Impact of ATCO Training and Expertise on Dynamic Spatial Abilities

Dynamic spatial ability is supposed to be involved in a critical process of air traffic controllers, namely conflict detection. The present paper aims at testing whether dynamic spatial ability improves with air traffic control training and/or experience. We designed a laboratory task to assess the performance in predicting if two moving disks would collide or not. We conducted a crosssectional study with four groups of participants : ATCO trainees at the beginning (N=129), middle (N=80) or end of training (N=66) and experienced ATCOs (N=14). Results suggested on one hand that air traffic control training leads to a decrease in the number of extremely high proportions of undetected collisions from the middle of the training. On the other hand, air traffic control operational experience leads to a decrease in the number of extremely high proportions of falsely detected collisions

EEG-based cognitive control behaviour assessment: an ecological study with professional air traffic controllers

Several models defining different types of cognitive human behaviour are available. For this work, we have selected the Skill, Rule and Knowledge (SRK) model proposed by Rasmussen in 1983. This model is currently broadly used in safety critical domains, such as the aviation. Nowadays, there are no tools able to assess at which level of cognitive control the operator is dealing with the considered task, that is if he/she is performing the task as an automated routine (skill level), as procedures-based activity (rule level), or as a problem-solving process (knowledge level). Several studies tried to model the SRK behaviours from a Human Factor perspective. Despite such studies, there are no evidences in which such behaviours have been evaluated from a neurophysiological point of view, for example, by considering brain activity variations across the different SRK levels. Therefore, the proposed study aimed to investigate the use of neurophysiological signals to assess the cognitive control behaviours accordingly to the SRK taxonomy. The results of the study, performed on 37 professional Air Traffic Controllers, demonstrated that specific brain features could characterize and discriminate the different SRK levels, therefore enabling an objective assessment of the degree of cognitive control behaviours in realistic setting

Human Factors and Neurophysiological Metrics in Air Traffic Control: a Critical Review

International audienceThis article provides the reader a focused and organised review of the research progresses on neurophysiological indicators, also called “neurometrics”, to show how neurometrics could effectively address some of the most important Human Factors (HFs) needs in the Air Traffic Management (ATM) field. The state of the art on the most involved HFs and related cognitive processes (e.g. mental workload, cognitive training) is presented together with examples of possible applications in the current and future ATM scenarios, in order to better understand and highlight the available opportunities of such neuroscientific applications. Furthermore, the paper will discuss the potential enhancement that further research and development activities could bring to the efficiency and safety of the ATM service

Aircraft Dynamic Rerouting Support

In the frame of Clean Sky 2 JU, the HARVIS (Human Aircraft Roadmap for Virtual Intelligent System) project introduces a cockpit assistant committed to help the pilot to reroute the aircraft in single-pilot operations. A relevant scenario for this AI assistant is that in which diversion to alternate airfield is required after an emergency. Another interesting scenario is the anticipation of radar vectors in the arrivals with time enough to safely configure the aircraft for the descent. A demonstrator is being developed for this second scenario in the context of Project HARVIS (www.harvis-project.eu). Diversion is often required after system failure, medical emergency, or just for weather phenomena (dense fog, storms, etc.) in the approaching. During regular operation if a diversion is needed the pilot in command and first officer discuss on the multiple options they have and try to find out the one they think is the best. The AI assistant will take into account characteristics of nearby airports, METAR at destination, and facilities to take care of passengers, among other factors. It may then consider several options, assess the risks and benefits of each one, and finally inform the pilot accordingly. In this scenario, the digital assistant takes care of the Options and Risks in a FORDEC procedure

Toward a Non Stabilized Approach assistant based on human expertise

97% of Non-Stabilized Approach (NSA) are continued until landing going against Standard Operational Procedures (SOP). For some of these approaches, the reason is a lack of situation awareness for others it is because of operational constraints that standard SOP do not take into account like ATC, remaining fuel on board, weather… Most of the time everything goes well but pilots often admit afterwards that they should have go-around and that safety margins were greatly reduced

Modeling the Controller's Conflict Detection Task Using Fast Time Simulation

International audienceThis paper shows how the CATS (Complete Air Traffic Simulator) can model the controller¡¯s conflict detection task using a sliding time window. Because of uncertainties, detection is by far the most time consuming and cognitively challenging aspect of air traffic control. The processes governing detection are distinct from resolution actions. Few conflicts detected lead to a resolution maneuver. Because future aircraft positions are uncertain, controllers detect many more conflicts or "potential conflicts" than actually occur. In this paper, we solve conflicts in a real time context and compare different uncertainty scenarios. We show how uncertainties impact the number of theoretical potential conflicts detected and the increase the number of unnecessary maneuver actions required to keep the traffic safe. When we deal with realistic uncertainty values, the majority of calculation time in CATS is used for calculating maneuvers that will usually not be transmitted to pilots. This observation reveals the true nature of the controller¡¯s workload today

Détection et résolution de conflits aériens (Modélisations et analyse)

PALAISEAU-Polytechnique (914772301) / SudocSudocFranceF

The Influence of Uncertainties on Traffic Control using Speed Adjustments

International audienceThe RTA (Required Time Arrival) capabilities of aircraft FMS (Flight Management Systems) offer new opportunities to solve mid-term horizon conflicts (20 minutes in advance) with small speed adjustments. The ERASMUS project has shown promising results of up to $80\%$ conflict resolution using small speed adjustments in the $[-6\%;+3\%]$ range with 20 minutes advance notice. The hypotheses were based on very accurate trajectory predictions (TPs). In this article we show how the quality of these results decreases as the uncertainties on the trajectory prediction increase. Therefore we used the CATS (Complete Air Traffic Simulator) developed in the late 90s at CENA (Centre d'Etudes de la Navigation A\'erienne) and constrained the solver to use only speed maneuvers for leveled or descending aircraft with different hypotheses on speed ranges and speed uncertainties. Results show that Traffic Control using Speed Adjustments (TCSA) can solve most of the conflicts even when we consider uncertainty on the TP. However, the number of maneuvers that need to be given to aircraft is highly influenced by the uncertainties used in the TP