Towards a Persuasive Recommender for Bike Sharing Systems: A Defeasible Argumentation Approach

[EN] This work proposes a persuasion model based on argumentation theory and users' characteristics for improving the use of resources in bike sharing systems, fostering the use of the bicycles and thus contributing to greater energy sustainability by reducing the use of carbon-based fuels. More specifically, it aims to achieve a balanced network of pick-up and drop-off stations in urban areas with the help of the users, thus reducing the dedicated management trucks that redistribute bikes among stations. The proposal aims to persuade users to choose different routes from the shortest route between a start and an end location. This persuasion is carried out when it is not possible to park the bike in the desired station due to the lack of parking slots, or when the user is highly influenceable. Differently to other works, instead of employing a single criteria to recommend alternative stations, the proposed system can incorporate a variety of criteria. This result is achieved by providing a defeasible logic-based persuasion engine that is capable of aggregating the results from multiple recommendation rules. The proposed framework is showcased with an example scenario of a bike sharing system.This work was supported by the projects TIN2015-65515-C4-1-R and TIN2017-89156-R of the Spanish government, and by the grant program for the recruitment of doctors for the Spanish system of science and technology (PAID-10-14) of the Universitat Politècnica de València.Diez-Alba, C.; Palanca Cámara, J.; Sanchez-Anguix, V.; Heras, S.; Giret Boggino, AS.; Julian Inglada, VJ. (2019). Towards a Persuasive Recommender for Bike Sharing Systems: A Defeasible Argumentation Approach. Energies. 12(4):1-19. https://doi.org/10.3390/en12040662S119124Erdoğan, G., Laporte, G., & Wolfler Calvo, R. (2014). The static bicycle relocation problem with demand intervals. European Journal of Operational Research, 238(2), 451-457. doi:10.1016/j.ejor.2014.04.013Alvarez-Valdes, R., Belenguer, J. M., Benavent, E., Bermudez, J. D., Muñoz, F., Vercher, E., & Verdejo, F. (2016). Optimizing the level of service quality of a bike-sharing system. Omega, 62, 163-175. doi:10.1016/j.omega.2015.09.007Schuijbroek, J., Hampshire, R. C., & van Hoeve, W.-J. (2017). Inventory rebalancing and vehicle routing in bike sharing systems. European Journal of Operational Research, 257(3), 992-1004. doi:10.1016/j.ejor.2016.08.029Li, L., & Shan, M. (2016). Bidirectional Incentive Model for Bicycle Redistribution of a Bicycle Sharing System during Rush Hour. Sustainability, 8(12), 1299. doi:10.3390/su8121299Anagnostopoulou, E., Bothos, E., Magoutas, B., Schrammel, J., & Mentzas, G. (2018). Persuasive Technologies for Sustainable Mobility: State of the Art and Emerging Trends. Sustainability, 10(7), 2128. doi:10.3390/su10072128Galbrun, E., Pelechrinis, K., & Terzi, E. (2016). Urban navigation beyond shortest route: The case of safe paths. Information Systems, 57, 160-171. doi:10.1016/j.is.2015.10.005Ferrara, J. (2013). Games for Persuasion: Argumentation, Procedurality, and the Lie of Gamification. Games and Culture, 8(4), 289-304. doi:10.1177/1555412013496891Fei, X., Shah, N., Verba, N., Chao, K.-M., Sanchez-Anguix, V., Lewandowski, J., … Usman, Z. (2019). CPS data streams analytics based on machine learning for Cloud and Fog Computing: A survey. Future Generation Computer Systems, 90, 435-450. doi:10.1016/j.future.2018.06.042Faed, A., Hussain, O. K., & Chang, E. (2013). A methodology to map customer complaints and measure customer satisfaction and loyalty. Service Oriented Computing and Applications, 8(1), 33-53. doi:10.1007/s11761-013-0142-6Xu, W., Li, Z., Cheng, C., & Zheng, T. (2012). Data mining for unemployment rate prediction using search engine query data. Service Oriented Computing and Applications, 7(1), 33-42. doi:10.1007/s11761-012-0122-2GARCÍA, A. J., & SIMARI, G. R. (2004). Defeasible logic programming: an argumentative approach. Theory and Practice of Logic Programming, 4(1+2), 95-138. doi:10.1017/s147106840300167

