Abstract
AbstractThe aim of this paper is to provide preliminary results on a traffic coordination framework based on stochastic task allocation. General trends and the predicted advent of personal aerial vehicles increase traffic rapidly, but current air traffic management methods admittedly cannot scale appropriately. A hierarchical system is proposed to overcome the problem, the middle layer of which is elaborated in this paper. This layer aims to enable stochastic control of traffic behaviour using a single parameter, which is achieved by applying distributed stochastic task allocation. The task allocation algorithm is used to allocate speeds to vehicles in a scalable way. By regulating the speed distribution of vehicles the conflict rates remain manageable. Multi-agent simulation results show that it is possible to control ensemble dynamics and together with that traffic safety and throughput via a single parameter. Using transient simulations the dynamic performance of the system is analysed. It is shown that the traffic conflict reduction problem can be transformed into a control design problem. The performance of a simple controller is also evaluated. It was shown that by applying the controller, quicker transients can be achieved for the mean speed of the system.
Highlights
1.1 Background and motivationBased on general trends in the aerospace industry a significant growth in air traffic can be expected
This paper proposes a traffic management framework and elaborates the middle layer, which is based on distributed stochastic task allocation
The aim, which is to coordinate the ensemble dynamics of traffic using a stochastic algorithm with a single parameter input is proven by the extensive simulation campaign to be appropriately accomplished
Summary
1.1 Background and motivationBased on general trends in the aerospace industry a significant growth in air traffic can be expected. An annual growth rate of 3.1% in commercial airline fleet and 4.0% in traffic is predicted for the 20 years by Boeing [1], which affects the utilisation of the controlled airspace. With the introduction of personal air mobility vehicles (PAVs) and air taxis [2] an even greater increase is forecast for urban air mobility (UAM) [3], which will definitely “stress the current ATM (Air Traffic Management) system” [4]. The annual growth rate for the urban air mobility market is forecast to be between 12% and 33.9% in the few years according to recent estimations in market studies [5,6,7,8,9,10,11]. The need emerges for an autonomous, fully digitised traffic management system to perform traditional ATC (Air Traffic Control) functions. Within the scope of this paper, a free flight scenario [15] is considered
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