Advances in Public Transport Platform for the Development of Sustainability Cities
Corchado, Juan M. (editor)
Larriba-Pey, Josep L. (editor)
Chamoso, Pablo (editor)
De la Prieta, Fernando (editor)
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.
Keywordsoptimization models; timetable; passenger waiting time; vehicle occupancy ratio; intelligent transportation systems; demand prediction; taxi recommendation; vehicle social network; ride-hailing; urban rail transit (URT); exploratory data analysis (EDA); data envelopment analysis (DEA); sustainable transport systems; intelligent transportation systems (ITS); big-data applications; dynamic bus travel time prediction; wide and deep; data fusion; attention; recurrent neural network; deep neural networks; intelligent transportation; railway; CPS; security; safety; critical infrastructure; carsharing; data analysis; delays; demand; public transit; taxi; complex network analysis; centrality measures; network robustness; ridership patterns; clustering analysis; passenger flow; Barcelona underground; artificial intelligence; Big Data analytics; forecasting systems; recommender system; Fintech; passenger traffic; artificial neural network; regression analysis; reputation algorithm; users’ reputation; transport; software application; deep learning; energy consumption; sustainable cities; transfer learning; wastewater treatment plants; unmanned aerial vehicles (UAVs); multi-objective optimization; integer programming; GLPK; variable neighborhood search; search and rescue; learning recommender system; learning object; learning videos; content-based; collaborative filtering; users’ profiling; data extraction; natural language processing; mapping application; time series forecasting; HTM; regression; machine intelligence; cyber-attack detection; IoT; trust; energy trading; trusted negotiations; n/a
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Publication date and placeBasel, 2022
Technology: general issues
History of engineering & technology
Environmental science, engineering & technology