Multi-Agent Systems

This Special Issue ""Multi-Agent Systems"" gathers original research articles reporting results on the steadily growing area of agent-oriented computing and multi-agent systems technologies. After more than 20 years of academic research on multi-agent systems (MASs), in fact, agent-oriented models and technologies have been promoted as the most suitable candidates for the design and development of distributed and intelligent applications in complex and dynamic environments. With respect to both their quality and range, the papers in this Special Issue already represent a meaningful sample of the most recent advancements in the field of agent-oriented models and technologies. In particular, the 17 contributions cover agent-based modeling and simulation, situated multi-agent systems, socio-technical multi-agent systems, and semantic technologies applied to multi-agent systems. In fact, it is surprising to witness how such a limited portion of MAS research already highlights the most relevant usage of agent-based models and technologies, as well as their most appreciated characteristics. We are thus confident that the readers of Applied Sciences will be able to appreciate the growing role that MASs will play in the design and development of the next generation of complex intelligent systems. This Special Issue has been converted into a yearly series, for which a new call for papers is already available at the Applied Sciences journal’s website: https://www.mdpi.com/journal/applsci/special_issues/Multi-Agent_Systems_2019

PV Charging and Storage for Electric Vehicles

Electric vehicles are only ‘green’ as long as the source of electricity is ‘green’ as well. At the same time, renewable power production suffers from diurnal and seasonal variations, creating the need for energy storage technology. Moreover, overloading and voltage problems are expected in the distributed network due to the high penetration of distributed generation and increased power demand from the charging of electric vehicles. The energy and mobility transition hence calls for novel technological innovations in the field of sustainable electric mobility powered from renewable energy. This Special Issue focuses on recent advances in technology for PV charging and storage for electric vehicles

Advances in Public Transport Platform for the Development of Sustainability Cities

Modern societies demand high and varied mobility, which in turn requires a complex transport system adapted to social needs that guarantees the movement of people and goods in an economically efficient and safe way, but all are subject to a new environmental rationality and the new logic of the paradigm of sustainability. From this perspective, an efficient and flexible transport system that provides intelligent and sustainable mobility patterns is essential to our economy and our quality of life. The current transport system poses growing and significant challenges for the environment, human health, and sustainability, while current mobility schemes have focused much more on the private vehicle that has conditioned both the lifestyles of citizens and cities, as well as urban and territorial sustainability. Transport has a very considerable weight in the framework of sustainable development due to environmental pressures, associated social and economic effects, and interrelations with other sectors. The continuous growth that this sector has experienced over the last few years and its foreseeable increase, even considering the change in trends due to the current situation of generalized crisis, make the challenge of sustainable transport a strategic priority at local, national, European, and global levels. This Special Issue will pay attention to all those research approaches focused on the relationship between evolution in the area of transport with a high incidence in the environment from the perspective of efficiency

Advances on Smart Cities and Smart Buildings

Modern cities are facing the challenge of combining competitiveness at the global city scale and sustainable urban development to become smart cities. A smart city is a high-tech, intensive and advanced city that connects people, information, and city elements using new technologies in order to create a sustainable, greener city; competitive and innovative commerce; and an increased quality of life. This Special Issue collects the recent advancements in smart cities and covers different topics and aspects

CITIES: Energetic Efficiency, Sustainability; Infrastructures, Energy and the Environment; Mobility and IoT; Governance and Citizenship

This book collects important contributions on smart cities. This book was created in collaboration with the ICSC-CITIES2020, held in San José (Costa Rica) in 2020. This book collects articles on: energetic efficiency and sustainability; infrastructures, energy and the environment; mobility and IoT; governance and citizenship

Mobi-System: towards an information system to support sustainable mobility with electric vehicle integration

