Simulation of urban air mobility (UAM) is a growing challenge – especially considering the risks of aircraft collisions. This study shows the importance of a simulation of a large number of vertical take-off and landing (VTOL) vehicles operating in one airspace. The purpose of this study is to investigate the proper modelling and implementation of the collision algorithm between the VTOLs. This study shows an approach based on which the tool could be used for a further detailed analysis of risk assessment.
This study uses the UAM Traffic Analysis Tool, which facilitates the simulation of various VTOL traffic scenarios and the analysis of their dynamics. The approach includes input data modelling, scenario generation and the application of collision detection algorithms, such as the Foster method.
The results demonstrate that using metrics that account for VTOL vehicles “existence” provides more accurate estimates of collision counts and risk-prone areas. The findings also indicate that decentralised control methods may offer greater efficiency in managing large volumes of drone traffic.
This research introduces a novel simulation tool for UAM, offering valuable insights into risk management and collision prevention. The findings contribute to the advancement of safety regulations and operational strategies, paving the way for more effective air traffic management solutions in urban environments.
