del accidente, evitando además posibles atascos. / Barrachina Villalba, J. (2014). Using Ontologies and Intelligent Systems for Traffic Accident Assistance in Vehicular Environments [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/39004

[EN] Intelligent Transportation Systems (ITS) can make transportation safer, more efficient, and more sustainable by applying various information and communication technologies. One of these technologies are \acfp{VN}. \acp{VN} combine different communication solutions such as cellular networks, \acfp{VANET}, or IEEE 802.11 technologies to provide connectivity among vehicles, and between vehicles and road infrastructure. This thesis focuses on VNs, and considers that the high speed of the nodes and the presence of obstacles like buildings, produces a highly variable network topology, as well as more frequent partitions in the network. Therefore, classical \ac{MANET} protocols do not adapt well to VANETs. Under these conditions, \ac{DTN} have been proposed as an alternative able to cope with these adverse characteristics. In DTN, when a message cannot be routed to its destination, it is not immediately dropped but it is instead stored and carried until a new route becomes available. The combination of VN and DTN is called \acp{VDTN}. In this thesis, we propose a new VDTN protocol designed to collect information from vehicular sensors. Our proposal, called \ac{MSDP}, combines information about the localization obtained from a GNSS system with the actual street/road layout obtained from a Navigation System (NS) to define a new routing metric. Both analytical and simulation results prove that MSDP outperforms previous proposals. Concerning the deployment of VNs and VANET technologies, technology already left behind the innovation and the standardization phases, and it is about time it reach the first early adopters in the market. However, most car manufacturers have decided to implement VN devices in the form of On Board Units (OBUs), which are expensive, heavily manufacturer dependent, and difficult to upgrade. These facts are delaying the deployment of VN. To boost this process, we have developed the GRCBox architecture. This architecture is based on low-cost devices and enables the establishment of V2X, \emph{i.e.} V2I and V2V, communications while integrating users by easing the use of general purpose devices like smartphones, tablets or laptops. To demonstrate the viability of the GRCBox architecture, we combined it with a DTN platform called Scampi to obtain actual results over a real VDTN scenario. We also present several GRCBox-aware applications that illustrate how developers can create applications that bring the potential of VN to user devices. / [ES] Los sistemas de transporte inteligente (ITS) son el soporte para el establecimiento de un transporte más seguro, más eficiente y más sostenible mediante el uso de tecnologías de la información y las comunicaciones. Una de estas tecnologías son las redes vehiculares (VNs). Las VNs combinan diferentes tecnologías de comunicación como las redes celulares, las redes ad-hoc vehiculares (VANETs) o las redes 802.11p para proporcionar conectividad entre vehículos, y entre vehículos y la infraestructura de carreteras. Esta tesis se centra en las VNs, en las cuales la alta velocidad de los nodos y la presencia de obstáculos como edificios producen una topología de red altamente variable, así como frecuentes particiones en la red. Debido a estas características, los protocolos para redes móviles ad-hoc (MANETs) no se adaptan bien a las VANETs. En estas condiciones, las redes tolerantes a retardos (DTNs) se han propuesto como una alternativa capaz de hacer frente a estos problemas. En DTN, cuando un mensaje no puede ser encaminado hacia su destino, no es inmediatamente descartado sino es almacenado hasta que una nueva ruta esta disponible. Cuando las VNs y las DTNs se combinan surgen las redes vehiculares tolerantes a retardos (VDTN). En esta tesis proponemos un nuevo protocolo para VDTNs diseñado para recolectar la información generada por sensores vehiculares. Nuestra propuesta, llamada MSDP, combina la información obtenida del servicio