An interest in developing the intelligent machine system that works in conjunction with human has been growing rapidly in recent years. A number of studies were conducted to shed light on how to design an interactive, adaptive and assistive machine system to serve a wide range of purposes including commonly seen ones like training, manufacturing and rehabilitation. In the year 2003, Human Adaptive Mechatronics (HAM) was proposed to resolve these issues. According to past research, the focus is predominantly on evaluation of human skill rather than human performance and that is the reason why intensive training and selection of suitable human subjects for those experiments were required. As a result, the pattern and state of control motion are of critical concern for these works. In this research, a focus on human skill is shifted to human performance instead due to its proneness to negligence and lack of reflection on actual work quality. Human performance or Human Performance Index (HPI) is defined to consist of speed and accuracy characteristics according to a well-renowned speed-accuracy trade-off or Fitts' Law. Speed and accuracy characteristics are collectively referred to as speed and accuracy criteria with corresponding contributors referred to as speed and accuracy variables respectively. This research aims at proving a validity of the HPI concept for the systems with different architecture or the one with and without hardware elements. A direct use of system output logged from the operating field is considered the main method of HPI computation, which is referred to as a non-model approach in this thesis. To ensure the validity of these results, they are compared against a model-based approach based on System Identification theory. Its name is due to being involved with a derivation of mathematical equation for human operator and extraction of performance variables. Certain steps are required to match the processing outlined in that of non-model approach. Some human operators with complicated output patterns are inaccurately derived and explained by the ARX models.

A helicopter can be used to transport a load hanging from a suspension cable. This technique is frequently used in construction, firefighting, and disaster relief operations, among other applications. Unfortunately, the suspended load swings, which makes load positioning difficult and can degrade control of the helicopter. This dissertation investigates the use of input shaping (a command-filtering technique for reducing vibration) to mitigate the load swing problem. The investigation is conducted using two different, but complementary, approaches. One approach studies manual tracking tasks, where a human attempts to make a cursor follow an unpredictably moving target. The second approach studies horizontal repositioning maneuvers on small-scale helicopter systems, including a novel testbed that limits the helicopter and suspended load to move in a vertical plane. Both approaches are used to study how input shaping affects control of a flexible element (the suspended load) and a driven base (the helicopter). In manual tracking experiments, conventional input shapers somewhat degraded control of the driven base but greatly improved control of the flexible element. New input shapers were designed to improve load control without negatively affecting base control. A method for adjusting the vibration-limiting aggressiveness of any input shaper between unshaped and fully shaped was also developed. Next, horizontal repositioning maneuvers were performed on the helicopter testbed using a human-pilot-like feedback controller from the literature, with parameter values scaled to match the fast dynamics of the model helicopter. It was found that some input shapers reduced settling time and peak load swing when applied to Attitude Command or Translational Rate Command response types. When the load was used as a position reference instead of the helicopter, the system was unstable without input shaping, and adding input shaping to a Translational Rate Command was able to stabilize the load-positioning system. These results show the potential to improve the safety and efficiency of helicopter suspended load operations.

Des voitures complètement automatisées pourraient circuler sur les routes dans les décennies à venir. Elles permettraient aux automobilistes d’être conduits dans leur véhicule par un système informatique. Une telle innovation pourrait engendrer une révolution qui affecterait le rôle du conducteur et ses activités pendant le trajet. Actuellement, ces véhicules ne sont pas encore accessibles au grand public, et il demeure difficile de prédire précisément quand cela se produira, et quelles seront leurs caractéristiques techniques finales. Dans ce contexte, un des objectifs de cette thèse a été d’étudier dans quelle mesure la conduite complètement automatisée sera acceptée. Bien que l’automobiliste soit conduit par son véhicule, il pourrait être amené à en reprendre le contrôle manuel dans différentes circonstances. En effet, cette manœuvre pourrait être effectuée en situation d’urgence ou de manière anticipée par le conducteur alors qu’il pourrait être engagé dans une autre activité que la conduite. La réalisation de cette reprise de contrôle manuel pourrait être plus ou moins difficile selon la situation et l’expérience d’interactions avec le système complètement automatisé. Nous avons examiné la manière dont cette manœuvre pourrait être apprise par des conducteurs, en testant l’effet de différentes formes d’entrainement sur la performance et la sécurité (temps de réponse et qualité de la reprise de contrôle). L’acceptabilité et la confiance, les attitudes des conducteurs, les intentions d’utilisation du système de conduite complètement automatisée et l’impact de ces variables sur les comportements dans le véhicule ont été mesurés. / Fully automated cars could possibly be on the road in the decades to come. They will allow drivers to be driven by an informatics system in their own vehicle. Such an innovation could lead to a revolution that would change the driver’s status and its activities during the trips, but also the infrastructure, freight, some professions, etc. Nowadays, these vehicles are not available for sale yet, and it is difficult to forecast accurately when they will be, and also what their features will be. Considering this, one of the aims of the present thesis is to examine to what extend fully automated driving will be accepted. Even though the driver is driven by its vehicle, he could have to resume manual control in different circumstances. Indeed, this maneuver could be performed in an emergency or in an anticipated situation while he could be engaged in a non driving-related activity. Performing a manual control recovery could be more or less difficult according to the situation and the experience with the fully automated system. The way this maneuver could be learned by drivers has been examined, testing the impact of different kinds of training on performance and safety (response time and control recovery quality). Acceptability, trust, drivers’ attitudes, intentions to use the fully automated driving system and the impact of these variables on behaviors inside the vehicle have been assessed.

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