Sensing raffic density combining V2V and V2I wireless communications

[EN] Wireless technologies are making the development of new applications and services in vehicular environments possible since they enable mobile communication between vehicles (V2V), as well as communication between vehicles and infrastructure nodes (V2I). Usually, V2V communications are dedicated to the transmission of small messages mainly focused on improving traffic safety. Instead, V2I communications allow users to access the Internet and benefit from higher level applications. The combination of both V2V and V2I, known as V2X communications, can increase the benefits even further, thereby making intelligent transportation systems (ITS) a reality. In this paper, we introduce V2X-d, a novel architecture specially designed to estimate traffic density on the road. In particular, V2X-d exploits the combination of V2V and V2I communications. Our approach is based on the information gathered by sensors (i.e., vehicles and road side units (RSUs)) and the characteristics of the roadmap topology to accurately make an estimation of the instant vehicle density. The combination of both mechanisms improves the accuracy and coverage area of the data gathered, while increasing the robustness and fault tolerance of the overall approach, e.g., using the information offered by V2V communications to provide additional density information in areas where RSUs are scarce or malfunctioning. By using our collaborative sensing scheme, future ITS solutions will be able to establish adequate dissemination protocols or to apply more efficient traffic congestion reduction policies, since they will be aware of the instantaneous density of vehicles.This work was supported by the Ministerio de Economia y Competitividad, Programa Estatal de Investigacion, Desarrollo e Innovacion Orientada a los Retos de la Sociedad, Proyectos I+D+I 2014, Spain, under Grant TEC2014-52690-R, and by the Government of Aragon and the European Social Fund (T91 Research Group).Sanguesa, JA.; Barrachina, J.; Fogue, M.; Garrido, P.; Martínez, FJ.; Cano Escribá, JC.; Tavares De Araujo Cesariny Calafate, CM.... (2015). Sensing raffic density combining V2V and V2I wireless communications. Sensors. 2015(2015):31794-31810. https://doi.org/10.3390/s151229889S31794318102015201

Fog Connectivity Clustering and MDP Modeling for Software-defined Vehicular Networks

Intelligent and networked vehicles cooperate to create a mobile Cloud through vehicular Fog computing (VFC). Such clouds rely heavily on the underlying vehicular networks, so estimating communication resilience allows to address the problems caused by intermittent vehicle connectivity for data transfers. Individually estimating the communication stability of vehicles, nevertheless, undergoes incorrect predictions due to their particular mobility patterns. Therefore, we provide a region-oriented fog management model based on the connectivity through vehicular heterogeneous network environment via V2X and C-V2X. A fog management strategy dynamically monitors nearby vehicles to determine distinct regions in urban centres. The model enables a software-defined vehicular network (\Gls{SDVN}) controller to coordinate data flows. The vehicular connectivity described by our model assesses the potential for vehicle communication and conducts dynamic vehicle clustering. From the stochasticity of the environment, our model is based on Markov Decision Process (MDP), tracking the status of vehicle clusters and their potential for provisioning services. The model for vehicular clustering is supported by 5G and DSRC heterogeneous networks. Simulated analyses have shown the capability of our proposed model to estimate cluster reliability in real-time urban scenarios and support effective vehicular fog management

From theory to experimental evaluation: resource management in software-defined vehicular networks

Managing resources in dynamic vehicular environments is a tough task, which is becoming more challenging with the increased number of access technologies today available in connected cars (e.g., IEEE 802.11, LIE), in the variety of applications provided on the road (e.g., safety, traffic efficiency, and infotainment), in the amount of driving awareness/coordination required (e.g., local, context, and cooperative awareness), and in the level of automation toward zero-accident driving (e.g., platooning and autonomous driving). The open programmability and logically centralized control features of the software-defined networking (SDN) paradigm offer an attractive means to manage communication and networking resources in the vehicular environment and promise improved performance. In this paper, we enumerate the potentials of software-defined vehicular networks, analyze the need to rethink the traditional SDN approach from theoretical and practical standpoints when applied in this application context, and present an emulation approach based on the proposed node car architecture in Mininet-WiFi to showcase the applicability and some expected benefits of SDN in a selected use case scenario530693076FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP14/18482-