de información geográfica (GIS) con el mapa real de las calles obtenido del sistema de navegación (NS) para definir una nueva métrica de encaminamiento. Resultados analíticos y mediante simulaciones prueban que MSDP mejora el rendimiento de propuestas anteriores. En relación con el despliegue de las VNs y las tecnologías VANET, la tecnología ha dejado atrás las fases de innovación y estandarización, ahora es el momento de alcanzar a los primeros usuarios del mercado. Sin embargo, la mayoría de fabricantes han decidido implementar los dispositivos para VN como unidades de a bordo (OBU), las cuales son caras y difíciles de actualizar. Además, las OBUs son muy dependientes del fabricante original. Todo esto esta retrasando el despliegue de las VNs. Para acelerar la adopción de las VNs, hemos desarrollado la arquitectura GRCBox. La arquitectura GRCBox esta basada en un dispositivo de bajo coste que permite a los usuarios usar comunicaciones V2X (V2V y V2I) mientras utilizan dispositivos de propósito general como teléfonos inteligentes, tabletas o portátiles. Las pruebas incluidas en esta tesis demuestran la viabilidad de la arquitectura GRCBox. Mediante la combinación de nuestra GRCBox y una plataforma de DTN llamada Scampi hemos diseñado y probado un escenario VDTN real. También presentamos como los desarrolladores pueden crear nuevas aplicaciones GRCBox para llevar el potencial de las VN a los dispositivos de usuario. / [CA] Els sistemes de transport intel·ligent (ITS) poden crear un transport més segur, més eficient i més sostenible mitjançant l'ús de tecnologies de la informació i les comunicacions aplicades al transport. Una d'aquestes tecnologies són les xarxes vehiculars (VN). Les VN combinen diferents tecnologies de comunicació, com ara les xarxes cel·lulars, les xarxes ad-hoc vehiculars (VANET) o les xarxes 802.11p, per a proporcionar comunicació entre vehicles, i entre vehicles i la infraestructura de carreteres. Aquesta tesi se centra en les VANET, en les quals l'alta velocitat dels nodes i la presència d'obstacles, com els edificis, produeixen una topologia de xarxa altament variable, i també freqüents particions en la xarxa. Per aquest motiu, els protocols per a xarxes mòbils ad-hoc (MANET) no s'adapten bé. En aquestes condicions, les xarxes tolerants a retards (DTN) s'han proposat com una alternativa capaç de fer front a aquests problemes. En DTN, quan un missatge no pot ser encaminat cap a la seua destinació, no és immediatament descartat sinó que és emmagatzemat fins que apareix una ruta nova. Quan les VN i les DTN es combinen sorgeixen les xarxes vehicular tolerants a retards (VDTN). En aquesta tesi proposem un nou protocol per a VDTN dissenyat per a recol·lectar la informació generada per sensors vehiculars. La nostra proposta, anomenada MSDP, combina la informació obtinguda del servei d'informació geogràfica (GIS) amb el mapa real dels carrers obtingut del sistema de navegació (NS) per a definir una nova mètrica d'encaminament. Resultats analítics i mitjançant simulacions proven que MSDP millora el rendiment de propostes prèvies. En relació amb el desplegament de les VN i les tecnologies VANET, la tecnologia ha deixat arrere les fases d'innovació i estandardització, ara és temps d'aconseguir als primers usuaris del mercat. No obstant això, la majoria de fabricants han decidit implementar els dispositius per a VN com a unitats de bord (OBU), les quals són cares i difícils d'actualitzar. A més, les OBU són molt dependents del fabricant original. Tot això està retardant el desplegament de les VN. Per a accelerar l'adopció de les VN, hem desenvolupat l'arquitectura GRCBox. L'arquitectura GRCBox està basada en un dispositiu de baix cost que permet als usuaris usar comunicacions V2V mentre usen dispositius de propòsit general, com ara telèfons intel·ligents, tauletes o portàtils. Les proves incloses en aquesta tesi demostren la viabilitat de l'arquitectura GRCBox. Mitjançant la combinació de la nostra GRCBox i la plataforma de DTN Scampi, hem dissenyat i provat un escenari VDTN pràctic. També presentem com els desenvolupadors poden crear noves aplicacions GRCBox per a portar el potencial de les VN als dispositius d'usuari. / Martínez Tornell, S. (2016). Delay Tolerant Networks for Efficient Information Harvesting and Distribution in Intelligent Transportation Systems [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/68486

