IoT, Intelligent Transport Systems and MaaS (Mobility as a Service)

IoT (Internet of Things) applications are crucial in Intelligent Transport Systems (ITS). MaaS (Mobility as a Service) is an advanced model of ITS in which public institutions, private operators and citizens are deeply connected since means of transport are virtualized in mobility resources and provided to users through the Internet. This contribution, after a short introduction, addresses legal concerns focusing on three aspects: (1) security of technological platforms and infrastructures, (2) protection of user\u2019s personal data, (3) communication among devices and in the IoT ecosystem

Multimodal route planners in maritime environment

Rapid development of information and communication technologies (ICT) enables complete distribution of traveler information to end-users through the whole travel. European intelligent transportation system (ITS) architecture defines traveler information as specific functional area, and it comprises static and dynamic information about transport network condition, traveler information services and support for services which perform collection, storage and management of traffic data for planning transport activities. The purpose of this research is to define the concept of development of multimodal route planners in maritime environment which are based on optimal usage of traveler and traffic data. End-users should receive complete traveler information for the entire duration of travel. Majority of present projects and studies is focused on road traveler information and services, but multimodal route planners can be extended at maritime environment, which is the basis of this research

A Data-driven Methodology Towards Mobility- and Traffic-related Big Spatiotemporal Data Frameworks

Human population is increasing at unprecedented rates, particularly in urban areas. This increase, along with the rise of a more economically empowered middle class, brings new and complex challenges to the mobility of people within urban areas. To tackle such challenges, transportation and mobility authorities and operators are trying to adopt innovative Big Data-driven Mobility- and Traffic-related solutions. Such solutions will help decision-making processes that aim to ease the load on an already overloaded transport infrastructure. The information collected from day-to-day mobility and traffic can help to mitigate some of such mobility challenges in urban areas. Road infrastructure and traffic management operators (RITMOs) face several limitations to effectively extract value from the exponentially growing volumes of mobility- and traffic-related Big Spatiotemporal Data (MobiTrafficBD) that are being acquired and gathered. Research about the topics of Big Data, Spatiotemporal Data and specially MobiTrafficBD is scattered, and existing literature does not offer a concrete, common methodological approach to setup, configure, deploy and use a complete Big Data-based framework to manage the lifecycle of mobility-related spatiotemporal data, mainly focused on geo-referenced time series (GRTS) and spatiotemporal events (ST Events), extract value from it and support decision-making processes of RITMOs. This doctoral thesis proposes a data-driven, prescriptive methodological approach towards the design, development and deployment of MobiTrafficBD Frameworks focused on GRTS and ST Events. Besides a thorough literature review on Spatiotemporal Data, Big Data and the merging of these two fields through MobiTraffiBD, the methodological approach comprises a set of general characteristics, technical requirements, logical components, data flows and technological infrastructure models, as well as guidelines and best practices that aim to guide researchers, practitioners and stakeholders, such as RITMOs, throughout the design, development and deployment phases of any MobiTrafficBD Framework. This work is intended to be a supporting methodological guide, based on widely used Reference Architectures and guidelines for Big Data, but enriched with inherent characteristics and concerns brought about by Big Spatiotemporal Data, such as in the case of GRTS and ST Events. The proposed methodology was evaluated and demonstrated in various real-world use cases that deployed MobiTrafficBD-based Data Management, Processing, Analytics and Visualisation methods, tools and technologies, under the umbrella of several research projects funded by the European Commission and the Portuguese Government.A população humana cresce a um ritmo sem precedentes, particularmente nas áreas urbanas. Este aumento, aliado ao robustecimento de uma classe média com maior poder económico, introduzem novos e complexos desafios na mobilidade de pessoas em áreas urbanas. Para abordar estes desafios, autoridades e operadores de transportes e mobilidade estão a adotar soluções inovadoras no domínio dos sistemas de Dados em Larga Escala nos domínios da Mobilidade e Tráfego. Estas soluções irão apoiar os processos de decisão com o intuito de libertar uma infraestrutura de estradas e transportes já sobrecarregada. A informação colecionada da mobilidade diária e da utilização da infraestrutura de estradas pode ajudar na mitigação de alguns dos desafios da mobilidade urbana. Os operadores de gestão de trânsito e de infraestruturas de estradas (em inglês, road infrastructure and traffic management operators — RITMOs) estão limitados no que toca a extrair valor de um sempre crescente volume de Dados Espaciotemporais em Larga Escala no domínio da Mobilidade e Tráfego (em inglês, Mobility- and Traffic-related Big Spatiotemporal Data —MobiTrafficBD) que estão a ser colecionados e recolhidos. Os trabalhos de investigação sobre os tópicos de Big Data, Dados Espaciotemporais e, especialmente, de MobiTrafficBD, estão dispersos, e a literatura existente não oferece uma metodologia comum e concreta para preparar, configurar, implementar e usar uma plataforma (framework) baseada em tecnologias Big Data para gerir o ciclo de vida de dados espaciotemporais em larga escala, com ênfase nas série temporais georreferenciadas (em inglês, geo-referenced time series — GRTS) e eventos espacio- temporais (em inglês, spatiotemporal events — ST Events), extrair valor destes dados e apoiar os RITMOs nos seus processos de decisão. Esta dissertação doutoral propõe uma metodologia prescritiva orientada a dados, para o design, desenvolvimento e implementação de plataformas de MobiTrafficBD, focadas em GRTS e ST Events. Além de uma revisão de literatura completa nas áreas de Dados Espaciotemporais, Big Data e na junção destas áreas através do conceito de MobiTrafficBD, a metodologia proposta contem um conjunto de características gerais, requisitos técnicos, componentes lógicos, fluxos de dados e modelos de infraestrutura tecnológica, bem como diretrizes e boas práticas para investigadores, profissionais e outras partes interessadas, como RITMOs, com o objetivo de guiá-los pelas fases de design, desenvolvimento e implementação de qualquer pla- taforma MobiTrafficBD. Este trabalho deve ser visto como um guia metodológico de suporte, baseado em Arqui- teturas de Referência e diretrizes amplamente utilizadas, mas enriquecido com as característi- cas e assuntos implícitos relacionados com Dados Espaciotemporais em Larga Escala, como no caso de GRTS e ST Events. A metodologia proposta foi avaliada e demonstrada em vários cenários reais no âmbito de projetos de investigação financiados pela Comissão Europeia e pelo Governo português, nos quais foram implementados métodos, ferramentas e tecnologias nas áreas de Gestão de Dados, Processamento de Dados e Ciência e Visualização de Dados em plataformas MobiTrafficB

