Air traffic controller perception towards air traffic and taskload

• Published in: International Journal of Engineering and Technology(UAE)
• Main Author: Rahman S.M.B.A.; Sidik M.F.; Nazir F.N.; Jamil M.S.A.
• Format: Article
• Language: English
• Published: Science Publishing Corporation Inc 2018
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056839838&partnerID=40&md5=69756371e3d7e2e38d9a59c651a3ec97

Malaysian airspace in specific Kuala Lumpur Flight Information Region (KLFIR) is considerably strategic due to its geographical location. It is set inbetween major airports in India, the Middle East, and European country on its western side, and airports in Singapore, Indonesia, and Australia on its eastern side. Thus, increasing air traffic movement between these two regions will significantly increase air traffic volume in KLFIR sectors. Currently, with more than 1800 flights per day, crossing, and operating within the airspace, understanding of Air traffic Controller (ATCO) taskload is vital in order to maintain a safe and orderly flow of air traffic. One of the most common method in maintaining an acceptable ATCO taskload level is by establishing the sector capacity or the maximum number of aircraft that can be within a sector at any given time. To capture this, it is important that ATCO perception towards Air Traffic and their taskload is fully understood. Based on interview sessions with active en route controller working at Kuala Lumpur Air Traffic Control Centre (KLATCC), it was found that there were certain sector/ area that was considered more difficult than others due to either its size, radar capabilities or routes organization. Also, there were certain coordination task that were perceived to be more demanding than others, such as coordination with adjacent Area Control Centre (ACC) unit. It is hoped that using the structured input from ATCO, a better understanding of controller perception towards air traffic and taskload can be gathered, enabling design of a more effective working condition with optimum taskload in the future. © 2018 Authors.