[ES] Para proporcionar un entorno de tráfico vial más seguro y eficiente, los sistemas ITS o Sistemas Inteligentes de Transporte representan como una solución dotada de avances tecnológicos de vanguardia. La integración de elementos de transporte como automóviles junto con elementos de infraestructura como RoadSide Units (RSUs) ubicados a lo largo de la vía de comunicación permiten ofrecer un entorno de red conectado con múltiples servicios, incluida conectividad a Internet. Esta integración se conoce con el término C-ITS o Sistemas Inteligentes de Transporte Cooperativos. La conexión de automóviles con dispositivos de infraestructura permite crear redes vehiculares conectadas (V2X) vehículo a dispositivos, que ofrecen la posibilidad de nuevos despliegues en aplicaciones C-ITS como las relacionadas con la seguridad. Hoy en día, con el uso masivo de teléfonos inteligentes y debido a su flexibilidad y movilidad, existen varios esfuerzos para integrarlos con los automóviles. De hecho, con el soporte adecuado de unidad a bordo (OBU), los teléfonos inteligentes se pueden integrar perfectamente con las redes vehiculares, permitiendo a los conductores usar sus teléfonos inteligentes como dispositivos de bordo a que participan en los servicios C-ITS, con el objeto de mejorar la seguridad al volante entre otros. Tópico este, que hoy día representa un tema relevante de investigación. Un problema a solucionar surge cuando las comunicaciones vehiculares sufren inferencias y bloqueos de la señal debidos al escenario. De hecho, el impacto de la vegetación y los edificios, ya sea en áreas urbanas y rurales, puede afectar a la calidad de la señal. Algunas estrategias para mejorar la comunicación vehicular en este tipo de entorno consiste en desplegar UAVs o vehículo aéreo no tripulado (drones), los cuales actúan como enlaces de comunicación entre vehículos. De hecho, UAV ofrece importantes ventajas de implementación, ya que tienen una gran flexibilidad en términos de movilidad, además de un rango de comunicaciones mejorado. Para evaluar la calidad de las comunicaciones, debe realizarse un conjunto de mediciones. Sin embargo, debido al costo de las implementaciones reales de UAV y automóviles, los experimentos reales podrían no ser factibles para actividades de investigación con recursos limitados. Por lo tanto, los experimentos de simulación se convierten en la opción preferida para evaluar las comunicaciones entre UAV y vehículos terrestres. Lograr modelos de propagación de señal correctos y representativos que puedan importarse a los entornos de simulación se vuelve crucial para obtener un mayor grado de realismo, especialmente para simulaciones que involucran el movimiento de UAVs en cualquier lugar del espacio 3D. En particular, la información de elevación del terreno debe tenerse en cuenta al intentar caracterizar los efectos de propagación de la señal. En esta tesis doctoral, proponemos nuevos enfoques tanto teóricos como empíricos para estudiar la integración de redes vehiculares que combinan automóviles y UAVs, así mismo el impacto del entorno en la calidad de las comunicaciones. Esta tesis presenta una aplicación, una metodología de medición en escenarios reales y un nuevo modelo de simulación, los cuales contribuyen a modelar, desarrollar e implementar servicios C-ITS. Más específicamente, proponemos un modelo de simulación que tiene en cuenta las características del terreno en 3D, para lograr resultados confiables de comunicación entre UAV y vehículos terrestres. / [CA] Per a proporcionar un entorn de trànsit viari més segur i eficient, els sistemes ITS o Sistemes Intel·ligents de Transport representen una solució dotada d'avanços tecnològics d'avantguarda. La integració d'elements de transport com auto móvils juntament amb elements d'infraestructura com Road Side Units (RSUs) situats al llarg de lav via de comunicació permeten oferir un entorn de xarxa connectat amb multiples serveis, inclusa