Tese de doutoramento do Programa Doutoral em Líderes para as Indústrias Tecnológicas (Programa MIT-Portugal - Área EDAM)The current Thesis proposes the conceptual aspects and the preliminary prototype of a mobile information system to support information integration and manipulation towards the Electric Vehicle (EV) introduction, and the support of mobility process in urban environments, giving recommendations to drivers about EV range autonomy, charging stations, electricity market, and also as route planner taking into account public transportation, car or bike sharing systems. The main work objective is the creation of an Information and Communication Technology (ICT) platform based on successful approaches developed in the Computer Science Area, recommender systems, cooperative systems and mobile devices, to help the driver of EV by giving real time information related with EV charging process, range autonomy, electricity market participation, and also smart mobility process in cities by giving guidance towards best route options, taking into account time travel and CO2 emissions. Based on the analysis of the problem a conceptual system and a prototype application were created under the designation “Mobi-System”, designed to mobile devices, with relevant information oriented to: (1) EV charging process; (2) EV range autonomy; (3) electricity market participation; and (4) mobility process in smart cities of the future. In this work it was developed an application to store data related with EV charging/discharging process, for further intelligent analysis and remote interaction with the charging system, determining a smart charging procedure, taking into account the distribution electrical system limitations, and the creation of communities with participation in the electricity market. A range estimation and representation process is introduced as part of the help process to assist EV drivers. An Aggregator system and a collaborative broker for distributed energy sources are proposed, taking into account the electricity market. A proposal for data integration of different transportation sources and a multimodal best route path are proposed based on CO2 emissions and time travel.O presente trabalho consiste na concepção e discussão do sistema Mobi-System, que disponibiliza informação relevante para condutores de veículos elétricos (VE), tendo em conta os problemas dos carregamentos dos VE, a gestão da ansiedade de autonomia (range anxiety) dos condutores, a participação no mercado de energia elétrica, a integração das fontes de energia renováveis, bem como a integração de informação de transportes públicos e a criação de sistemas para gerir o problema da mobilidade sustentável em cidades inteligentes (smart cities). O objectivo principal do trabalho é o uso apropriado de Tecnologia da Informação e Comunicação (TIC) baseada em abordagens bem-sucedidas desenvolvidas na área da informática, como os sistemas de recomendação, sistemas cooperativos e dispositivos móveis para ajudar o condutor de VE, dando informações relevantes em tempo real, orientando o condutor para os pontos de carregamento públicos, ou para o melhor caminho tendo em conta o tempo e as políticas ambientais, nomeadamente as emissões de CO2. Com base na análise do problema, um sistema conceitual e uma aplicação protótipo foram criadas sob a designação de Mobi-System, projetada para dispositivos móveis com informações relevantes orientadas a: (1) processo de carregamento do VE feito num local público com a orientação e a reserva de slots de carregamento, ou em casa com a programação do processo de carregamento lento, tendo em conta limitações de potência; (2) gestão assistida da autonomia dos VE; (3) participação no mercado de energia, pela criação de comunidades de condutores com capacidade de participar no mercado de energia, dado o VE poder atuar como um armazenador de energia; e (4) processo de mobilidade em cidades inteligentes do futuro, com a proposta de integração de dados de diferentes tipos de transporte, com indicação do trajeto de melhor rota multimodal, proposto com base nas emissões de CO2 e no tempo das viagens

iCity. Transformative Research for the Livable, Intelligent, and Sustainable City

This open access book presents the exciting research results of the BMBF funded project iCity carried out at University of Applied Science Stuttgart to help cities to become more liveable, intelligent and sustainable, to become a LIScity. The research has been pursued with industry partners and NGOs from 2017 to 2020. A LIScity is increasingly digitally networked, uses resources efficiently, and implements intelligent mobility concepts. It guarantees the supply of its grid-bound infrastructure with a high proportion of renewable energy. Intelligent cities are increasingly human-centered, integrative, and flexible, thus placing the well-being of the citizens at the center of developments to increase the quality of life. The articles in this book cover research aimed to meet these criteria. The book covers research in the fields of energy (i.e. algorithms for heating and energy storage systems, simulation programs for thermal local heating supply, runtime optimization of combined heat and power (CHP), natural ventilation), mobility (i.e. charging distribution and deep learning, innovative emission-friendly mobility, routing apps, zero-emission urban logistics, augmented reality, artificial intelligence for individual route planning, mobility behavior), information platforms (i.e. 3DCity models in city planning: sunny places visualization, augmented reality for windy cities, internet of things (IoT) monitoring to visualize device performance, storing and visualizing dynamic energy data of smart cities), and buildings and city planning (i.e. sound insulation of sustainable facades and balconies, multi-camera mobile systems for inspection of tunnels, building-integrated photovoltaics (BIPV) as active façade elements, common space, the building envelopes potential in smart sustainable cities)

