Real-Time State Estimation in a Flight Simulator Using fNIRS

Working memory is a key executive function for flying an aircraft. This function is particularly critical when pilots have to recall series of air traffic control instructions. However, working memory limitations may jeopardize flight safety. Since the functional near-infrared spectroscopy (fNIRS) method seems promising for assessing working memory load, our objective is to implement an on-line fNIRS-based inference system that integrates two complementary estimators. The first estimator is a real-time state estimation MACD-based algorithm dedicated to identifying the pilot’s instantaneous mental state (not-on-task vs. on-task). It does not require a calibration process to perform its estimation. The second estimator is an on-line SVM-based classifier that is able to discriminate task difficulty (low working memory load vs. high working memory load). These two estimators were tested with 19 pilots who were placed in a realistic flight simulator and were asked to recall air traffic control instructions. We found that the estimated pilot’s mental state matched significantly better than chance with the pilot’s real state (62% global accuracy, 58% specificity, and 72% sensitivity). The second estimator, dedicated to assessing single trial working memory loads, led to 80% classification accuracy, 72% specificity, and 89% sensitivity. These two estimators establish reusable blocks for further fNIRS-based passive brain computer interface development

Initial Assessment of the Impact of Modern Taxiing Techniques on Airport Ground Control

Project Modern Taxiing (MoTa) studies the impact of future taxiing technologies such as Datalink and autonomous taxiing tugs on airport taxiing operations and air traffic controller workload. Seven air traffic controllers were asked to manage ground traffic in two scenarios that imposed medium and high levels of workload with three different degrees of automated technology assistance: paper strips; Datalink and path suggestion; Datalink, path suggestion, and tugs. Initial results indicate that participants were able to manage more traffic when using either just the interface or interface and tugs, but the inclusion of tugs also resulted in an increase in self-reported workload. Participants were divided on technology acceptance with no one rejecting completely the new technology

Encoding decisions and expertise in the operator's eyes: Using eye-tracking as input for system adaptation

We investigated the possibility of developing a decision support system (DSS) that integrates eye-fixation measurements to better adapt its suggestions. Indeed, eye fixation give insight into human decision-making: Individuals tend to pay more attention to key information in line with their upcoming selection. Thus, eye-fixation measures can help the DSS to better capture the context that determines user decisions. Twenty-two participants performed a simplified Air Traffic Control (ATC) simulation in which they had to decide to accept or to modify route suggestions according to specific parameter values displayed on the screen. Decisions and fixation times on each parameter were recorded. The user fixation times were used by an algorithm to estimate the utility of each parameter for its decision. Immediately after this training phase, the algorithm generated new route suggestions under two conditions: 1) Taking into account the participant's decisions, 2) Taking into account the participant's decisions plus their visual behavior using the measurements of dwell times on displayed parameters. Results showed that system suggestions were more accurate than the base system when taking into account the participant's decisions, and even more accurate using their dwell times. Capturing the crucial information for the decision using the eye tracker accelerated the DSS learning phase, and thus helped to further enhance the accuracy of consecutive suggestions. Moreover, exploratory eye-tracking analysis reflected two different stages of the decision-making process, with longer dwell times on relevant parameters (i.e. involved in a rule) during the entire decision time course, and frequency of fixations on these relevant parameters that increased, especially during the last fixations prior to the decision. Consequently, future DSS integrating eye-tracking data should pay specific care to the final fixations prior to the decision. In general, our results emphasize the potential interest of eye-tracking to enhance and accelerate system adaptation to user preference, knowledge, and expertise

tert-Butyl 6-bromo-1,4-dimethyl-9H-carbazole-9-carboxyl­ate

The title compound, C19H20BrNO2, consists of a carbazole skeleton with methyl groups at positions 1 and 4, a protecting group located at the N atom and a Br atom at position 6. The pyrrole ring is oriented at dihedral angles of 1.27 (7) and 4.86 (7)° with respect to the adjacent benzene rings. The dihedral angle between the benzene rings is 5.11 (7). The crystal structure is determined mainly by intra­molecular C—H⋯O and inter­molecular π–π inter­actions. π-stacking between adjacent molecules forms columns with a parallel arrangement of the carbazole ring systems. The presence of the tert-but­oxy­carbonyl group on the carbazole N atom and the intra­molecular hydrogen bond induce a particular conformation of the exocyclic N—C bond within the mol­ecule