connectivitat a Internet. Aquesta integració es connex amb el terme C-ITS o Sistemes Intel·ligents de Transport Cooperatius , com ara els automòbils, amb elements d'infraestructura, com ara les road side units (RSU) o pals situats al llarg de la carretera, per a aconseguir un entorn de xarxa que oferisca nous serveis a més de connectivitat a Internet. Aquesta integració s'expressa amb el terme C-ITS, o sistemes intel·ligents de transport cooperatius. La connexió d'automòbils amb dispositius d'infraestructura permet crear xarxes vehiculars connectades (V2X) vehicle a dispositiu, que ofreixen la possibilitat de nous desplegaments en aplicacions C-ITS, com ara les relacionades amb la seguretat. Avui dia, amb l'ús massiu dels telèfons intel·ligents, i a causa de la flexibilitat i mobilitat que presenten, es fan esforços per integrar-los amb els automòbils. De fet, amb el suport adequat d'unitat a bord (OBU), els telèfons intel·ligents es poden integrar perfectament amb les xarxes vehiculars, permetent als conductors usar els seus telèfons intel·ligents com a dispositius per a participar en els serveis de C-ITS, a fi de millorar la seguretat al volant entre altres. Tòpic est, que hui dia representa un tema rellevant d'investigació. Un problema a solucionar sorgeix quan les comunicacions vehiculars ateixen inferències i bloquejos del senyal deguts a l'escenari. De fet, l'impacte de la vegetació i els edificis, tant en àrees urbanes com rurals, pot afectar la qualitat del senyal. Algunes estratègies de millorar la comunicació vehicular en aquest tipus d'entorn consisteix a desplegar UAVs o vehicles aeris no tripulats (drones), els quals actuen com a enllaços de comunicació entre vehicles. De fet, l'ús d'UAVs ofereix importants avantatges d'implementació, ja que tenen una gran flexibilitat en termes de mobilitat, a més d'un rang de comunicacions millorat. Per a avaluar la qualitat de les comunicacions, s'han de realitzar mesures en escenaris reals. No obstant això, a causa del cost de les implementacions i desplegaments reals d'UAV i el seu ús combinat amb vehicles, aquests experiments reals podrien no ser factibles per a activitats d'investigació amb recursos limitats. Per tant, la metodologia basada en simulació es converteixen en l'opció preferida entre els investigadors per a avaluar les comunicacions entre UAV i vehicles terrestres. Aconseguir models de propagació de senyal correctes i representatius que puguen importar-se als entorns de simulació resulta crucial per a obtenir un major grau de realisme, especialment per a simulacions que involucren el moviment d'UAV en qualsevol lloc de l'espai 3D. En particular, cal tenir en compte la informació d'elevació del terreny per a intentar caracteritzar els efectes de propagació del senyal. En aquesta tesi doctoral proposem enfocaments tant teòrics com empírics per a estudiar la integració de xarxes vehiculars que combinen automòbils i UAV, així com l'impacte de l'entorn en la qualitat de les comunicacions. Aquesta tesi presenta una aplicació, una metodología de mesurament en escenaris reals i un nou model de simulació, els quals contribueixen a modelar, desenvolupar i implementar serveis C-ITS. Més específicament, proposem un model de simulació que té en compte les característiques del terreny en 3D, per a aconseguir resultats fiables de comunicació entre UAV i vehicles terrestres. / [EN] To provide a safer road traffic environment and make it more convenient, Intelligent Transport Systems (ITSs) are proposed as a solution endowed with cutting-edge technological advances. The integration of transportation elements like cars together with infrastructure elements like Road Side Units to achieve a networking environment offers new services in addition to Internet connectivity. This integration comes under the term Cooperative Intelligent Transport System (C-ITS). Connecting cars with surrounding devices forming vehicular networks in Vehicle-to-Everything (V2X) open new deployments in C-ITS applications like safety-related ones. With the massive use of smartphones nowadays, and due to their flexibility and mobility, several efforts exist to integrate them with cars. In fact, with