Start Date
6-10-2025 9:00 AM
End Date
8-10-2025 7:00 PM
Description
Urban Air Mobility offers an innovative solution to traffic congestion in Indian cities by introducing aerial transport to ease pressure on road networks. To ensure safe and efficient UAM operations, Air Traffic Management (ATM) as a Service is crucial. This framework facilitates real-time coordination between aerial and ground transportation, leveraging existing airspace over metro, rail, and highways to create an integrated urban mobility system. This study explores a service design approach to ATM, focusing on AI-powered air traffic management, real-time communication, and user-friendly systems. AI-driven predictive models optimize UAM routes, reduce congestion, and enhance safety. Additionally, the study examines policy frameworks and infrastructure requirements to support UAM integration while ensuring regulatory compliance. Using a multi-method research approach, including literature reviews, AI-based and stakeholder analysis, the study evaluates ATM implementation. Findings suggest AI driven air traffic control enhances efficiency, while policy interventions and multimodal transport integration are key to ensuring sustainable and scalable UAM adoption in India.
Citation
Kar, S.K., Mathew, D.J., S, M.M.,and John, A.M.(2025) Air Traffic Management as a Service for Urban Air Mobility in Indian Cities: A Study for Scalable and Adaptive Design Framework for Optimizing Airspace Over Rail, Metro, and Roads.. https://dl.designresearchsociety.org/servdes/servdes2025/researchpapers/56
Air Traffic Management as a Service for Urban Air Mobility in Indian Cities: A Study for Scalable and Adaptive Design Framework for Optimizing Airspace Over Rail, Metro, and Roads
Urban Air Mobility offers an innovative solution to traffic congestion in Indian cities by introducing aerial transport to ease pressure on road networks. To ensure safe and efficient UAM operations, Air Traffic Management (ATM) as a Service is crucial. This framework facilitates real-time coordination between aerial and ground transportation, leveraging existing airspace over metro, rail, and highways to create an integrated urban mobility system. This study explores a service design approach to ATM, focusing on AI-powered air traffic management, real-time communication, and user-friendly systems. AI-driven predictive models optimize UAM routes, reduce congestion, and enhance safety. Additionally, the study examines policy frameworks and infrastructure requirements to support UAM integration while ensuring regulatory compliance. Using a multi-method research approach, including literature reviews, AI-based and stakeholder analysis, the study evaluates ATM implementation. Findings suggest AI driven air traffic control enhances efficiency, while policy interventions and multimodal transport integration are key to ensuring sustainable and scalable UAM adoption in India.