In the framework of the COAST (Cost Optimized Avionics SysTem) project funded by Clean Sky 2 Joint Undertaking in the European Union’s Horizon 2020 Research and Innovation Programme, several key technologies are under development, aimed to enable single pilot operations of Small Air Transport (SAT) vehicles. One of these technologies is AWAS (Advanced Weather Awareness System), which aims to provide and visualize on board of the aircraft updated weather information regarding areas affected by weather hazards, in order to increase the weather awareness of the pilot. The system is composed by three main components: AWAS on-ground, devoted to generate and provide on board data regarding weather hazards observed and forecast along the flight route; AWAS on-board, aimed to send on-ground information concerning aircraft position and current time and to elaborate data provided by AWAS on-ground; AWAS Human Machine Interface (HMI), that visualize data on-board over a Portable Electronic Device (PED). AWAS on-ground and AWAS on-board segments are connected each other via a low-cost satellite communication system. The meteorological information is extracted from MATISSE (Meteorological AviaTIon Supporting System), a prototype software developed by the Meteorology Laboratory of CIRA. This paper describes the main functionalities and components of the system under development, highlighting the advancements achieved with respect to the one presented in 2020, and the work performed to allow the on-board integration of AWAS system. Furthermore, the paper reports the main results obtained during the dedicated flight test campaign successfully completed in summer 2021, validating the technology when integrated into the aircraft.
It is well known that, in the aviation sector, flights are strongly influenced by weather conditions, especially considering small aircrafts. This kind of vehicles, ideal for transportation on regional base, are having an increasing importance in the last decades. In the framework of the COAST (Cost Optimized Avionics SysTem) project, funded by Clean Sky 2, several key technologies are under development for the affordable cockpit and avionics in the area of small aircrafts. One of these technologies is AWAS (Advanced Weather Awareness System), devoted to increase the weather awareness of the pilots, providing on board information concerning monitoring and forecasting of weather hazards having not negligible potential impact on the aircrafts. AWAS technology is composed by two applications, namely AWAS on-ground and AWAS on-board, connected each other via a satellite link. The AWAS on-ground is the core of the entire system, devoted to provide on-board synthetic information concerning the weather hazards detected or forecast over an area defined according to the aircraft position. The weather information is extracted from the geodatabase of MATISSE (Meteorological AviaTIon Supporting SystEm), a prototype software developed by the Meteorology Laboratory of CIRA, in which weather data coming from different sources are stored. The AWAS on-board application, instead, is devoted to provide on-ground the required input information (such as the aircraft position). Moreover, it decodes the data received by the on-ground application and allows the visualization of weather information in the cockpit by means of a Human Machine Interface specifically designed for the project. In this work, the main features of the AWAS system are presented, along with the future activities to be carried out in the COAST project.
Purpose This paper aims to describe the advancements of the activities that have been carried out, in the Cost-Optimized Avionics SysTem (COAST) project, to complete the design and in-flight demonstration of the Tactical Separation System (TSS), which is an automatic support system to the pilot’s decision-making, onboard on small air transport (SAT) vehicles under single pilot operations, in the separation management. Design/methodology/approach In the framework of the Clean Sky 2 funded project COAST, some enabling technologies for single pilot operations in the EASA CS-23 category vehicles are designed and demonstrated in flight. Among the relevant flight management technologies addressed in the project, the specific one devoted to the real-time support to pilot’s decision-making in maintaining the vehicle self-separation is the TSS, designed by the Italian Aerospace Research Centre. Findings The TSS design started in the year 2016 and has been completed in the year 2021 after successful in-flight demonstration in the dedicated flight test campaign. The system has been validated by means of several simulation campaigns and finally demonstrated its effectiveness in providing its intended functionalities (situational awareness, conflict detection, conflict resolution) to the pilot in real flight trials, involving the presence of real conflicting aircraft. Originality/value The TSS contributes enabling the implementation of single pilot operations in CS-23 category vehicles, thanks to the possibility to support the pilot with provision of consolidated traffic picture, detection of conflicting surrounding traffic and suggestion of suitable conflict resolution manoeuvre real-time during the flight, through dedicated human–machine interface designed on purpose. The TSS supports the new separation modes that are envisaged in the future SESAR ATM target concept, with particular reference to the possible delegation of the separation responsibility to the pilot.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.