Modelling and Real Deployment of C-ITS by Integrating Ground Vehicles and Unmanned Aerial Vehicles

[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 no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/118796TESI

Experimental characterization of UAV-to-car communications

[EN] Unmanned Aerial Vehicles (UAVs), popularly known as drones, can be deployed in conjunction with a network of ground vehicles. In situations where no infrastructure is available, drones can be deployed as mobile infrastructure elements to offer all types of services. Examples of such services include safety in rural areas where, upon an emergency event, drones can be quickly deployed as information relays for distributing critical warning to vehicles. In this work, we analyze the communications performance on the link between cars and drones taking into account the altitude, the antenna orientation, and the relative distance. The presented results show that the communication between a drone and a car can reach up to three kilometers in a rural area, and achieves at least a fifty percent success ratio for the delivery rate at a 2.7 km range. Finally, to allow integrating the communications link behaviour in different network simulators, the experimental results were also modeled with a modified Gaussian function that offers a suitable representation for this kind of communication.This work was partially supported by the "Ministerio de Economia y Competividad, Programa Estatal de Investigacion, Desarollo e Innovacion Orientada a los Retos de la Sociedad, Proyectos I+D+I 2014", Spain, under grants TEC2014-52690-R and BES-2015-075988.Hadiwardoyo, SA.; Hernández-Orallo, E.; Tavares De Araujo Cesariny Calafate, CM.; Cano, J.; Manzoni, P. (2018). Experimental characterization of UAV-to-car communications. Computer Networks. 136:105-118. https://doi.org/10.1016/j.comnet.2018.03.002S10511813

3D Simulation Modeling of UAV-to-Car Communications

(c) 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.[EN] In this paper, we propose a realistic model for simulating communications between unmanned aerial vehicles (UAVs), or drones, and ground vehicles, which can support mobile infrastructure to broadcast alerts in emergency situations. Three-dimensional positioning features should be considered in these simulations that involve UAVs and ground vehicles since communications links are not based on a flat surface. In fact, irregular terrains in the form of hills and mountains can greatly affect the communications by acting as obstacles that block radio signals partially or totally. Hence, in this paper, we propose a simulation model that conforms to this kind of communication and that was developed in the scope of the OMNeT++ simulator. The simulation results achieved showed a great degree of similarities with those results obtained in a real testbed for different scenarios. In addition, various path loss models and elevation models were considered to improve the level of realism of the simulation model.This work was supported in part by the Japan Society for the Promotion of Science KAKENHI under Grant JP16H02817 and Grant JP18KK0279, in part by the International Internship Program of the National Institute of Informatics, Japan, and in part by the Ministerio de Economía y Competividad, Programa Estatal de Investigación, Desarollo e Innovación Orientada a los Retos de la Sociedad, Proyectos ICDCI 2014, Government of Spain, under Grant TEC2014-52690-R and Grant BES-2015-075988.Hadiwardoyo, SA.; Tavares De Araujo Cesariny Calafate, CM.; Cano, J.; Ji, Y.; Hernández-Orallo, E.; Manzoni, P. (2019). 3D Simulation Modeling of UAV-to-Car Communications. IEEE Access. 7:8808-8823. https://doi.org/10.1109/ACCESS.2018.2889604S88088823

Empirical Study and Modeling of Vehicular Communications at Intersections in the 5 GHz Band

