The project X-TEAM D2D (extended ATM for door-to-door travel) has been funded by SESAR JU in the framework of the research activities devoted to the investigation of integration of Air Traffic Management (ATM) and aviation into a wider transport system able to support the implementation of the door-to-door (D2D) travel concept. The project defines a concept for the seamless integration of ATM and Air Transport into an intermodal network, including other available transportation means, such as surface and waterways, to contribute to the 4 h door-to-door connectivity targeted by the European Commission in the ACARE SRIA FlightPath 2050 goals. In particular, the project focused on the design of a concept of operations for urban and extended urban (up to regional) integrated mobility, taking into account the evolution of transportation and passengers service scenarios for the next decades, according to baseline (2025), intermediate (2035) and final target (2050) time horizons. The designed ConOps encompassed both the transportation platforms integration concepts and the innovative seamless Mobility as a Service, integrating emerging technologies, such as Urban Air Mobility (e.g., electric vertical take-off and landing vehicles) and new mobility forms (e.g., micromobility vehicles) into the intermodal traffic network, including Air Traffic Management (ATM) and Unmanned Traffic Management (UTM). The developed concept has been evaluated against existing KPAs and KPIs, implementing both qualitative and quantitative performance assessment approaches, while also considering specific performance metrics related to transport integration efficiency from the passenger point of view, being the proposed solution designed to be centered around the passenger needs. The aim of this paper is to provide a description of the activities carried out in the project and to present at high level the related outcomes.
This research aims to find relevant evidence on whether there is a link between air capacity management (ACM) optimization and airline operations, also considering the airline business model perspective. The selected research strategy includes a case study based on Paris Charles de Gaulle Airport to measure the impact of ACM optimization variables on airline operations. For the analysis we use historical data which allows us to evaluate to what extent the new schedule obtained from the optimized scenario disrupts airline planned operations. The results of this study indicate that ACM optimization has a substantial impact on airline operations. Moreover, the airlines were categorized according to their business model, so that the results of this study revealed which category was the most affected. In detail, this study revealed that, on the one hand, Full-Service Cost Carriers (FSCCs) were the most impacted and the presented ACM optimization variables had a severe impact on slot allocation (approximately 50% of slots lost), fuel burn accounted as extra flight time in the airspace (approximately 12 min per aircraft) and disrupted operations (approximately between 31% and 39% of the preferred assigned runways were changed). On the other hand, the comparison shows that the implementation of an optimization model for managing the airport capacity, leads to a more balanced usage of runways and saves between 7% and 8% of taxi time (which decreases fuel emission).
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Airport capacity, expressed as the maximum number of air traffic movements that can be accommodated during a given period of time under given conditions, has become a hard constraint to the air transportation, due to the scarce amount of resources on the ground and restrictions in the airspace. Usually the problem of capacity at airports is studied separating airspace operations from ground operations, but it is evident that the two areas are tied to each other. This work aims at developing a simulation model that takes into account both airspace and ground operations. The approach used is a divide and conquer approach, which allows the combination of four different models. The four models refer to the airside, and airspace operations. This approach allows to evaluate the system from diffrent angles depending on the scope of the study, the results show the analytic potential of this approach.