A traffic-aware electric vehicle charging management system for smart cities

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/The expected increase in the number of electric vehicles (EVs) in the coming years will contribute to reducing CO2 pollution in our cities. Currently, EVs' users may suffer from distress due to long charging service times and overloaded charging stations (CSs). Critical traffic conditions (e.g., traffic jams) affect EVs' trip time (TT) towards CSs and thus influence the total trip duration. With this concern, Intelligent transport systems (ITS) and more specifically connected vehicle technologies, can leverage an efficient real-time EV charging service by jointly considering CSs status and traffic conditions in the city. In this work, we propose a scheme to manage EVs' charging planning, focusing on the selection of a CS for the energy-requiring EV. The proposed scheme considers anticipated charging slots reservations performed through a vehicular ad hoc network (VANET), which has been regarded as a cost-efficient communication framework. In specific, we consider two aspects: 1) the EV's total trip time towards its destination considering an intermediate charging at each candidate CS, and 2) the communication delay of the VANET routing protocol. First, in order to estimate the EV's total trip time, our CS selection scheme takes into account the average road speed, traffic lights, and route distance, along the path of the EV. The optimal CS that produces the minimum total charging service time (including the TT) is suggested to that energy-requiring EV. Then, we introduce two communication modes based on geographical routing protocols for VANETs to attain an anticipated charging slot reservation. Simulation results show that with our charging scheme EVs' charging service time is reduced and more EVs are successfully charged.Peer ReviewedPostprint (author's final draft

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

Cooperative Perception for Social Driving in Connected Vehicle Traffic

The development of autonomous vehicle technology has moved to the center of automotive research in recent decades. In the foreseeable future, road vehicles at all levels of automation and connectivity will be required to operate safely in a hybrid traffic where human operated vehicles (HOVs) and fully and semi-autonomous vehicles (AVs) coexist. Having an accurate and reliable perception of the road is an important requirement for achieving this objective. This dissertation addresses some of the associated challenges via developing a human-like social driver model and devising a decentralized cooperative perception framework. A human-like driver model can aid the development of AVs by building an understanding of interactions among human drivers and AVs in a hybrid traffic, therefore facilitating an efficient and safe integration. The presented social driver model categorizes and defines the driver\u27s psychological decision factors in mathematical representations (target force, object force, and lane force). A model predictive control (MPC) is then employed for the motion planning by evaluating the prevailing social forces and considering the kinematics of the controlled vehicle as well as other operating constraints to ensure a safe maneuver in a way that mimics the predictive nature of the human driver\u27s decision making process. A hierarchical model predictive control structure is also proposed, where an additional upper level controller aggregates the social forces over a longer prediction horizon upon the availability of an extended perception of the upcoming traffic via vehicular networking. Based on the prediction of the upper level controller, a sequence of reference lanes is passed to a lower level controller to track while avoiding local obstacles. This hierarchical scheme helps reduce unnecessary lane changes resulting in smoother maneuvers. The dynamic vehicular communication environment requires a robust framework that must consistently evaluate and exploit the set of communicated information for the purpose of improving the perception of a participating vehicle beyond the limitations. This dissertation presents a decentralized cooperative perception framework that considers uncertainties in traffic measurements and allows scalability (for various settings of traffic density, participation rate, etc.). The framework utilizes a Bhattacharyya distance filter (BDF) for data association and a fast covariance intersection fusion scheme (FCI) for the data fusion processes. The conservatism of the covariance intersection fusion scheme is investigated in comparison to the traditional Kalman filter (KF), and two different fusion architectures: sensor-to-sensor and sensor-to-system track fusion are evaluated. The performance of the overall proposed framework is demonstrated via Monte Carlo simulations with a set of empirical communications models and traffic microsimulations where each connected vehicle asynchronously broadcasts its local perception consisting of estimates of the motion states of self and neighboring vehicles along with the corresponding uncertainty measures of the estimates. The evaluated framework includes a vehicle-to-vehicle (V2V) communication model that considers intermittent communications as well as a model that takes into account dynamic changes in an individual vehicle’s sensors’ FoV in accordance with the prevailing traffic conditions. The results show the presence of optimality in participation rate, where increasing participation rate beyond a certain level adversely affects the delay in packet delivery and the computational complexity in data association and fusion processes increase without a significant improvement in the achieved accuracy via the cooperative perception. In a highly dense traffic environment, the vehicular network can often be congested leading to limited bandwidth availability at high participation rates of the connected vehicles in the cooperative perception scheme. To alleviate the bandwidth utilization issues, an information-value discriminating networking scheme is proposed, where each sender broadcasts selectively chosen perception data based on the novelty-value of information. The potential benefits of these approaches include, but are not limited to, the reduction of bandwidth bottle-necking and the minimization of the computational cost of data association and fusion post processing of the shared perception data at receiving nodes. It is argued that the proposed information-value discriminating communication scheme can alleviate these adverse effects without sacrificing the fidelity of the perception