the right support from the vehicle's On-Board Unit (OBU), smartphones can be seamlessly integrated with vehicular networks. Hence, drivers can use their smartphones as a device to participate in C-ITS services for safety purposes, among others, which is a quite interesting research topic. A significant problem arises when vehicular communications face signal obstructions caused by the environment. In fact, the impact of vegetation and buildings, whether in urban and rural areas, can result in a lower signal quality. One way to enhance vehicular communication networks is to deploy Unmanned Aerial Vehicles (UAVs) to act as relays for communication between cars, or ground vehicles. In fact, UAVs offer important deployment advantages, as they offer great flexibility in terms of mobility, in addition to an enhanced communications range. To assess the quality of the communications, a set of measurements must take place. However, due to the cost of real deployments of UAVs and cars, real experiments might not be feasible for research activities with limited resources. Hence, simulation experiments become the preferred option to assess UAV-to- car communications. Achieving correct and representative signal propagation models that can be imported to the simulation environments becomes crucial to obtain a higher degree of realism, especially for simulations involving UAVs moving anywhere throughout the 3D space. In particular, terrain elevation information must be taken into account when attempting to characterize signal propagation effects. In this research work, we propose both theoretical and empirical approaches to study the integration of vehicular networks combining cars and UAVs, and we study the impact of the surrounding environment on the communications quality. An application, a measurement framework, and a simulation model are presented in this thesis in an effort to model, develop, and deploy C-ITS services. More specifically, we propose a simulation model that takes into account 3D terrain features to achieve reliable UAV-to-car communication results. / I want to thank the Spanish government through the Ministry of Economy and Competitiveness (MINECO) and the European Union Commission through the European Social Fund (ESF) for co-financing and granting me the fellowship to fund my studies in Spain and my research stay in Russia. In addition, I would to thank the National Institute of Informatics for granting me the internship fund and the Japanese government through the Japan Society for the Promotion of Science (JSPS) for supporting my research work in Japan. / Hadiwardoyo, SA. (2019). Modelling and Real Deployment of C-ITS by Integrating Ground Vehicles and Unmanned Aerial Vehicles [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/118796

Yes / Blockchain operates on a highly secured framework, and its decentralized consensus has benefits for supply chain sustainability. Scholars have recognized the growing importance of sustainability in supply chains and studied the potential of blockchain for sustainable supply chain management. However, no study has taken stock of high-quality research in this area. To address this gap, this paper aims to provide a state-of-the-art overview of high-quality research on blockchain for sustainable supply chain management. To do so, this paper conducts a systematic literature review using a bibliometric analysis of 146 high-quality articles on blockchain for sustainable supply chain management that have been published in journals ranked “A*”, “A”, and “B” by the Australian Business Deans Council and retrieved from the Scopus database. In doing so, this paper unpacks the most prominent journals, authors, institutions, and countries that have contributed to three major themes in the field, namely blockchain for sustainable business activities, decision support systems using blockchain, and blockchain for intelligent transportation system. This paper also reveals the use of blockchain for sustainable supply chain management across four major sectors, namely food, healthcare, manufacturing, and infrastructure, and concludes with suggestions for future research in each sector.

