About this Research Topic
Innovation challenges related to sustainable energy and sustainable transportation require multistakeholder approach to produce a large set of emergent technologies to technical maturity. This Research Topic is a platform for researchers, developers and practitioners to disseminate their latest research, development, results, and innovative ideas in the areas of sustainable energy and sustainable transportation for the smart cities. Such a topic solicits novel solutions and techniques in term of concepts, state-of-the-art, implementations, test-beds, and industrial case studies. Contributions, which can be in the form of Original Research papers, Perspective, Review articles, and technical notes, should focus on following topics of interests (but are not limited to):
• Visions and strategies for convergence of mobility and energy: Electromobility (e-mobility); EV charging infrastructure; EV charging/discharging strategies; low-carbon smart grid and vehicle-to-grid (V2G); cloud and fog computing based applications; cybersecurity; reliability, resilience and sustainability; innovative business models.
• CAEV for sustainable transportation: Smart urban mobility; mobility on demand; mobility as a service; multimodal route planning; cooperative mobility; eco-driving; fuel efficiency and emissions control; CAEV support systems; smart demand management.
• Data analytics: Big data and analytics for sustainable smart e-mobility solutions; big data for CAEV analytics; big data for travel behavior analytics; context-aware mobility related analytics; visualisation approaches; self-learning (pattern discovery, prediction, auto-configuration); optimization and metaheuristics; data mining.
• Sustainable smart city and society: Sustainable smart city policy making; socio-economic and environmental impacts of urban e-mobility; institutional and legal aspects of urban e-mobility; new concepts and case studies of urban e-mobility.
• AI and Machine Learning: AI and smart urban mobility; machine learning, reinforcement learning, deep learning in urban e-mobility; transfer learning and federated learning for CAEV applications in smart cities.
Keywords: Sustainable smart city, sustainable transportation, sustainable energy, connected and autonomous electric vehicles (CAEVs), sustainable smart e-mobility, smart urban mobility, AI and Machine Learning
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.