Scalable Map Information Dissemination for Connected and Automated Vehicle Systems

Situational awareness in connected and automated vehicle (CAV) systems becomes particularly challenging in the presence of non-line of sight objects and/or objects beyond the sensing range of local onboard sensors. Despite the fact that fully autonomous driving requires the use of multiple redundant sensor systems, primarily including camera, radar, and LiDAR, the non-line of sight object detection problem still persists due to the inherent limitations of those sensing techniques. To tackle this challenge, the inter-vehicle communication system is envisioned that allows vehicles to exchange self-status updates aiming to extend their effective field of view and thus compensate for the limitations of the vehicle tracking subsystem that relies substantially on onboard sensing devices. Tracking capability in such systems can be further improved through the cooperative sharing of locally created map data instead of transmitting only self-update messages containing core basic safety message (BSM) data. In the cooperative sharing of safety messages, it is imperative to have a scalable communication protocol to ensure optimal use of the communication channel. This dissertation contributes to the analysis of the scalability issue in vehicle-to-everything (V2X) communication and then addresses the range issue of situational awareness in CAV systems by proposing a content-adaptive V2X communication architecture. To that end, we first analyze the BSM scheduling protocol standardized in the SAE J2945/1 and present large-scale scalability results obtained from a high-fidelity simulation platform to demonstrate the protocol\u27s efficacy to address the scalability issues in V2X communication. By employing a distributed opportunistic approach, the SAE J2945/1 congestion control algorithm keeps the overall offered channel load within an optimal operating range, while meeting the minimum tracking requirements set forth by upper-layer applications. This scheduling protocol allows event-triggered and vehicle-dynamics driven message transmits that further the situational awareness in a cooperative V2X context. Presented validation results of the congestion control algorithm include position tracking errors as the performance measure, with the age of communicated information as the evaluation measure. In addition, we examine the optimality of the default settings of the congestion control parameters. Comprehensive analysis and trade-off study of the control parameters reveal some areas of improvement to further the algorithm\u27s efficacy. Motivated by the effectiveness of channel congestion control mechanism, we further investigate message content and length adaptations, together with transmit rate control. Reasonably, the content of the exchanged information has a significant impact on the map accuracy in cooperative driving systems. We investigate different content control schemes for a communication architecture aimed at map sharing and evaluate their performance in terms of position tracking error. This dissertation determines that message content should be concentrated to mapped objects that are located farther away from the sender to the edge of the local sensor range. This dissertation also finds that optimized combination of message length and transmit rate ensures the optimal channel utilization for cooperative vehicular communication, which in turn improves the situational awareness of the whole system

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

A probability-based multimetric routing protocol for vehicular ad hoc networks in urban scenarios

Vehicular Ad hoc Networks have received considerable attention in recent years and are considered as one of the most promising ad-hoc network technologies for intelligent transport systems. Vehicular Ad hoc Networks have special requirements and unique characteristics (e.g., special mobility patterns, short life links, rapid topology changes) which make the design of suitable routing protocols, a challenge. Consequently, an efficient routing protocol that fits with VANETs’ requirements and characteristics is a crucial task to obtain a good performance in terms of average percentage of packet losses and average end-to-end packet delay. To attain this goal, we propose a novel probabilistic multimetric routing protocol (ProMRP) that is specially designed for VANETs. ProMRP estimates the probability for each neighbor of the node currently carrying the packet, to successfully deliver a packet to destination. This probability is computed based on four designed metrics: distance to destination, node’s position, available bandwidth and nodes’ density. Furthermore, an improved version of ProMRP called EProMRP is also proposed. EProMRP includes an algorithm that accurately estimates the current position of nodes in the moment of sending the packet instead of using the last updated position obtained from the previous beacon message. Simulations are carried out in a realistic urban scenario using OMNeT++/VEINS/SUMO, including real maps from the OpenStreetMaps platform. Simulation results show a better performance of ProMRP and EProMRP compared to recent similar proposals found in the literature in terms of packet losses and end-to-end packet delay, for different vehicles’ densities.Peer ReviewedPostprint (published version