Automobile accidents are one of the leading causes of death and claim more than 40,000 lives annually in the US alone. A substantial portion of these accidents occur at road intersections. Stop signs and traffic signals are some of the intersection control devices used to increase safety and prevent collisions. However, these devices themselves can contribute to collisions, are costly, inefficient, and are prone to failure. This thesis proposes an adaptive, decentralized, cooperative collision avoidance (CCA) system that optimizes each vehicle's controls subject to the constraint that no collisions occur. Three major contributions to the field of collision avoidance have resulted from this research. First, a nonlinear 5-state variable vehicle model is expanded from an earlier model developed in [1]. The model accounts for internal engine characteristics and more realistically approximates vehicle behavior in comparison to idealized, linear models. Second, a set of constrained, coupled Extended Kalman Filters (EKF) are used to predict the trajectory of the vehicles approaching an intersection in real-time. The coupled filters support decentralized operation and ensure that the optimization algorithm bases its decisions on good, reliable estimates. Third, a vehicular network based on the new WAVE standard is presented that provides cooperative capabilities by enabling intervehicle communication. The system is simulated against today's common intersection control devices and is shown to be superior in minimizing average vehicle delay. / Master of Science

Esta dissertação propõe um modelo tecnológico de automação para realização de pesquisas no setor do transporte público, com o objetivo de contribuir para o aprimoramento da coleta de dados, avaliação e manutenção da qualidade dos serviços prestados à população. O trabalho justifica-se pela necessidade de superação de lacunas existentes para obtenção de informações, o que repercute na gestão do sistema de transporte público como um todo. Devido à relevância crescente do tema da mobilidade urbana e os impactos que provoca na qualidade de vida das pessoas, o objeto de estudo escolhido foram os deslocamentos dos passageiros por meio do uso de ônibus na cidade de São Paulo. O modelo proposto integra a tecnologia de identificação por radiofrequência (RFID - Radio Frequency IDentification), em cartões inteligentes, utilizados atualmente para pagar a tarifa, com tecnologias de rastreamento da frota, que, por meio de GPS (Global Position Systems), fornecem informações sobre os locais de circulação dos ônibus. Os resultados obtidos mostram que esta integração pode resolver os problemas da falta de precisão no levantamento de dados sobre os locais onde são iniciadas e finalizadas as viagens de passageiros, bem como tornar sistemáticos os levantamentos de tais dados, sem necessidade de pesquisas manuais, o que representa economia de recursos. Constitui uma proposta inovadora com grande utilidade para ampliar as condições que favorecem a mobilidade urbana e é convergente no desenvolvimento de cidades inteligentes. / This dissertation proposes a technological model for automation for conducting surveys in the public transport sector, in order to contribute to the improvement of data collection, evaluation and maintenance of quality of services rendered to the population. The work is justified by the need to overcome gaps for obtaining information, which affects the management of the public transport system as a whole. Due to the increasing relevance of the issue of urban mobility and its impact on quality of life, the chosen object of study were the passenger movements through the bus use in the city of São Paulo. The proposed model integrates the radio frequency identification technology - RFID, on smart cards currently used to pay the fare, with fleet tracking technologies, which, through GPS (Global Position Systems), provide information on the bus traffic locations. The results show that this integration can solve the problems of lack of precision in data about where passenger trips are initiated and completed as well as make systematic withdrawals of such data without the need for manual searches, saving features. It is an innovative proposal with great use to expand the conditions that improve urban mobility and is convergent to the development of smart cities.

This work presents the implementations of three adaptive broadcast protocols for vehicular ad hoc networks (VANET) using the Network Simulator 3 (Ns-3). Performing real life tests for VANET protocols is very costly and risky, so simulation becomes a viable alternative technique. Ns-3 is one of the most advanced open source network simulators. Yet Ns-3 lacks implementations of broadcast protocols for VANET. We first implement the Distance to Mean (DTM) protocol, which uses the distance to mean to determine if a node should rebroadcast or not. We then implement the Distribution-Adaptive Distance with Channel Quality (DADCQ) protocol, which uses node distribution, channel quality and distance to determine if a node should favor rebroadcasting. The third protocol, Statistical Location-Assisted Broadcast protocol (SLAB), is an improvement of DADCQ which automates the threshold function design using machine learning. Our NS-3 implementations of the three protocols have been validated against their JiST/SWANS implementations. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2016. / FAU Electronic Theses and Dissertations Collection