Artificial Intelligence in Aircraft Docking: The Fear of Reducing Ground Marshalling Jobs to Robots and Way-Out

  • Adeniran, Adetayo Olaniyi Department of Transport Management Technology, Federal University of Technology, Akure, Nigeria
  • Kanyio, Olufunto Adedotun Department of Transport Management Technology, Federal University of Technology, Akure, Nigeria
Keywords: Artificial İntelligence, Ground Marshalling, Air Transportation.


This study gaudily examines the impact of Artificial Intelligence on aircraft docking, and technophobia that may arise on the part of ground marshallers. Ground marshallers are ground personnel that signal or communicate visually to pilots when docking the aircraft in an airport. Artificial Intelligence is an expert system which can be incorporated in different areas, such as finance, transportation, aviation, and tele-communications. Attitude theory and Technology Acceptance Model (TAM) were used to establish the acceptance of Artificial Intelligence. It should be noted that expert systems make decisions which requires human level of expertise. In order to reduce the fear that technology will replace the jobs of human in the field of air transportation particularly with aircraft docking, it is crucial for airport personnel to embrace the upcoming revolution by developing themselves as regard Artificial Intelligence; Universities should prepare the transport students to face the upcoming reality. Also various organizations should put in place necessary resources needed to be part of this revolution which will be fully achieved in the fourth indus-trial revolution and the fifth industrial revolution.


Adeniran, A. O. (2014). Perception of Ground Marshallers towards the Use of Visual Docking Guidance System (VDGS) Using Murtala Muhammed International Airport as Case Study. An Unpublished Undergraduate Thesis Submitted to the Department of Transport Management, Ladoke Akintola University, Ogbomoso, Oyo State, Nigeria.
Allport, G. W. (1935). Attitudes. In: Murchison C. (Ed.), Handbook of Social Psychology.
Andrei A. Kirilenko and Andrew W. Lo. (2013). Moore’s Law versus Murphy’s Law: Algorithmic Trading and Its Discontents. Journal of Economic Perspectives.
António, B. Moniz and Bettina-Johanna Krings (2016). Robots Working with Humans or Humans Working with Robots? Searching for Social Dimensions in New Human-Robot Interaction in Industry. Societies, 6 (23).
Barattini, P., Wögerer, C., Robertson, N., Morand, C., Pichler, A., Rovetta, A., Corradini, A., Samani, H., Hopgood, J., and Almajai, I. (2012). In the Reference Proposal to the Workshop on Human Interaction with Industrial Collaborative Autonomous Robots. In Proceedings of the 2012 Conference on RO-Man, Paris, France, 9–13 September 2012.
Chan, D. C. and E. Auster. (2003). Factors Contributing to the Professional Development of Reference Librarians. Library & Information Science Research, 25, 265-286.
David, T. (2017). Robots are Taking Jobs, but also Creating them. Research Review. [Accessed 29th December, 2017]
Executive Office of the President (2016). Artificial Intelligence, Automation, and the Economy. White House, 2016. [Accessed 29th December, 2017]
EUROP. Robotic Visions to 2020 and beyond the Strategic Research Agenda for Robotics in Europe.
Available online: (Accessed on 22nd December, 2017).
Fine, S. (1986). Technological Innovation, Diffusion and Resistance: An Historical Perspective. Journal of Library Administration, 7(1), 83-108.
Fine, S. (1994). A Psychologist’s Response. The Journal of Academic Librarianship, 20(3), 138-139.
George, J. (2002). Influences on the Intent to Make Internet Purchases. Internet Research, 12(2), 165-80.
Gribbins, M., Shaw, M. and Gebauer, J. (2003). An Investigation into Employees’ Acceptance of Integrating Mobile Commerce into Organizational Processes. Proceedings of the 9th Americas Conference on Information Systems, Tampa, FL, 77-87.
IFR-International Federation of Robotics. World Robotics 2015; IFR: Frankfurt, Germany.
Kelly, G. (2016). The Robots are Coming. Will they Bring Wealth or a Divided Society? Available online:
Leandros A. M., Ali, H. A., Ying, H., Isabel, W. and Helge, J. (2016). Social Internet of Vehicles for Smart Cities. Journal of Sensor and Actuator Networks. Vol. 5, No. 3, 1-26; doi:10.3390/jsan5010003.
Mathieson, K. (1991). Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior. Information Systems Research, 2(3), 173-91.
Moniz, A. B. (2016). Redesigning Work Organizations and Technologies: Experiences from European Projects. Available online:
New York Times: Bits Robotica Series. Available online: (Accessed on 22nd December, 2017).
OCED (2015). The Future of Productivity; OECD Publishing: Paris, France.
Spacey Z., Attwell, T. (1998). Attitude of Library Staff to the Use of ICT in Business School Library, Selected. Dergipark
Spacey, R., Goulding, A. and Murry, I. (2004). Exploring the Attitudes of Public Library Staff to the Internet Using TAM. Journal of Documentation, 60(5), 550-564.
Taylor, S. and Todd, P. A. (1995).Understanding information technology usage: A test of competing models. Information System Research, 6(2), 144-74.
The Economist Newspaper Limited (2016). The Impact on Jobs. Automation and Anxiety. Will Smarter Machines Cause Mass Unemployment? [Accessed 29th December, 2017]
Van Est, R., Kools, L., Eds. (2015). Working on the Robot Society; Rathenau Instituut: The Hague, The Netherlands.
Venkatesh, V., M. G. Morris, Davis, G. B. and Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly 27(3), 425-478.
How to Cite
Adetayo Olaniyi, A., & Olufunto Adedotun, K. (2018). Artificial Intelligence in Aircraft Docking: The Fear of Reducing Ground Marshalling Jobs to Robots and Way-Out. American International Journal of Multidisciplinary Scientific Research, 1(2), 25-32.
Research Paper/Theoretical Paper/Review Paper/Short Communication Paper