Smart Sustainable Mobility: Analytics and Algorithms for Next-Generation Mobility Systems

To this date, mobility ecosystems around the world operate on an uncoordinated, inefficient and unsustainable basis. Yet, many technology-enabled solutions that have the potential to remedy these societal negatives are already at our disposal or just around the corner. Innovations in vehicle technology, IoT devices, mobile connectivity and AI-powered information systems are expected to bring about a mobility system that is connected, autonomous, shared and electric (CASE). In order to fully leverage the sustainability opportunities afforded by CASE, system-level coordination and management approaches are needed. This Thesis sets out an agenda for Information Systems research to shape the future of CASE mobility through data, analytics and algorithms (Chapter 1). Drawing on causal inference, (spatial) machine learning, mathematical programming and reinforcement learning, three concrete contributions toward this agenda are developed. Chapter 2 demonstrates the potential of pervasive and inexpensive sensor technology for policy analysis. Connected sensing devices have significantly reduced the cost and complexity of acquiring high-resolution, high-frequency data in the physical world. This affords researchers the opportunity to track temporal and spatial patterns of offline phenomena. Drawing on a case from the bikesharing sector, we demonstrate how geo-tagged IoT data streams can be used for tracing out highly localized causal effects of large-scale mobility policy interventions while offering actionable insights for policy makers and practitioners. Chapter 3 sets out a solution approach to a novel decision problem faced by operators of shared mobility fleets: allocating vehicle inventory optimally across a network when competition is present. The proposed three-stage model combines real-time data analytics, machine learning and mixed integer non-linear programming into an integrated framework. It provides operational decision support for fleet managers in contested shared mobility markets by generating optimal vehicle re-positioning schedules in real time. Chapter 4 proposes a method for leveraging data-driven digital twin (DT) frameworks for large multi-stage stochastic design problems. Such problem classes are notoriously difficult to solve with traditional stochastic optimization. Drawing on the case of Electric Vehicle Charging Hubs (EVCHs), we show how high-fidelity, data-driven DT simulation environments fused with reinforcement learning (DT-RL) can achieve (close-to) arbitrary scalability and high modeling flexibility. In benchmark experiments we demonstrate that DT-RL-derived designs result in superior cost and service-level performance under real-world operating conditions

iCity. Transformative Research for the Livable, Intelligent, and Sustainable City

This open access book presents the exciting research results of the BMBF funded project iCity carried out at University of Applied Science Stuttgart to help cities to become more liveable, intelligent and sustainable, to become a LIScity. The research has been pursued with industry partners and NGOs from 2017 to 2020. A LIScity is increasingly digitally networked, uses resources efficiently, and implements intelligent mobility concepts. It guarantees the supply of its grid-bound infrastructure with a high proportion of renewable energy. Intelligent cities are increasingly human-centered, integrative, and flexible, thus placing the well-being of the citizens at the center of developments to increase the quality of life. The articles in this book cover research aimed to meet these criteria. The book covers research in the fields of energy (i.e. algorithms for heating and energy storage systems, simulation programs for thermal local heating supply, runtime optimization of combined heat and power (CHP), natural ventilation), mobility (i.e. charging distribution and deep learning, innovative emission-friendly mobility, routing apps, zero-emission urban logistics, augmented reality, artificial intelligence for individual route planning, mobility behavior), information platforms (i.e. 3DCity models in city planning: sunny places visualization, augmented reality for windy cities, internet of things (IoT) monitoring to visualize device performance, storing and visualizing dynamic energy data of smart cities), and buildings and city planning (i.e. sound insulation of sustainable facades and balconies, multi-camera mobile systems for inspection of tunnels, building-integrated photovoltaics (BIPV) as active façade elements, common space, the building envelopes potential in smart sustainable cities)