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A concept for time-related forecasts of lane change maneuvers in highway scenarios is presented within the present work. Automated driving systems rely on understanding the driving environment to fulfill their driving task transparently and safely. This involves the perception of the driving environment as well as its interpretation to detect and predict driving maneuvers of road users.

Fahrstreifenwechsel --- Automatisches Fahren --- Maschinelles Lernen --- dynamic Bayesian networks --- Dynamische Bayes'sche Netzwerke --- lane change --- machine learning --- automated driving

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It has been confirmed that the number of cases and the death toll of COVID-19 are continuing to rise in many countries around the globe. Governments around the world have been struggling with containing and reducing the socioeconomic impacts of COVID-19; however, their respective responses have not been consistent. Aggressive measures imposed by some governments have resulted in a complete lockdown that has disrupted all facets of life and poses massive health, social, and financial impacts. Other countries, however, are taking a more wait-and-see approach in an attempt to maintain business as usual. Collectively, these challenges reflect a super wicked problem that places immense pressure on economies and societies and requires the strategic management of health systems to avoid overwhelming them—this has been linked to the public mantra of ‘flattening the curve’, which acknowledges that while the pandemic cannot be stopped, its impact can be regulated so that the number of cases at any given time is not beyond the capacity of the health system. Dynamic simulation modelling is a framework that facilitates the understanding/exploring of complex problems, of searching for and finding the best option(s) from all practical solutions where time dynamics are essential. The papers in this book provide research insights into this super wicked problem and case studies exploring the interactions between social, economic, environmental, and health factors through the use of a systems approach.

Technology: general issues --- History of engineering & technology --- Environmental science, engineering & technology --- COVID-19 --- pandemic --- wicked problem --- systems approach --- leverage points --- Bayesian Networks --- system thinking --- mathematical epidemiology --- SIR-type model --- model parameter estimation --- non-pharmaceutical intervention --- dynamical systems --- COVID-19/SARS-CoV2 --- computational cognitive science --- semantic networks --- text mining --- social media mining --- emotions --- tour and traveling --- digitalization shift --- change readiness --- expanded TOPSIS --- UK --- vaccination --- immunity --- policy --- system dynamics --- modelling --- uncertainty --- branded content --- marketing --- total interpretive structural modelling --- decision-making Trial and Evaluation Laboratory --- causal loop diagram --- systems thinking --- network theory --- complexity economics --- economic crisis --- agent-based model --- information theory --- global value chains --- megaprojects --- housing markets --- economic networks --- n/a

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It has been confirmed that the number of cases and the death toll of COVID-19 are continuing to rise in many countries around the globe. Governments around the world have been struggling with containing and reducing the socioeconomic impacts of COVID-19; however, their respective responses have not been consistent. Aggressive measures imposed by some governments have resulted in a complete lockdown that has disrupted all facets of life and poses massive health, social, and financial impacts. Other countries, however, are taking a more wait-and-see approach in an attempt to maintain business as usual. Collectively, these challenges reflect a super wicked problem that places immense pressure on economies and societies and requires the strategic management of health systems to avoid overwhelming them—this has been linked to the public mantra of ‘flattening the curve’, which acknowledges that while the pandemic cannot be stopped, its impact can be regulated so that the number of cases at any given time is not beyond the capacity of the health system. Dynamic simulation modelling is a framework that facilitates the understanding/exploring of complex problems, of searching for and finding the best option(s) from all practical solutions where time dynamics are essential. The papers in this book provide research insights into this super wicked problem and case studies exploring the interactions between social, economic, environmental, and health factors through the use of a systems approach.

Technology: general issues --- History of engineering & technology --- Environmental science, engineering & technology --- COVID-19 --- pandemic --- wicked problem --- systems approach --- leverage points --- Bayesian Networks --- system thinking --- mathematical epidemiology --- SIR-type model --- model parameter estimation --- non-pharmaceutical intervention --- dynamical systems --- COVID-19/SARS-CoV2 --- computational cognitive science --- semantic networks --- text mining --- social media mining --- emotions --- tour and traveling --- digitalization shift --- change readiness --- expanded TOPSIS --- UK --- vaccination --- immunity --- policy --- system dynamics --- modelling --- uncertainty --- branded content --- marketing --- total interpretive structural modelling --- decision-making Trial and Evaluation Laboratory --- causal loop diagram --- systems thinking --- network theory --- complexity economics --- economic crisis --- agent-based model --- information theory --- global value chains --- megaprojects --- housing markets --- economic networks --- COVID-19 --- pandemic --- wicked problem --- systems approach --- leverage points --- Bayesian Networks --- system thinking --- mathematical epidemiology --- SIR-type model --- model parameter estimation --- non-pharmaceutical intervention --- dynamical systems --- COVID-19/SARS-CoV2 --- computational cognitive science --- semantic networks --- text mining --- social media mining --- emotions --- tour and traveling --- digitalization shift --- change readiness --- expanded TOPSIS --- UK --- vaccination --- immunity --- policy --- system dynamics --- modelling --- uncertainty --- branded content --- marketing --- total interpretive structural modelling --- decision-making Trial and Evaluation Laboratory --- causal loop diagram --- systems thinking --- network theory --- complexity economics --- economic crisis --- agent-based model --- information theory --- global value chains --- megaprojects --- housing markets --- economic networks

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The concept of sustainability has been intensively used over the last decades since Brundtland´s report was published in 1987. This concept, due to its transversal, horizontal and interdisciplinary nature, can be used in many disciplines, scenarios, spatio-temporal dimensions and different circumstances. The intensive development in recent years of analytical techniques and tools based on disciplines such as artificial intelligence, machine learning, data mining, information theory and the Internet of Things, among others, has meant we are very well-placed for analysing the sustainability of water systems in a multiperspective way. Water systems management requires the most advanced approaches and tools for rigorously addressing all the dimensions involved in the sustainability of its development. Consequently, addressing the sustainability of water systems management may comprise physical (natural processes), chemical, socioeconomic, legal, institutional, infrastructure (engineering), political and cultural aspects, among others. This Special Issue welcomes general and specific contributions that address the sustainability of water systems management considering its development. Special interest will be given to those contributions that consider tradeoffs and/or integration between some of the aspects or disciplines that drive the sustainability of water systems in the context of their management and development.

