About this Research Topic
Urban Air Mobility (UAM) is a rapidly advancing field that aims to revolutionize transportation by providing efficient, safe, and sustainable air transportation services. The integration of new technologies such as electric propulsion, advanced materials, artificial intelligence, and digital twin is critical to achieving these goals. The field of electric vertical take-off and landing (eVTOL) aircraft is rapidly evolving, with the potential to revolutionize urban air mobility. However, the integration of new technologies such as artificial intelligence, digital twin, and virtual reality in the design and control of these aircraft poses significant challenges in terms of dynamics and control. These challenges require the development of innovative solutions that can ensure the safe and efficient operation of these aircraft while also supporting the growth and advancement of the urban air mobility industry. One of the major challenges is to ensure the safe and efficient operation of eVTOL aircraft, which are complex systems with multiple rotors and a highly dynamic flight behavior. To address this challenge, advanced control algorithms are being developed that incorporate data from on-board sensors and real-time monitoring systems to optimize the aircraft's flight performance. Additionally, fault detection and isolation techniques are being developed to ensure the safe operation of the aircraft in the event of a system failure. Another challenge is the integration of artificial intelligence (AI) in the design and control of eVTOL aircraft. AI algorithms can be used to optimize the aircraft's flight performance and improve safety by enabling real-time monitoring and decision-making.
However, the integration of AI also poses significant challenges, such as the need for large amounts of high-quality data for training and validation, as well as ensuring the reliability and security of AI systems in the context of aviation. Operational digital twin, also known as digital twin of operations (DTO), is a technology that creates a virtual replica of a physical system, such as a factory or a city, to simulate and optimize its operations in real-time. It allows for the prediction of system behavior, identification of potential failures, and optimization of resources, leading to improved efficiency and resilience. The integration of digital twin technology in the design and control of eVTOL aircraft presents a significant challenge in terms of creating a virtual replica of the aircraft that accurately reflects its behavior and performance. Digital twin technology can be used to simulate and optimize the aircraft's flight performance and to support decision-making in real-time. However, the integration of digital twin technology in the context of aviation also poses significant challenges, such as ensuring the accuracy and reliability of the digital replica, as well as the real-time integration of data from multiple sources.
This Research Topic aims to provide a comprehensive overview of the latest advancements in Urban Air Mobility (UAM) and to identify the key challenges and opportunities associated with the integration of new technologies in this field. The focus is on exploring the potential of electric propulsion, advanced materials, artificial intelligence, and digital twin in revolutionizing transportation and ensuring safe, efficient, and sustainable air transportation services. Ultimately, the goal is to contribute to the growth and development of the urban air mobility industry and to provide practical solutions for the integration of new technologies in UAM.
To gather further insights into the dynamics and control of eVTOL aircraft, operational digital twin, and AI integration, we welcome articles addressing, but not limited to, the following themes:
- AI-based flight control of multi-rotor eVTOL aircraft
- AI-based dynamics digitalization of multi-rotor eVTOL aircraft
- Fault-tolerant and robust control for safety in UAM systems
- Control and navigation for eVTOL aircraft in urban environments
- Real-time control and monitoring of UAM systems using operational digital twin
- Control and optimization of UAM systems using operational digital twin
- Control and optimization of energy consumption in UAM systems
- Control and optimization of traffic flow in UAM systems using operational digital twin
- Design and implementation of control algorithms for UAM systems
- Energy management and control of eVTOL aircraft
- Virtual and mixed reality-based control systems of eVTOL aircraft
- Control and estimation for UAM systems with communication delays and faults
- Integration of UAM with other transportation systems
- Safety, reliability, and risk assessment for UAM operations
However, the integration of AI also poses significant challenges, such as the need for large amounts of high-quality data for training and validation, as well as ensuring the reliability and security of AI systems in the context of aviation. Operational digital twin, also known as digital twin of operations (DTO), is a technology that creates a virtual replica of a physical system, such as a factory or a city, to simulate and optimize its operations in real-time. It allows for the prediction of system behavior, identification of potential failures, and optimization of resources, leading to improved efficiency and resilience. The integration of digital twin technology in the design and control of eVTOL aircraft presents a significant challenge in terms of creating a virtual replica of the aircraft that accurately reflects its behavior and performance. Digital twin technology can be used to simulate and optimize the aircraft's flight performance and to support decision-making in real-time. However, the integration of digital twin technology in the context of aviation also poses significant challenges, such as ensuring the accuracy and reliability of the digital replica, as well as the real-time integration of data from multiple sources.
This Research Topic aims to provide a comprehensive overview of the latest advancements in Urban Air Mobility (UAM) and to identify the key challenges and opportunities associated with the integration of new technologies in this field. The focus is on exploring the potential of electric propulsion, advanced materials, artificial intelligence, and digital twin in revolutionizing transportation and ensuring safe, efficient, and sustainable air transportation services. Ultimately, the goal is to contribute to the growth and development of the urban air mobility industry and to provide practical solutions for the integration of new technologies in UAM.
To gather further insights into the dynamics and control of eVTOL aircraft, operational digital twin, and AI integration, we welcome articles addressing, but not limited to, the following themes:
- AI-based flight control of multi-rotor eVTOL aircraft
- AI-based dynamics digitalization of multi-rotor eVTOL aircraft
- Fault-tolerant and robust control for safety in UAM systems
- Control and navigation for eVTOL aircraft in urban environments
- Real-time control and monitoring of UAM systems using operational digital twin
- Control and optimization of UAM systems using operational digital twin
- Control and optimization of energy consumption in UAM systems
- Control and optimization of traffic flow in UAM systems using operational digital twin
- Design and implementation of control algorithms for UAM systems
- Energy management and control of eVTOL aircraft
- Virtual and mixed reality-based control systems of eVTOL aircraft
- Control and estimation for UAM systems with communication delays and faults
- Integration of UAM with other transportation systems
- Safety, reliability, and risk assessment for UAM operations
Keywords: Urban Air Mobility (UAM), eVTOL aircraft, Dynamics and Control, Operational Digital Twin, Artificial Intelligence (AI)
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.