[EN] Event warnings are critical in the context of ITS, being dependent on reliable and low-delay delivery ofmessages to nearby vehicles. One of the main challenges to address in this context is intersection management. Since buildings will severely hinder signals in the 5GHz band, it becomes necessary to transmit at the exact moment a vehicle is at the center of an intersection to maximize delivery chances. However, GPS inaccuracy, among other problems, complicates the achievement of this goal. In this paper we study this problem by first analyzing different intersection types, studying the vehicular communications performance in each type of intersection through real scenario experiments. Obtained results show that intersection-related communications depend on the distances to the intersection and line-of-sight (LOS) conditions. Also, depending on the physical characteristics of intersections, the presented blockages introduce different degrees of hampering to message delivery. Based on the modeling of the different intersection types, we then study the expected success ratio when notifying events at intersections. In general, we find that effective propagation of messages at intersections is possible, even in urban canyons and despite GPS errors, as long as rooftop antennas are used to compensate for poor communication conditions.This work was partially supported by the “Ministerio de Economía y Competividad, Programa Estatal de Investigación, Desarollo e Innovación Orientada a los Retos de la Sociedad, Proyectos I+D+I 2014,” Spain, under Grants TEC2014-52690-R and BES-2015-075988.Hadiwardoyo, SA.; Tomás Domínguez, AE.; Hernández-Orallo, E.; Tavares De Araujo Cesariny Calafate, CM.; Cano, J.; Manzoni, P. (2017). Empirical Study and Modeling of Vehicular Communications at Intersections in the 5 GHz Band. Mobile Information Systems. (2861827):1-15. https://doi.org/10.1155/2017/2861827S1152861827Xiong, Z., Sheng, H., Rong, W., & Cooper, D. E. (2012). Intelligent transportation systems for smart cities: a progress review. Science China Information Sciences, 55(12), 2908-2914. doi:10.1007/s11432-012-4725-1Papadimitratos, P., La Fortelle, A., Evenssen, K., Brignolo, R., & Cosenza, S. (2009). Vehicular communication systems: Enabling technologies, applications, and future outlook on intelligent transportation. IEEE Communications Magazine, 47(11), 84-95. doi:10.1109/mcom.2009.5307471Grant-Muller, S., & Usher, M. (2014). Intelligent Transport Systems: The propensity for environmental and economic benefits. Technological Forecasting and Social Change, 82, 149-166. doi:10.1016/j.techfore.2013.06.010Ma, X., Chen, X., & Refai, H. H. (2009). Performance and Reliability of DSRC Vehicular Safety Communication: A Formal Analysis. EURASIP Journal on Wireless Communications and Networking, 2009(1). doi:10.1155/2009/969164Martinez, F. J., Toh, C.-K., Cano, J.-C., Calafate, C. T., & Manzoni, P. (2010). A Street Broadcast Reduction Scheme (SBR) to Mitigate the Broadcast Storm Problem in VANETs. Wireless Personal Communications, 56(3), 559-572. doi:10.1007/s11277-010-9989-4Sanguesa, J. A., Fogue, M., Garrido, P., Martinez, F. J., Cano, J.-C., & Calafate, C. T. (2016). A Survey and Comparative Study of Broadcast Warning Message Dissemination Schemes for VANETs. Mobile Information Systems, 2016, 1-18. doi:10.1155/2016/8714142Sommer, C., Joerer, S., Segata, M., Tonguz, O. K., Cigno, R. L., & Dressler, F. (2015). How Shadowing Hurts Vehicular Communications and How Dynamic Beaconing Can Help. IEEE Transactions on Mobile Computing, 14(7), 1411-1421. doi:10.1109/tmc.2014.2362752Lin, J.-C., Lin, C.-S., Liang, C.-N., & Chen, B.-C. (2012). Wireless communication performance based on IEEE 802.11p R2V field trials. IEEE Communications Magazine, 50(5), 184-191. doi:10.1109/mcom.2012.6194401Gozalvez, J., Sepulcre, M., & Bauza, R. (2012). IEEE 802.11p vehicle to infrastructure communications in urban environments. IEEE Communications Magazine, 50(5), 176-183. doi:10.1109/mcom.2012.6194400Tornell, S. M., Patra, S., Calafate, C. T., Cano, J.-C., & Manzoni, P. (2015). GRCBox: Extending Smartphone Connectivity in Vehicular Networks. International Journal of Distributed Sensor Networks, 11(3), 478064. doi:10.1155/2015/478064Chou, L.-D., Yang, J.-Y., Hsieh, Y.-C., Chang, D.-C., & Tung, C.-F. (2011). Intersection-Based Routing Protocol for VANETs. Wireless Personal Communications, 60(1), 105-124. doi:10.1007/s11277-011-0257-zSaleet, H., Langar, R., Naik, K., Boutaba, R., Nayak, A., & Goel, N. (2011). Intersection-Based Geographical Routing Protocol for VANETs: A Proposal and Analysis. IEEE Transactions on Vehicular Technology, 60(9), 4560-4574. doi:10.1109/tvt.2011.2173510Guan, X., Huang, Y., Cai, Z., & Ohtsuki, T. (2015). Intersection-based forwarding protocol for vehicular ad hoc networks. Telecommunication Systems, 62(1), 67-76. doi:10.1007/s11235-015-9983-yKarney, C. F. F. (2011). Transverse Mercator with an accuracy of a few nanometers. Journal of Geodesy, 85(8), 475-485. doi:10.1007/s00190-011-0445-3Durgin, G., Rappaport, T. S., & Hao Xu. (1998). Measurements and models for radio path loss and penetration loss in and around homes and trees at 5.85 GHz. IEEE Transactions on Communications, 46(11), 1484-1496. doi:10.1109/26.729393Haklay, M., & Weber, P. (2008). OpenStreetMap: User-Generated Street Maps. IEEE Pervasive Computing, 7(4), 12-18. doi:10.1109/mprv.2008.8

