Franck Mars

Previous studies have sought to better understand exogenous factors explaining drivers’ ability to regain control or not from highly automated driving. However, few studies have examined the role of individual factors in drivers’ take-over behavior and performance. The present study sought to examine the extent to which take-over performance can be predicted by individual differences in visuo-attentional and executive abilities. After a period of automated driving on a simulator, participants aged 20 to 60 ( N = 118) had to regain control of their vehicle in a critical take-over situation (i.e., avoiding an obstacle by changing lanes while other vehicles are approaching at higher speeds). The take-over manoeuvre was considered successful if the participants managed to complete it without colliding with the obstacle or another vehicle. All participants completed a battery of cognitive (working memory, inhibitory control, attentional flexibility, and planning) and visuo-attentional tests (visuomanual coordination, multiple object avoidance, and multiple object tracking), and reported their age and driving experience. Several partial least-squares models predicting the success of the manoeuvre from individual abilities were compared. The most accurate model had an accuracy of 70.79% and identified spatial working memory (measured with the CORSI task), visuomanual coordination (one’s ability to manually track a moving target) and driving experience (annual mileage) as key factors for the success of the take-over. Conversely, higher inhibitory control ability, as measured by the Flanker and Stop-Signal tasks, was negatively related to take-over success, possibly because these participants exerted strong cognitive control over the non-driving task during automated driving, which came at the cost of flexibility.

The presence of small urban green spaces, such as streetscape vegetation, plays a significant role in the daily exposure to nature for a considerable proportion of urban inhabitants across the globe. This study examines how specific design elements (vegetal and non-vegetal) of small urban green spaces influence human preferences and their alignment with perceived restorativeness dimensions. In each of the 30 trials, participants selected their preferred option and gave reasons for their choice based on the four aspects of the Attention Restoration Theory (fascination, coherence, being away, compatibility). The results demonstrate that the absence of a fence was the most preferred option, irrespective of the fence type. Shorter fences and fences that include greenery were found to be significantly more favored than other types, primarily due to the factor of fascination. Conversely, attributes such as metal and high fences were selected less frequently, with coherence identified as the primary reason for this preference. The most preferred vegetation type was trees, which were selected primarily due to their capacity to evoke fascination. In contrast, bushes and grass, which were less favored, were chosen for their contribution to coherence. A medium level of diversity was preferred over high or low levels when the arrangement of vegetation was not regular. Furthermore, random and regular arrangements were less favored than an intermediate level of arrangement. With regard to the Attention Restoration Theory dimensions, fascination was the primary motive for all options except for the regular arrangement. These findings could assist designers of small urban green spaces in creating more restorative environments. Additionally, the study illustrates the value of employing virtual environments in environmental preference research.

Cette étude cherche à investiguer un schème trompeur, apparu dans un atelier d’aéronautique, elle cherche également à tester des formes de remédiations possibles. Un schème trompeur est un schème activé par des caractéristiques trompeuses de la situation et qui peut diminuer la performance. Un tel schème avait été identifié chez des opérateurs dans un atelier d’étirage de cadres métalliques. Il se manifestait par l’utilisation des résultats obtenus sur un cadre afin de paramétrer une machine d’étirage pour les cadres suivants. L’étude de ce schème trompeur s’étant révélée difficile dans l’atelier réel, le paradigme du micromonde est utilisé afin d’évaluer deux formes de remédiation : une formation succincte à l’inhibition du schème trompeur et une simulation en temps réel. Le schème trompeur apparaît chez les participants « tout venant » dans l’étude sur le micromonde comme il apparaissait chez les opérateurs de l’atelier. De plus, dans le micromonde, le schème trompeur provoque une diminution des performances. L’outil de simulation en temps réel ne permet pas de faire disparaître le schème trompeur même s’il semble permettre aux utilisateurs d’apprendre à affiner les règles guidant le réglage de la machine-outil. L’article pose ainsi la question de la persistance d’un schème trompeur et de la pertinence de l’utilisation de la simulation en temps réel sans accompagnement pour éviter son utilisation dans une situation où il n’est pas pertinent.

This case study investigated the experience of a military helicopter pilot trainee during formation flight. Formation flight is a technique used in military operations, consisting of maneuvering safely around a Lead helicopter by controlling the rate and direction of motion to avoid collisions. Using the Course-of-Action framework, we described the pilot's cognitive activity during formation-flight maneuvers (join-up patterns) in a practice session from his own perspective to provide insights into his lived experience. Focus was placed on the situational elements that were meaningful to the pilot at a given moment (i.e., Representamen), and how these meaningful situational elements were guided by his situated concerns (i.e., Involvement). Data were collected in two steps: (1) collection of activity traces during formation flight training and (2) self-confrontation interviews using these activity traces in which the pilot was invited to relive his experience and describe his activity. The results indicated five typical representamen and four typical involvements, and revealed eight different associations between these typical representamen and typical involvements over the course of the maneuvers. The discussion addresses how the description of these associations provides a better understanding of the pilot's activity during formation maneuvers and proposes possible extensions of this study.

