From partial and high automation to manual driving: Relationship between non-driving related tasks, drowsiness and take-over performance.

BACKGROUND: Until the level of full vehicle automation is reached, users of vehicle automation systems will be required to take over manual control of the vehicle occasionally and stay fallback-ready to some extent during the drive. Both, drowsiness caused by inactivity and the engagement in distracting non-driving related tasks (NDRTs) such as entertainment or office work have been suggested to impair the driver's ability to safely handle these transitions of control. Thus, it is an open question whether engagement in NDRTs will impair or improve take-over performance. METHOD: In a motion-based driving simulator, 64 participants completed an automated drive that lasted either one or two hours using either a partially or highly automated driving system. In the partially automated driving condition, a warning was issued after several seconds when drivers took both hands off the steering wheel, while the highly automated driving system allowed hands-off driving permanently. Drivers were allowed to bring along their smartphones and to use them during the drive. They engaged in a wide variety of NDRTs such as reading or using social media. At the end of the session, drivers had to react to a sudden lead vehicle braking event. In the partial automation condition, there was no take-over request (TOR) to notify the drivers of the braking vehicle, while in the highly automated condition, the situation happened right after the drivers had deactivated the automation in response to a TOR. The lead time of the TOR was set at 8 s. Driver's level of drowsiness, workload (visual, mental and motoric) from carrying out the NDRT and motivational appeal of the NDRT right before the control transition were video-coded and used to predict the outcome of the braking event (i.e., reaction and system deactivation times, minimal Time-to-collision (TTC) and self-reported criticality) with a multiple regression approach. RESULTS: In the partial automation condition, reaction times to the braking vehicle and situation criticality as measured by the minimum TTC could be well predicted. Main predictors for increased reaction time were drowsiness and motivational appeal of the NDRT. However, visual and mental demand associated with NDRTs did decrease reaction time, suggesting that the NDRT helped the drivers to maintain alertness during the partially automated drive. Accordingly, drowsiness and motivational appeal of the NDRT increased situation criticality, while cognitive load due to the NDRT decreased it. In the highly automated condition, however, it was not possible to predict system deactivation time (in reaction to the TOR), brake reaction time to the braking vehicle and situation criticality by observed drowsiness and NDRT engagement. DISCUSSION: The results suggest a relationship between the driver's drowsiness and NDRT engagement in partial automation but not in highly automated driving. Several explanations for this finding are discussed. It could be possible that the lead time of 8 s might have given the drivers enough time to complete the driver state transition process from executing NDRTs to manual driving, putting them in a position to be able to cope with the driving event, while this was not possible in the partial automation condition. Methodological issues that might have led to a non-detection of an effect of drowsiness or NDRT engagement in the highly automated driving condition, such as the sample size and sensitivity of the observer ratings, are also discussed.

A literature review on the levels of automation during the years. What are the different taxonomies that have been proposed?

In this paper we present a literature review of the evolution of the levels of autonomy from the end of the 1950s up until now. The motivation of this study was primarily to gather and to compare the literature that exists, on taxonomies on levels of automation. Technical developments within both computer hardware and software have made it possible to introduce autonomy into virtually all aspects of human-machine systems. The current study, is focusing on how different authors treat the problem of different levels of automation. The outcome of this study is to present the differences between the proposed levels of automation and the various taxonomies, giving the potential users a number of choices in order to decide which taxonomy satisfies their needs better. In addition, this paper surveys deals with the term adaptive automation, which seems to be a new trend in the literature on autonomy.

[Automation in surgery: a systematical approach]. / Automation in der HNO-Chirurgie.

Surgical assistance systems permit a misalignment from the purely manual to an assisted activity of the surgeon (automation). Automation defines a system, that partly or totally fulfils function, those was carried out before totally or partly by the user. The organization of surgical assistance systems following application (planning, simulation, intraoperative navigation and visualization) or technical configuration of the system (manipulator, robot) is not suitable for a description of the interaction between user (surgeon) and the system. The available work has the goal of providing a classification for the degree of the automation of surgical interventions and describing by examples. The presented classification orients itself at pre-working from the Human-Factors-Sciences. As a condition for an automation of a surgical intervention applies that an assumption of a task, which was alone assigned so far to the surgeon takes place via the system. For both reference objects (humans and machine) the condition passively or actively comes into consideration. Besides can be classified according to which functions are taken over during a selected function division by humans and/or the surgical assistance system. Three functional areas were differentiated: "information acquisition and -analysis", "decision making and action planning" as well as "execution of the surgical action". From this results a classification of pre- and intraoperative surgical assist systems in six categories, which represent different automation degrees. The classification pattern is described and illustrated on the basis of surgical of examples.

La expansión del rol de la robótica en el laboratorio clínico / The spansion of roll of the robotic in the clinic laboratory

Un número creciente de robots serán empleados en laboratorios químicos industriales. Muchos de ellos serán usados para reducir las tareas monótonas de preparación de muestras, para minimizar la exposición humana a entornos riesgosos o para realizar gran número de procedimientos experimentales repetitivos. Por ejemplo, buscar la condición más efectiva o sus combinaciones en síntesis química o el mejor microorganismo en un gran número de cultivos. En el laboratorio clínico la situación es ligeramente diferente y la robótica no es tan ampliamente aplicada, pero hay una tendencia definida para emplear robots o sistemas robóticos, tanto como para reducir el volumen de trabajo y la exposición del personal a posibles biopeligros y para ayudar a obtener resultados más precisos y correctos. Estas necesidades son difíciles de llenar a través delos dispositivos automáticos usuales y especialmente cuando no estan disponibles dispositivos adecuados. Aparatos especialmente diseñados deberán ser producidos para satisfacer estas demandas y la robótica jugará una parte. Finalmente necesitamos evaluar la efectividad de la introducción de la robótica en términos de economía, estrategia, bioseguridad y otros aspectos. ejemplos típicos de implementación de la robótica en el laboratorio clínico son el transporte de especímenes, la automatización de la preparación de muestras, separación, fraccionamiento en al cuotas, así como procesos seleccionados en sistemas automatizados en gran escala. Como se describió previamente, los robots que están comercialmente disponibles actualmente, no son suficientemente inteligentes para ser fácilmente manejados por personal no entrenado en robótica. Hay una necesidad de personal dedicado a robótica que se incorpore al proyecto desde el principio del plan y que pueda mantener el sistema adecuadamente. Nosotros predecimos que esta situación permanecerá de esta forma por un tiempo considerable en el futuro. Los sistemas robots o mecanismos serán gradualmente introducidos en los laboratorios clínicos. La robótica será una de las mejores formas para mantener la bioseguridad en el entorno del laboratorio clínico y en el futuro se necesitarán laboratorios más automatizados con menos personal. Una vez más nosotros queremos enfatizar que se debe establecer una interfase estandarizada y un protocolo para la comunicación entre robots, computadoras e instrumentos, antes de que la robótica sea ampliamente empleada