Sustainable Mobility and Transport

This Special Issue is dedicated to sustainable mobility and transport, with a special focus on technological advancements. Global transport systems are significant sources of air, land, and water emissions. A key motivator for this Special Issue was the diversity and complexity of mitigating transport emissions and industry adaptions towards increasingly stricter regulation. Originally, the Special Issue called for papers devoted to all forms of mobility and transports. The papers published in this Special Issue cover a wide range of topics, aiming to increase understanding of the impacts and effects of mobility and transport in working towards sustainability, where most studies place technological innovations at the heart of the matter. The goal of the Special Issue is to present research that focuses, on the one hand, on the challenges and obstacles on a system-level decision making of clean mobility, and on the other, on indirect effects caused by these changes

Novel approach for integrated biomass supply chain synthesis and optimisation

Despite looming energy crises, fossil resources are still widely used for energy and chemical production. Growing awareness of the environmental impact from fossil fuels has made sustainability one of the main focuses in research and development. Towards that end, biomass is identified as a promising renewable source of carbon that can potentially replace fossil resources in energy and chemical productions. Although many researches on converting biomass to value-added product have been done, biomass is still considered underutilised in the industry. This is mainly due to challenges in the logistic and processing network of biomass. An integrated biomass supply chain synthesis and optimisation are therefore important. Thus, the ultimate goal of this thesis is to develop a novel approach for an integrated biomass supply chain. Firstly, a multiple biomass corridor (MBC) concept is presented to integrate various biomass and processing technologies into existing biomass supply chain system in urban and developed regions. Based on this approach, a framework is developed for the synthesis of a more diversified and economical biomass supply chain system. The work is then extended to consider the centralisation and decentralisation of supply chain structure. In this manner, P-graph-aided decomposition approach (PADA) is proposed, whereby it divides the complex supply chain problem into two smaller sub-problems – the processing network is solved via mixed-integer linear programming (MILP) model, whereas the binaries-intensive logistic network configuration is determined through P-graph framework. As existing works often focus on supply chain synthesis in urban regions with well-developed infrastructure, resources integrated network (RIN) – a novel approach for the synthesis of integrated biomass supply chain in rural and remote regions is introduced to enhance rural economies. This approach incorporates multiple resources (i.e. bioresources, food commodities, rural communities’ daily needs) into the value chain and utilises inland water system as the mode of transport, making the system more economically feasible. It extends the MBC approach for technology selection and adopts vehicle routing problem (VRP) for inland water supply and delivery network. To evaluate the performance of the proposed integrated biomass supply chain system, a FANP-based (fuzzy analytical network process) sustainability assessment tool is established. A framework is proposed to derive sustainability index (SI) from pairwise comparison done by supply chain stakeholders to assess the sustainability of a system. Fuzzy limits are introduced to reduce uncertainties in human judgment while conducting the pairwise comparison. To design a sustainable integrated biomass supply chain, a FANP-aided, a novel multiple objectives optimisation framework is proposed. This approach transforms multiple objective functions into single objective function by prioritising each of the objective through the FANP framework. The multiple objectives are then normalised via max-min aggregation to ensure the trade-off between objectives is performed on the same scale. At the end of this thesis, viable future works of the whole programme is presented for consideration

The role of Artificial Intelligence and distributed computing in IoT applications

[EN]The exchange of ideas between scientists and technicians, from both academic and business areas, is essential in order to ease the development of systems which can meet the demands of today’s society. Technology transfer in this field is still a challenge and, for that reason, this type of contributions are notably considered in this compilation. This book brings in discussions and publications concerning the development of innovative techniques of IoT complex problems. The technical program focuses both on high quality and diversity, with contributions in well-established and evolving areas of research. Specifically, 10 chapters were submitted to this book. The editors particularly encouraged and welcomed contributions on AI and distributed computing in IoT applications.Financed by regional government of Castilla y León and FEDER funds

The role of Artificial Intelligence and Distributed computing in IoT applications