Shared spaces are urban areas without physical separation between motorised and non-motorised users. Previous research has suggested that it is difficult for users to appropriate these spaces and that the advent of self-driving cars could further complicate interactions. It is therefore important to study the perception of these spaces from the users’ perspectives to determine which conditions may promote their acceptance of the vehicles. This study investigates the perceived collision risk of a self-driving car’s passenger when pedestrians cross the vehicle’s path. The experiment was conducted with a driving simulator. Seven factors were manipulated to vary the dynamics of the crossing situations in order to analyse their influence on the passenger’s perception of collision risk. Two measures of perceived risk were obtained. A continuous subjective assessment, reflecting an explicit risk evaluation, was reported in real time by participants. On the other hand, their skin conductance responses, which reflects implicit information processing, were recorded. The relationship between the factors and the risk perception indicators was studied using Bayesian networks. The best Bayesian networks demonstrate that subjective collision risk assessments are primarily influenced by the factors that determine the relative positions of the vehicle and the pedestrian as well as the distance between them when they are in close proximity. The analysis further reveals that variations in skin conductance response indicators are more likely to be explained by variations in subjective assessments than by variations in the manipulated factors. These findings could benefit the development of self-driving navigation among pedestrians by improving understanding of the factors that influence passengers’ feelings.

Taking a motor planning perspective, this study investigates whether haptic force cues displayed on the steering wheel are more effective than visual cues in signaling the direction of an upcoming lane change. Licensed drivers drove in a fixed-base driving simulator equipped with an active steering system for realistic force feedback. They were instructed to make lane changes upon registering a directional cue. Cues were delivered according to the movement precuing technique employing a pair of precues and imperative cues which could be either visual, haptic, or crossmodal (a visual precue with a haptic imperative cue, and vice versa). The main dependent variable was response time. Additional analyses were conducted on steering wheel angle profiles and the rate of initial steering errors. Conditions with a haptic imperative cue produced considerably faster responses than conditions with a visual imperative cue, irrespective of the precue modality. Valid and invalid precues produced the typical gains and costs, with one exception. There appeared to be little cost in response time or initial steering errors associated with invalid cueing when both cues were haptic. The results are consistent with the hypothesis that imperative haptic cues facilitate action selection while visual stimuli require additional time-consuming cognitive processing.

The objective of this study is to determine the ability of a two-point steering control model to account for the influence of a haptic guidance system in different visibility conditions. For this purpose, the lateral control of the vehicle was characterized in terms of driving performance as well as through the identification of anticipation and compensation parameters of the driver model. The hypothesis is that if the structure of the model is valid in the considered conditions, the value of the parameters will change in coherence with the observed behavior. The results of an experiment conducted on a driving simulator demonstrate that the identified model can account for the cumulative influence of the haptic guidance system and degraded visibility. The anticipatory gain is sensitive to changes in driving conditions that have a direct influence on the produced trajectory, and the compensatory gain is sensitive to a decrease in the variability of the lateral position. However, a model with only the steering wheel angle as output is not able to determine whether the change in lateral position variability is due to the driver’s lack of anticipation or to the assistance provided by the haptic guidance system.

Objective: Multiple sclerosis (MS) is a multifactorial disease with increasingly complicated management. Our objective is to use on‐demand computational power to address the challenges of dynamically managing MS.Methods: A phase 3 clinical trial data (NCT00906399) were used to contextualize the medication efficacy of peg‐interferon beta‐1a vs placebo on patients with relapsing–remitting MS (RRMS). Using a set of reference patients (PORs), selected based on adequate features similar to those of an individual patient, we visualize disease activity by measuring the percentage of relapses, accumulation of new T2 lesions on MRI, and worsening EDSS during the clinical trial.Results: We developed MS Vista, a functional prototype of clinical decision support system (CDSS), with a user‐centered design and distributed infrastructure. MS Vista shows the medication efficacy of peginterferon beta‐1a versus placebo for each individual patient with RRMS. In addition, MS Vista initiated the integration of a longitudinal magnetic resonance imaging (MRI) viewer and interactive dual physician‐patient data display to facilitate communication.Interpretation: The pioneer use of PORs for each individual patient enables personalized analytics sustaining the dialog between neurologists, patients and caregivers with quantified evidence.