Three Dimensional UAV Positioning for Dynamic UAV-to-Car Communications

[EN] In areas with limited infrastructure, Unmanned Aerial Vehicles (UAVs) can come in handy as relays for car-to-car communications. Since UAVs are able to fully explore a three-dimensional environment while flying, communications that involve them can be affected by the irregularity of the terrains, that in turn can cause path loss by acting as obstacles. Accounting for this phenomenon, we propose a UAV positioning technique that relies on optimization algorithms to improve the support for vehicular communications. Simulation results show that the best position of the UAV can be timely determined considering the dynamic movement of the cars. Our technique takes into account the current flight altitude, the position of the cars on the ground, and the existing flight restrictions.This work was partially supported by the Ministerio de Ciencia, Innovación y Universidades, Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad, Proyectos I+D+I 2018 , Spain, under Grant RTI2018-096384-B-I00, and grant BES-2015-075988, Ayudas para contratos predoctorales 2015.Hadiwardoyo, SA.; Tavares De Araujo Cesariny Calafate, CM.; Cano, J.; Krinkin, K.; Klionskiy, D.; Hernández-Orallo, E.; Manzoni, P. (2020). Three Dimensional UAV Positioning for Dynamic UAV-to-Car Communications. Sensors. 20(2):1-18. https://doi.org/10.3390/s20020356S11820

Reinforcing Traffic Safety by Using CAM to Verify Velocity Accuracy

none4siThe benefits of Cooperative Intelligent Transport Systems (C-ITS) span a range of areas, such as road safety and service reliability. Thus, traffic accidents can be avoided, and ultimately human lives can be saved. As C- ITS disseminate in-vehicle information, an error in the disseminated velocity accuracy may cause accidents, particularly in the automated and autonomous driving contexts. Hence, it is vital to detect these errors and warn vehicles about the inaccuracy of the speed reported by the vehicle in the C- ITS Cooperative Awareness Message (CAM). To illustrate the potential of our solution, we present one use case with platooning green light priority and another to save the life of a cyclist when it jumps into the lane of a vehicle without signaling or without enough space to do so. Our solution integrates a Roadside Unit (RSU) with a velocity detection device to enforce the accuracy of the disseminated velocity from a vehicle using C- ITS. We compare the velocity disseminated by a vehicle, via CAMs, with the velocity acquired from a standard deployed “speed detection device”. To show the feasibility of our proposal, we emulate a vehicle sending and receiving C- ITS messages in a virtualized environment. The RSU receives C- ITS messages to get the disseminated velocity of a vehicle and, if needed, warn that the disseminated velocity is inaccurate. Focusing on our experiments, it takes less than 500 μs to process the information and report the inaccuracy. Additionally, our work introduces a data calibration warning that could be needed by autonomous vehicles.noneErik De Britto e Silva; Seilendria A. Hadiwardoyo; Cristina Emilia Costa; Johann M. Marquez-BarjaDe Britto E Silva, Erik; Hadiwardoyo, Seilendria A.; Costa, Cristina Emilia; Marquez-Barja, Johann M