[ES] La serie «El rol de la inteligencia artificial y la computación distribuida en las aplicaciones IoT» contiene publicaciones sobre la teoría y aplicaciones de la computación distribuida y la inteligencia artificial en el Internet de las cosas. Prácticamente todas las disciplinas como la ingeniería, las ciencias naturales, la informática y las ciencias de la información, las TIC, la economía, los negocios, el comercio electrónico, el medio ambiente, la salud y las ciencias de la vida están cubiertas. La lista de temas abarca todas las áreas de los sistemas inteligentes modernos y la informática como: inteligencia computacional, soft computing incluyendo redes neuronales, inteligencia social, inteligencia ambiental, sistemas auto-organizados y adaptativos, computación centrada en el ser humano y centrada en el ser humano, sistemas de recomendación, control inteligente, robótica y mecatrónica, incluida la colaboración entre el ser humano y la máquina, paradigmas basados en el conocimiento, paradigmas de aprendizaje, ética de la máquina, análisis inteligente de datos, gestión del conocimiento, agentes inteligentes, toma de decisiones inteligentes y apoyo, seguridad de la red inteligente, gestión de la confianza, entretenimiento interactivo, inteligencia de la Web y multimedia. Las publicaciones en el marco de «El rol de la inteligencia artificial y la computación distribuida en las aplicaciones IoT» son principalmente las actas de seminarios, simposios y conferencias. Abarcan importantes novedades recientes en la materia, tanto de naturaleza fundacional como aplicable. Un importante rasgo característico de la serie es el corto tiempo de publicación. Esto permite una rápida y amplia difusión de los resultados de las investigaciones[EN] The series «The Role of Artificial Intelligence and Distributed Computing in IoT Applications» contains publications on the theory and applications of distributed computing and artificial intelligence in the Internet of Things. Virtually all disciplines such as engineering, natural sciences, computer and information sciences, ICT, economics, business, e-commerce, environment, health and life sciences are covered. The list of topics covers all areas of modern intelligent systems and computer science: computational intelligence, soft computing including neural networks, social intelligence, ambient intelligence, self-organising and adaptive systems, human-centred and people-centred computing, recommendation systems, intelligent control, robotics and mechatronics including human-machine collaboration, knowledge-based paradigms, learning paradigms, machine ethics, intelligent data analysis, knowledge management, intelligent agents, intelligent decision making and support, intelligent network security, trust management, interactive entertainment, web intelligence, and multimedia. The publications in the framework of «The Role of Artificial Intelligence and Distributed Computing in IoT Applications» are mainly the proceedings of seminars, symposia and conferences. They cover important recent developments in the field, whether of a foundational or applicable character. An important feature of the series is the short publication time. This allows for the rapid and wide dissemination of research results

Sustaining Glasgow's Urban Networks: the Link Communities of Complex Urban Systems

