A deep reinforcement learning approach for airport departure metering under spatial-temporal airside interactions

• المؤلفون الرئيسيون: Ali, Hasnain, Pham, Duc-Thinh, Schultz, Michael, Alam, Sameer
• مؤلفون آخرون: School of Mechanical and Aerospace Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2022
• الموضوعات: Engineering::Computer science and engineering::Data::Coding and information theory; Airside Traffic Management; Airport Departure Metering
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/161934
• المؤسسة: Nanyang Technological University

Airport taxi delays adversely affect airports and airlines around the world leading to airside congestion, increased Air Traffic Controllers/Pilot workload, and adverse environmental impact due to excessive fuel burn. Airport Departure Metering (DM) is an effective approach to contain taxi delays by...