Browsing by Author "Ruscio, Daniele"

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    Analysis of autonomic indexes on drivers' workload to assess the effect of visual ADAS on user experience and driving performance in different driving conditions
    (ASME, 2018-06-12) Ariansyah, Dedy; Caruso, Giandomenico; Ruscio, Daniele; Bordegoni, Monica
    Advanced driver assistance systems (ADASs) allow information provision through visual, auditory, and haptic signals to achieve multidimensional goals of mobility. However, processing information from ADAS requires operating expenses of mental workload that drivers incur from their limited attentional resources. The change in driving condition can modulate drivers' workload and potentially impair drivers' interaction with ADAS. This paper shows how the measure of cardiac activity (heart rate and the indexes of autonomic nervous system (ANS)) could discriminate the influence of different driving conditions on drivers' workload associated with attentional resources engaged while driving with ADAS. Fourteen drivers performed a car-following task with visual ADAS in a simulated driving. Drivers' workload was manipulated in two driving conditions: one in monotonous condition (constant speed) and another in more active condition (variable speed). Results showed that drivers' workload was similarly affected, but the amount of attentional resources allocation was slightly distinct between both conditions. The analysis of main effect of time demonstrated that drivers' workload increased over time without the alterations in autonomic indexes regardless of driving condition. However, the main effect of driving condition produced a higher level of sympathetic activation on variable speed driving compared to driving with constant speed. Variable speed driving requires more adjustment of steering wheel movement (SWM) to maintain lane-keeping performance, which led to higher level of task involvement and increased task engagement. The proposed measures appear promising to help designing new adaptive working modalities for ADAS on the account of variation in driving condition.
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    Charting the edges of human performance
    (EDP Sciences, 2019-12-17) Kirwan, Barry; Wies, Matthias; Charles, Rebecca; Dormoy, Charles-Alban; Letouze, Theodore; Lemkadden, Alia; Maille, Nicolas; Nixon, Jim; Ruscio, Daniele; Schmidt-Moll, Carsten
    In the Horizon 2020 funded Future Sky Safety programme, the Human Performance Envelope project pushed airline pilots to the edges of their performance in real-time cockpit simulations, by increasing stress and workload, and decreasing situation awareness. The aim was to find out how such factors interact, and to detect the edges of human performance where some form of automation support should be employed to ensure safe continued flight. A battery of measures was used, from behavioural to physiological (e.g. heart rate, eye tracking and pupil dilation), to monitoring pilot performance in real time. Several measures – e.g. heart rate, heart rate variability, eye tracking, cognitive walkthrough, and Human Machine Interface (HMI) usability analysis – proved to be useful and relatively robust in detecting performance degradation, and determining where changes in information presentation are required to better support pilot performance in challenging situations. These results led to proposed changes in a prototype future cockpit human-machine interface, which were subsequently validated in a final simulation. The results also informed the development of a ‘Smart-Vest’ that can be worn by pilots to monitor a range of signals linked to performance.