The project X-TEAM D2D (Extended ATM for Door-to-Door Travel) has been funded by SESAR JU in 2020 and completed its activities in 2022, pursuing and accomplishing the definition, development and initial assessment of a Concept of Operations (ConOps) for the seamless integration of ATM and air transport into an overall intermodal network, including other available transportation means (surface, water), to support the door-to-door connectivity, in up to 4 hours, between any location in Europe. The project addressed the ATM and air transport, including Urban Air Mobility (UAM), integration in the overall transport network serving urban and extended urban (up to regional level) mobility, specifically identifying and considering the transportation and passengers service scenarios expected for the near, medium and long-term future, i.e. for the project baseline (2025), intermediate (2035) and final (2050) time horizons. In this paper, the main outcomes from the project activities are summarized, with particular emphasis on the studies about the definition of future scenarios and use cases for the integration of the vertical transport with the surface transport towards integrated intermodal transport system and about identification of the barriers towards this goal. In addition, an outline is provided on the specific ConOps for the integration of ATM in intermodal transport infrastructure (i.e. the part of the overall ConOps devoted to integration of different transportation means) and on the specific ConOps for the integration of ATM in intermodal service to passengers (i.e. the specific component of the ConOps devoted to design of a unique service to passengers). Finally, the main outcomes are summarized from the validation of the proposed ConOps through dedicated simulations.
Predictive models and decision support toolsallow information sharing, common situational awarenessand real-time collaborative decision-making betweenairports and ground transport stakeholders. To supportthis general goal, IMHOTEP has developed a set of modelsable to anticipate the evolution of an airport’s passengerflows within the day of operations. This is to assess theoperational impact of different management measures onthe airport processes and the ground transport system. Twomodels covering the passenger flows inside the terminal andof passengers accessing and egressing the airport have beenintegrated to provide a holistic view of the passengerjourney from door-to-gate and vice versa.This paper describes IMHOTEP’s application at two casestudy airports, Palma de Mallorca (PMI) and London City(LCY), at Proof of Concept (PoC-level) assessing impactand service improvements for passengers, airport operatorsand other key stakeholders.For the first time onemeasurable process is created to open up opportunities forbetter communication across all associated stakeholders.Ultimately the successful implementation will lead to areduction of the carbon footprint of the passenger journeyby better use of existing facilities and surface transportservices, and the delay or omission of additional airportfacility capacities.
Anxiety among pregnant women can significantly impact their overall well-being. However, the development of data-driven HCI interventions for this demographic is often hindered by data scarcity and collection challenges. In this study, we leverage the Empatica E4 wristband to gather physiological data from pregnant women in both resting and relaxed states. Additionally, we collect subjective reports on their anxiety levels. We integrate features from signals including Blood Volume Pulse (BVP), Skin Temperature (SKT), and Inter-Beat Interval (IBI). Employing a Support Vector Machine (SVM) algorithm, we construct a model capable of evaluating anxiety levels in pregnant women. Our model attains an emotion recognition accuracy of 69.3%, marking achievements in HCI technology tailored for this specific user group. Furthermore, we introduce conceptual ideas for biofeedback on maternal emotions and its interactive mechanism, shedding light on improved monitoring and timely intervention strategies to enhance the emotional health of pregnant women.
