Сonstruction of a comprehensive autonomous navigation system for service vehicles and aircraft on the territory of an airfield

Аuthors

Baryaksheva V. P.

Saint Petersburg State University of Aerospace Instrumentation, 67, Bolshaya Morskaya str., Saint Petersburg, 190000, Russia

e-mail: vsvally@mail.ru

Abstract

In the context of sanctions pressure from foreign countries, the implementation of domestic research and technologies is a highly relevant area for the development of aviation and air traffic. Import substitution applies not only to large projects such as the SSJ-100NEW, Ту-204СМ, МС-21-300, but also to smaller issues faced daily in the aviation industry, such as airport traffic management. According to the Russian Government Decree "On the Strategic Direction for the Digital Transformation of the Transport Sector of the Russian Federation" until 2030, special attention is being paid to process automation. This issue undoubtedly affects the aviation industry as well.
The annual increase in passenger traffic at the country's key airports requires the deployment of more equipment, engineering personnel, and enhanced monitoring in aircraft loading and maintenance areas. This work focuses on modernizing the visual control system for airport vehicles by creating an assistive autonomous navigation system that classifies obstacle types and generates recommendations for vehicle control, improving airport traffic safety.
Using systems analysis methods, the author presents the system's structure, describes its operating algorithm, and formulates its operational requirements.
For practical results, a reference is provided to previously published results on the lidar channel of an autonomous navigation assistance system. Its distinctive feature is the prediction of the probable trajectory of vehicles by estimating their central cross-sections. Central cross-section information represents the minimum amount of information about objects in the scene. Moreover, it provides information about the vehicle's size, which is an important parameter for large objects such as aircraft. It will also potentially reduce the technical and computational requirements for lidar, reducing the number and density of scanning planes.
The development of the digital economy implies a high degree of automation, especially in the air transportation system as a complex logistics system. The transfer of some control and decision-making functions to artificial intelligence is inevitable, especially for cargo transportation. Examples of proven solutions from other ground transportation sectors offer hope for the successful implementation of driverless technologies in the complex airport infrastructure. Thus, the system being developed meets the challenges of achieving digital transformation in the Russian Federation's transport sector, aligns with promising economic development trends, and has potential for implementation.

Keywords:

automation; aircraft; collision avoidance system; object detection; central section

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