As cities grow in population size and became more crowded (UN DESA, 2018), the main future challenges around the world will remain to be accommodating the growing urban population while drastically reducing environmental pressure. Contemporary urban agglomerations (large or small) constantly impose burden on the natural environment by conveying ecosystem services to close and distant places, through coupled human nature [infrastructure] systems (CHANS). Tobler’s first law in geography (1970) that states that “everything is related to everything else, but near things are more related than distant things” is now challenged by globalization. When this law was first established, the hypothesis referred to geological processes (Campbell and Shin, 2012, p.194) that were predominantly observed in pre-globalized economy, where freight was costly and mainly localized (Zhang et al., 2018). With the recent advances and modernisation made in transport technologies, most of them in the sea and air transportation (Zhang et al., 2018) and the growth of cities in population, natural resources and bi-products now travel great distances to infiltrate cities (Neuman, 2006) and satisfy human demands. Technical modernisation and the global hyperconnectivity of human interactions and trading, in the last thirty years alone resulted with staggering 94 per cent growth of resource extraction and consumption (Giljum et al., 2015). Local geographies (Kennedy, Cuddihy and Engel-Yan, 2007) will remain affected by global urbanisation (Giljum et al., 2015), and as a corollary, the operational inefficiencies of their local infrastructure networks, will contribute even more to the issues of environmental unsustainability on a global scale. Another challenge for future city-regions is the equity of public infrastructure services and policy creation that promote the same (Neuman and Hull, 2009). Public infrastructure services refer to services provisioned by networked infrastructure, which are subject to both public obligation and market rules. Therefore, their accessibility to all citizens needs to be safeguarded. The disparity of growth between networked infrastructure and socio-economic dynamics affects the sustainable assimilation and equal access to infrastructure in various districts in cities, rendering it as a privilege. Yet, the empirical evidence of whether the place of residence acts as a disadvantage to public service access and use, remains rather scarce (Clifton et al., 2016). The European Union recognized (EU, 2011) the issue of equality in accessibility (i.e. equity) critical for territorial cohesion and sustainable development across districts, municipalities and regions with diverse economic performance. Territorial cohesion, formally incorporated into the Treaty of Lisbon, now steers the policy frameworks of territorial development within the Union. Subsequently, the European Union developed a policy paradigm guided by equal access (Clifton et al., 2016) to public infrastructure services, considering their accessibility as instrumental aspect in achieving territorial cohesion across and within its member states. A corollary of increasing the equity to public infrastructure services among growing global population is the potential increase in environmental pressure they can impose, especially if this pressure is not decentralised and surges at unsustainable rate (Neuman, 2006). This danger varies across countries and continents, and is directly linked to the increase of urban population due to; [1] improved quality of life and increased life expectancy and/or [2] urban in-migration of rural population and/or [3] global political or economic immigration. These three rising urban trends demand new approaches to reimagine planning and design practices that foster infrastructure equity, whilst delivering environmental justice. Therefore, this research explores in depth the nature of growth of networked infrastructure (Graham and Marvin, 2001) as a complex system and its disparity from the socio-economic growth (or decline) of Glasgow and Clyde Valley city-region. The results of this research gain new understanding in the potential of using emerging tools from network science for developing optimization strategy that supports more cecentralized, efficient, fair and (as an outcome) sustainable enlargement of urban infrastructure, to accommodate new and empower current residents of the city. Applying the novel link clustering community detection algorithm (Ahn et al., 2010) in this thesis I have presented the potential for better understanding the complexity behind the urban system of networked infrastructure, through discovering their overlapping communities. As I will show in the literature review (Chapter 2), the long standing tradition of centralised planning practice relying on zoning and infiltrating infrastructure, left us with urban settlements which are failing to respond to the environmental pressure and the socio-economic inequalities. Building on the myriad of knowledge from planners, geographers, sociologists and computer scientists, I developed a new element (i.e. link communities) within the theory of urban studies that defines cities as complex systems. After, I applied a method borrowed from the study of complex networks to unpack their basic elements. Knowing the link (i.e. functional, or overlapping) communities of metropolitan Glasgow enabled me to evaluate the current level of communities interconnectedness and reveal the gaps as well as the potentials for improving the studied system’s performance. The complex urban system in metropolitan Glasgow was represented by its networked infrastructure, which essentially was a system of distinct sub-systems, one of them mapped by a physical and the other one by a social graph. The conceptual framework for this methodological approach was formalised from the extensively reviewed literature and methods utilising network science tools to detect community structure in complex networks. The literature review led to constructing a hypothesis claiming that the efficiency of the physical network’s topology is achieved through optimizing the number of nodes with high betweenness centrality, while the efficiency of the logical network’s topology is achieved by optimizing the number of links with high edge betweenness. The conclusion from the literature review presented through the discourse on to the primal problem in 7.4.1, led to modelling the two network topologies as separate graphs. The bipartite graph of their primal syntax was mirrored to be symmetrical and converted to dual. From the dual syntax I measured the complete accessibility (i.e. betweenness centrality) of the entire area and not only of the streets. Betweenness centrality of a node measures the number of shortest paths that pass through the node connecting pairs of nodes. The betweenness centrality is same as the integration of streets in space syntax, where the streets are analysed in their dual syntax representation. Street integration is the number of intersections the street shares with other streets and a high value means high accessibility. Edges with high betweenness are shared between strong communities. Based on the theoretical underpinnings of the network’s modularity and community structure analysed herein, it can be concluded that a complex network that is both robust and efficient (and in urban planning terminology ‘sustainable’) is consisted of numerous strong communities connected with each other by optimal number of links with high edge betweenness. To get this insight, the study detected the edge cut-set and vertex cut-set of the complex network. The outcome was a statistical model developed in the open source software R (Ihaka and Gentleman, 1996). The model empirical detects the network’s overlapping communities, determining the current sustainability of its physical and logical topologies. Initially, an assumption was that the number of communities within the infrastructure (physical) network layer were different from the one in the logical. They were detected using the Louvain method that performs graph partitioning on the hierarchical streets structure. Further, the number of communities in the relational network layer (i.e. accessibility to locations) was detected based on the OD accessibility matrix established from the functional dependency between the household locations and predefined points of interest. The communities from the graph of the ‘relational layer' were discovered with the single-link hierarchical clustering algorithm. The number of communities observed in the physical and the logical topologies of the eight shires significantly deviated