Geomatics for Mobility Management. A comprehensive database model for Mobility Management

In urban and metropolitan context, Traffic Operations Centres (TOCs) use technologies as Geographic Information Systems (GIS) and Intelligent Transport Systems (ITS) to tackling urban mobility issue. Usually in TOCs, various isolated systems are maintained in parallel (stored in different databases), and data comes from different sources: a challenge in transport management is to transfer disparate data into a unified data management system that preserves access to legacy data, allowing multi-thematic analysis. This need of integration between systems is important for a wise policy decisions. This study aims to design a comprehensive and general spatial data model that could allow the integration and visualization of traffic components and measures. The activity is focused on the case study of 5T Agency in Turin, a TOC that manages traffic regulation, public transit fleets and information to users, in the metropolitan area of Turin and Piedmont Region. In particular, the agency has set up during years a wide system of ITS technologies that acquires continuously measures and traffic information, which are used to deploy information services to citizens and public administrations. However, the spatial nature of these data is not fully considered in the daily operational activity, with the result of difficulties in information integration. Indeed the agency lacks of a complete GIS that includes all the management information in an organized spatial and “horizontal” vision. The main research question concerns the integration of different kind of data in a unique GIS spatial data model. Spatial data interoperability is critical and particularly challenging because geographic data definition in legacy database can vary widely: different data format and standards, data inconsistencies, different spatial and temporal granularities, different methods and enforcing rules that relates measures, events and physical infrastructures. The idea is not to replace the existing implemented and efficient system, but to built-up on these systems a GIS that overpass the different software and DBMS platforms and that can demonstrate how a spatial and horizontal vision in tackling urban mobility issues may be useful for policy and strategies decisions. The modelling activity take reference from a transport standards review and results in database general schema, which can be reused by other TOCs in their activities, helping the integration and coordination between different TOCs. The final output of the research is an ArcGIS geodatabase, tailored on 5T data requirements, which enable the customised representation of private traffic elements and measures. Specific custom scripts have been developed to allow the extraction and the temporal aggregation of traffic measures and events. The solution proposed allows the reuse of data and measures for custom purposes, without the need to deeply know the entire ITS environment system. In addition, The proposed ArcGIS geodatabase solution is optimised for limited power-computing environment. A case study has been deepened in order to evaluate the suitability of the database: a confrontation between damages, detected by Emergency Mapping Services (EMS), and Traffic Message Channel traffic events, has been conducted, evaluating the utility of 5T historical information of traffic events of the Piedmont floods of November 2016 for EMS services

Multimodal route planners in maritime environment

Rapid development of information and communication technologies (ICT) enables complete distribution of traveler information to end-users through the whole travel. European intelligent transportation system (ITS) architecture defines traveler information as specific functional area, and it comprises static and dynamic information about transport network condition, traveler information services and support for services which perform collection, storage and management of traffic data for planning transport activities. The purpose of this research is to define the concept of development of multimodal route planners in maritime environment which are based on optimal usage of traveler and traffic data. End-users should receive complete traveler information for the entire duration of travel. Majority of present projects and studies is focused on road traveler information and services, but multimodal route planners can be extended at maritime environment, which is the basis of this research

Data Communication in Hungary - The Telecommunication Infrastructure and Relevant Administrative Procedures

A description is provided of the data communication and telecommunication infrastructure in Hungary together with all the relevant administrative procedures. First, on a historical basis, the general status of telecommunication, information processing, and data communication is given. This is followed by a description of all the data communication services of the telegraph, telex, telephone, and dedicated data networks and the corresponding administrative procedures. Special emphasis is given to the public digital data network NEDIX, which is the first such service in Eastern Europe. Last but not least the legal basis for transborder data flows is outlined and a short overview of the present transborder data flow applications is described