History of engineering & technology --- suspended solids --- unmanned aerial vehicle --- spectral imaging --- artificial neural networks --- water resource --- South Korean urban industry --- green use efficiency of industrial water (GUEIW) --- global non-radial directional distance function model (GNDDF) --- economic efficiency of industrial water use (ECEIW) --- environmental efficiency of industrial water use (ENEIW) --- water quality --- climate change --- Bayesian networks --- uncertainty --- multi-models --- prioritization --- geomorphometric parameters --- compound parameter --- geospatial distribution --- GIS --- GHGs --- aquatic factors --- random forest --- water temperature --- nitrogen --- sulfate --- concrete arch-dams --- stability scenarios --- deformation scenarios --- safety management --- sustainability assessment --- runoff --- temporal dependence --- rivers’ sustainability --- predictive methods --- causal reasoning --- runoff fractions --- water management --- contamination --- integrated water resources management --- groundwater --- pollution --- Sub-Saharan Africa --- transition management --- water safety plan --- aquifer management --- water governance --- irrigation --- unauthorized use --- barbate river basin --- biocalcarenites --- remote sensing --- citizen surveys --- artificial neural network (ANN) --- chemical oxygen demand (COD) --- wastewater treatment plant (WWTP)

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The concept of sustainability has been intensively used over the last decades since Brundtland´s report was published in 1987. This concept, due to its transversal, horizontal and interdisciplinary nature, can be used in many disciplines, scenarios, spatio-temporal dimensions and different circumstances. The intensive development in recent years of analytical techniques and tools based on disciplines such as artificial intelligence, machine learning, data mining, information theory and the Internet of Things, among others, has meant we are very well-placed for analysing the sustainability of water systems in a multiperspective way. Water systems management requires the most advanced approaches and tools for rigorously addressing all the dimensions involved in the sustainability of its development. Consequently, addressing the sustainability of water systems management may comprise physical (natural processes), chemical, socioeconomic, legal, institutional, infrastructure (engineering), political and cultural aspects, among others. This Special Issue welcomes general and specific contributions that address the sustainability of water systems management considering its development. Special interest will be given to those contributions that consider tradeoffs and/or integration between some of the aspects or disciplines that drive the sustainability of water systems in the context of their management and development.

History of engineering & technology --- suspended solids --- unmanned aerial vehicle --- spectral imaging --- artificial neural networks --- water resource --- South Korean urban industry --- green use efficiency of industrial water (GUEIW) --- global non-radial directional distance function model (GNDDF) --- economic efficiency of industrial water use (ECEIW) --- environmental efficiency of industrial water use (ENEIW) --- water quality --- climate change --- Bayesian networks --- uncertainty --- multi-models --- prioritization --- geomorphometric parameters --- compound parameter --- geospatial distribution --- GIS --- GHGs --- aquatic factors --- random forest --- water temperature --- nitrogen --- sulfate --- concrete arch-dams --- stability scenarios --- deformation scenarios --- safety management --- sustainability assessment --- runoff --- temporal dependence --- rivers’ sustainability --- predictive methods --- causal reasoning --- runoff fractions --- water management --- contamination --- integrated water resources management --- groundwater --- pollution --- Sub-Saharan Africa --- transition management --- water safety plan --- aquifer management --- water governance --- irrigation --- unauthorized use --- barbate river basin --- biocalcarenites --- remote sensing --- citizen surveys --- artificial neural network (ANN) --- chemical oxygen demand (COD) --- wastewater treatment plant (WWTP) --- suspended solids --- unmanned aerial vehicle --- spectral imaging --- artificial neural networks --- water resource --- South Korean urban industry --- green use efficiency of industrial water (GUEIW) --- global non-radial directional distance function model (GNDDF) --- economic efficiency of industrial water use (ECEIW) --- environmental efficiency of industrial water use (ENEIW) --- water quality --- climate change --- Bayesian networks --- uncertainty --- multi-models --- prioritization --- geomorphometric parameters --- compound parameter --- geospatial distribution --- GIS --- GHGs --- aquatic factors --- random forest --- water temperature --- nitrogen --- sulfate --- concrete arch-dams --- stability scenarios --- deformation scenarios --- safety management --- sustainability assessment --- runoff --- temporal dependence --- rivers’ sustainability --- predictive methods --- causal reasoning --- runoff fractions --- water management --- contamination --- integrated water resources management --- groundwater --- pollution --- Sub-Saharan Africa --- transition management --- water safety plan --- aquifer management --- water governance --- irrigation --- unauthorized use --- barbate river basin --- biocalcarenites --- remote sensing --- citizen surveys --- artificial neural network (ANN) --- chemical oxygen demand (COD) --- wastewater treatment plant (WWTP)