IEEE Access Special Section Editorial: Big Data Technology and Applications in Intelligent Transportation

During the last few years, information technology and transportation industries, along with automotive manufacturers and academia, are focusing on leveraging intelligent transportation systems (ITS) to improve services related to driver experience, connected cars, Internet data plans for vehicles, traffic infrastructure, urban transportation systems, traffic collaborative management, road traffic accidents analysis, road traffic flow prediction, public transportation service plan, personal travel route plans, and the development of an effective ecosystem for vehicles, drivers, traffic controllers, city planners, and transportation applications. Moreover, the emerging technologies of the Internet of Things (IoT) and cloud computing have provided unprecedented opportunities for the development and realization of innovative intelligent transportation systems where sensors and mobile devices can gather information and cloud computing, allowing knowledge discovery, information sharing, and supported decision making. However, the development of such data-driven ITS requires the integration, processing, and analysis of plentiful information obtained from millions of vehicles, traffic infrastructures, smartphones, and other collaborative systems like weather stations and road safety and early warning systems. The huge amount of data generated by ITS devices is only of value if utilized in data analytics for decision-making such as accident prevention and detection, controlling road risks, reducing traffic carbon emissions, and other applications which bring big data analytics into the picture

Development of transportation and supply chain problems with the combination of agent-based simulation and network optimization

Demand drives a different range of supply chain and logistics location decisions, and agent-based modeling (ABM) introduces innovative solutions to address supply chain and logistics problems. This dissertation focuses on an agent-based and network optimization approach to resolve those problems and features three research projects that cover prevalent supply chain management and logistics problems. The first case study evaluates demographic densities in Norway, Finland, and Sweden, and covers how distribution center (DC) locations can be established using a minimizing trip distance approach. Furthermore, traveling time maps are developed for each scenario. In addition, the Nordic area consisting of those three countries is analyzed and five DC location optimization results are presented. The second case study introduces transportation cost modelling in the process of collecting tree logs from several districts and transporting them to the nearest collection point. This research project presents agent-based modelling (ABM) that incorporates comprehensively the key elements of the pick-up and delivery supply chain model and designs the components as autonomous agents communicating with each other. The modelling merges various components such as GIS routing, potential facility locations, random tree log pickup locations, fleet sizing, trip distance, and truck and train transportation. The entire pick-up and delivery operation are modeled by ABM and modeling outcomes are provided by time series charts such as the number of trucks in use, facilities inventory and travel distance. In addition, various scenarios of simulation based on potential facility locations and truck numbers are evaluated and the optimal facility location and fleet size are identified. In the third case study, an agent-based modeling strategy is used to address the problem of vehicle scheduling and fleet optimization. The solution method is employed to data from a real-world organization, and a set of key performance indicators are created to assess the resolution's effectiveness. The ABM method, contrary to other modeling approaches, is a fully customized method that can incorporate extensively various processes and elements. ABM applying the autonomous agent concept can integrate various components that exist in the complex supply chain and create a similar system to assess the supply chain efficiency.Tuotteiden kysyntä ohjaa erilaisia toimitusketju- ja logistiikkasijaintipäätöksiä, ja agenttipohjainen mallinnusmenetelmä (ABM) tuo innovatiivisia ratkaisuja toimitusketjun ja logistiikan ongelmien ratkaisemiseen. Tämä väitöskirja keskittyy agenttipohjaiseen mallinnusmenetelmään ja verkon optimointiin tällaisten ongelmien ratkaisemiseksi, ja sisältää kolme tapaustutkimusta, jotka voidaan luokitella kuuluvan yleisiin toimitusketjun hallinta- ja logistiikkaongelmiin. Ensimmäinen tapaustutkimus esittelee kuinka käyttämällä väestötiheyksiä Norjassa, Suomessa ja Ruotsissa voidaan määrittää strategioita jakelukeskusten (DC) sijaintiin käyttämällä matkan etäisyyden minimoimista. Kullekin skenaariolle kehitetään matka-aikakartat. Lisäksi analysoidaan näistä kolmesta maasta koostuvaa pohjoismaista aluetta ja esitetään viisi mahdollista sijaintia optimointituloksena. Toinen tapaustutkimus esittelee kuljetuskustannusmallintamisen prosessissa, jossa puutavaraa kerätään useilta alueilta ja kuljetetaan lähimpään keräyspisteeseen. Tämä tutkimusprojekti esittelee agenttipohjaista mallinnusta (ABM), joka yhdistää kattavasti noudon ja toimituksen toimitusketjumallin keskeiset elementit ja suunnittelee komponentit keskenään kommunikoiviksi autonomisiksi agenteiksi. Mallinnuksessa yhdistetään erilaisia komponentteja, kuten GIS-reititys, mahdolliset tilojen sijainnit, satunnaiset puunhakupaikat, kaluston mitoitus, matkan pituus sekä monimuotokuljetukset. ABM:n avulla mallinnetaan noutojen ja toimituksien koko ketju ja tuloksena saadaan aikasarjoja kuvaamaan käytössä olevat kuorma-autot, sekä varastomäärät ja ajetut matkat. Lisäksi arvioidaan erilaisia simuloinnin skenaarioita mahdollisten laitosten sijainnista ja kuorma-autojen lukumäärästä sekä tunnistetaan optimaalinen toimipisteen sijainti ja tarvittava autojen määrä. Kolmannessa tapaustutkimuksessa agenttipohjaista mallinnusstrategiaa käytetään ratkaisemaan ajoneuvojen aikataulujen ja kaluston optimoinnin ongelma. Ratkaisumenetelmää käytetään dataan, joka on peräisin todellisesta organisaatiosta, ja ratkaisun tehokkuuden arvioimiseksi luodaan lukuisia keskeisiä suorituskykyindikaattoreita. ABM-menetelmä, toisin kuin monet muut mallintamismenetelmät, on täysin räätälöitävissä oleva menetelmä, joka voi sisältää laajasti erilaisia prosesseja ja elementtejä. Autonomisia agentteja soveltava ABM voi integroida erilaisia komponentteja, jotka ovat olemassa monimutkaisessa toimitusketjussa ja luoda vastaavan järjestelmän toimitusketjun tehokkuuden arvioimiseksi yksityiskohtaisesti.fi=vertaisarvioitu|en=peerReviewed

