Abstract
Autonomous vehicles equipped with integrity augmentation systems offer the potential to increase safety, efficiency and sustainability of airport ground operations. The model predictive behavior of these systems supports a timely detection of any deviations from the Required Navigation Performance (RNP), producing useful alerts for onboard mission management. Firstly, the system architecture of a Navigation and Guidance System (NGS) for autonomous airport surface vehicle operations based on Global Navigation Satellite System (GNSS) measurements is described. Subsequently, an integrity augmentation module is implemented in the NGS by modeling the key GNSS signal degradation phenomena including masking, multipath and signal attenuation. The GNSS integrity augmentation system is capable of monitoring the RNP and alerting the remote operator of the airport surface vehicle. The uniqueness of the presented system is that both caution and warning flags are produced based on prediction-avoidance and reaction-correction capabilities respectively. Additionally, the system is capable of issuing suitable steering commands to the onboard mission management system/remote ground base station operator in the event of GNSS signal degradations or losses. Multipath is modelled in detail using a ray tracing algorithm and the vehicle position error is computed as a function of relative geometry between the satellites, receiver antenna and reflectors in realistic airport operation scenarios. Additionally, the surface vehicle dynamics and reflective surfaces of buildings are modelled in order to simulate a vehicle trajectory through a typical airport airside/aprons environment. Simulation case studies are performed to validate the mathematical models developed for the integrity augmentation system and the results corroborate the suitability of the proposed system to generate useful and timely integrity flags when GNSS is used as the primary means of navigation.
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