Novel approach for integrated biomass supply chain synthesis and optimisation

Despite looming energy crises, fossil resources are still widely used for energy and chemical production. Growing awareness of the environmental impact from fossil fuels has made sustainability one of the main focuses in research and development. Towards that end, biomass is identified as a promising renewable source of carbon that can potentially replace fossil resources in energy and chemical productions. Although many researches on converting biomass to value-added product have been done, biomass is still considered underutilised in the industry. This is mainly due to challenges in the logistic and processing network of biomass. An integrated biomass supply chain synthesis and optimisation are therefore important. Thus, the ultimate goal of this thesis is to develop a novel approach for an integrated biomass supply chain. Firstly, a multiple biomass corridor (MBC) concept is presented to integrate various biomass and processing technologies into existing biomass supply chain system in urban and developed regions. Based on this approach, a framework is developed for the synthesis of a more diversified and economical biomass supply chain system. The work is then extended to consider the centralisation and decentralisation of supply chain structure. In this manner, P-graph-aided decomposition approach (PADA) is proposed, whereby it divides the complex supply chain problem into two smaller sub-problems – the processing network is solved via mixed-integer linear programming (MILP) model, whereas the binaries-intensive logistic network configuration is determined through P-graph framework. As existing works often focus on supply chain synthesis in urban regions with well-developed infrastructure, resources integrated network (RIN) – a novel approach for the synthesis of integrated biomass supply chain in rural and remote regions is introduced to enhance rural economies. This approach incorporates multiple resources (i.e. bioresources, food commodities, rural communities’ daily needs) into the value chain and utilises inland water system as the mode of transport, making the system more economically feasible. It extends the MBC approach for technology selection and adopts vehicle routing problem (VRP) for inland water supply and delivery network. To evaluate the performance of the proposed integrated biomass supply chain system, a FANP-based (fuzzy analytical network process) sustainability assessment tool is established. A framework is proposed to derive sustainability index (SI) from pairwise comparison done by supply chain stakeholders to assess the sustainability of a system. Fuzzy limits are introduced to reduce uncertainties in human judgment while conducting the pairwise comparison. To design a sustainable integrated biomass supply chain, a FANP-aided, a novel multiple objectives optimisation framework is proposed. This approach transforms multiple objective functions into single objective function by prioritising each of the objective through the FANP framework. The multiple objectives are then normalised via max-min aggregation to ensure the trade-off between objectives is performed on the same scale. At the end of this thesis, viable future works of the whole programme is presented for consideration