The manufacturing industry is shifting, entering a new era with smart and connected devices. The fourth industrial revolution (Industry 4.0) is promising increased growth and productivity by the Smart Factory and within the enabling technologies is Augmented Reality (AR). This is a technology that can be used to augment the reality with digital information. At the same time as the technology is introduced, errors in manufacturing are a problem which are affecting the productivity and the quality. The errors can be caused by humans and companies strive to eliminate the errors caused by humans. This research aims to find the main causes of human errors in assembly lines and thereafter explores whether AR is an appropriate tool to be used in order to address those issues. Based on a literature review that identified and characterized a preliminary set of root causes for human errors in assembly lines, these causes were empirically studied in an exercise that covered an in-depth case study at a multinational automotive company. Data in form of interviews and deviation reports have been used to identify the causing factors and the result showed that the main causes of human errors are the amount of thinking, deciding and searching for information which affected the cognitive load of the operator and in result their performance. Several interviews with experts in AR allowed to verify if this technology would be feasible to solve or mitigate the found causes. Besides that, in repetitive manual assembly operations, AR is better used showing the process in order to train new operators, at the same time as for experienced operators AR show information only when an error occurs and when there is a need of taking an active choice is more appropriate. Nevertheless, while theoretically able to managing human error when fully developed, the desired application makes the augmentation of visual objects redundant and increasingly complex for solving the identified causes of errors which questions the appropriateness of using AR systems. However, the empirical findings showed that for managing human errors, the main bottleneck of an AR system is the software and AI. / Den tillverkande industrin skiftar och går in i en ny era där smart och uppkopplad teknologi introduceras i de operativa delarna av tillverkningen. Denna fjärde industriella revolution (Industry 4.0) som den även kallas för med smarta fabriker, utlovar ökad produktivitet och tillväxt. Bland de teknologier som representeras i detta nya landskap återfinns Augmented Reality (AR), vilket är en teknik som används för att förstärka verkligheten med digital information. I samband med att denna nya teknik introduceras, är avvikelser i produktion ett problem som påverkar företags produktivitet och kvalitet. Den mänskliga faktorn är en bidragande del till detta problem och företag strävar efter att eliminera felen orsakade av människor. Denna studie syftar till att hitta orsakerna till att människor orsakar fel i produktion och därefter utforska om AR är ett lämpligt verktyg att använda för att råda bot på dessa orsaker och därmed eliminera felen. Genom en litteraturstudie har det identifierats ett antal faktorer som påverkar den mentala belastningen hos människor i produktionssammanhang. Dessa faktorer har därefter undersökts genom en fallstudie hos en multinationell tillverkare av kommersiella fordon. Datainsamling i form av intervjuer och avvikelsedata har använts för att identifiera de påverkande faktorerna och resultaten pekade på att behovet av att behöva tänka, leta efter information och fatta beslut påverkade den mentala belastningen mest. Intervjuer hölls med forskare och montörer för att definiera en lämplig AR funktion som sedan undersöktes genom flera intervjuer med forskare inom AR för att verifiera om AR är en lämplig teknik att använda för de identifierade orsakerna. I termer av AR i en arbetsmiljö med repetitiva aktiviteter efterfrågas en funktion som visualiserar fel för montörer som är erfarna medan det för oerfarna montörer är bättre med visualisering av hela arbetsprocessen. Men, trots att systemet i teorin är lämpligt att använda för att hantera orsakerna till att felen uppstår så är den efterfrågade funktionen överflödig då visualisering kommer visas väldigt sällan samt att tekniken är väldigt komplex. Detta gör att det går att ifrågasätta hela funktionen av att använda AR system i det fall som studerades. Dessutom visade sig tekniken vara olämplig att använda i den miljö fallet utspelar sig i på grund av svårigheter med artificiell intelligens (AI).

The usage of autonomous vehicles is starting to appear in several different domains and the domain of public safety is no exception. Wallenberg Artificial Intelligence, Autonomous Systems and Software Program (WASP) has created a research arena for public safety (WARA-PS) to explore experimental features, usages, and implementation of autonomous vehicles within the domain of public safety. Collaborating in the arena are several companies, universities, and researchers. This thesis examines, in collaboration with Combitech, a company partnered in WARA-PS, how the implementation of autonomous vehicles affects the sociotechnical system of a search and rescue operation during a drifting boat with potential castaways. This is done by creating a case together with domain experts, analyzing the sociotechnical system within the case using cognitive work analysis and then complementing the analyses with the unmanned autonomous vehicles of WARA-PS. This thesis has shown how the WARA-PS vehicles can be implemented in the case of a drifting boat with potential castaways and how the implementation affects the sociotechnical system. Based on the analyses and opinions of domain experts’ future guidelines has been derived to further the work with sociotechnical aspects in WARA-PS. / WARA-PS

Face à l’évolution rapide des technologies nécessaires à l’automatisation de la conduite au cours de ces dernières années, les grands constructeurs automobiles promettent la commercialisation de véhicules autonomes à l’horizon 2020. Cependant, la définition des interactions entre les systèmes de conduite automatisée et le conducteur au cours de la tâche de conduite reste une question ouverte. L'objectif de cette thèse est de concevoir, développer et évaluer des principes de coopération entre le conducteur et les systèmes de conduite automatisée. Compte tenu de la complexité d'un tel Système Homme-Machine, la thèse propose, en premier lieu une architecture de contrôle coopératif hiérarchique et deux principes de coopération généraux sur deux niveaux dans l’architecture qui serviront ensuite de base commune pour la conception des systèmes coopératifs développés pour les cas d’usages définis. Afin d’assurer une coopération efficace avec le conducteur dans un environnement de conduite dynamique, le véhicule autonome a besoin de comprendre la situation et de partager sa compréhension de la situation avec le conducteur. Pour cela, cette thèse propose un formalisme de représentation de la scène de conduite basé sur le repère de Frenet. Ensuite, une méthode de prédiction de trajectoire est également proposée. Sur la base de la détection de manœuvre et de l'estimation du jerk, cette méthode permet d’améliorer la précision de la trajectoire prédite comparée à celle déterminée par la méthode basée sur une hypothèse d'accélération constante. Dans la partie d’études de cas, deux principes de coopération sont mis en œuvre dans deux cas d’usage. Dans le premier cas de la gestion d’insertion sur autoroute, un système de contrôle longitudinal coopératif est conçu. Il comporte une fonction de planification de manœuvre et de génération de trajectoire basée sur la commande prédictive. En fonction du principe de coopération, ce système peut à la fois gérer automatiquement l’insertion d’un véhicule et donner la possibilité au conducteur de changer la décision du système. Dans le second cas d'usage qui concerne le contrôle de trajectoire et le changement de voie sur autoroute, le problème de partage du contrôle est formulé comme un problème d’optimisation sous contraintes qui est résolu en ligne en utilisant l’approche de la commande prédictive (MPC). Cette approche assure le transfert continu de l’autorité du contrôle entre le système et le conducteur en adaptant les pondérations dans la fonction de coût et en mettant en œuvre des contraintes dynamiques en ligne dans le modèle prédictif, tout en informant le conducteur des dangers potentiels grâce au retour haptique sur le volant. Les deux systèmes sont évalués à l’aide de tests utilisateur sur simulateur de conduite. En fonction des résultats des tests, cette thèse discute la question des facteurs humains et la perception de l'utilisateur sur les principes de coopération. / Given rapid advancement of automated driving (AD) technologies in recent years, major car makers promise the commercialization of AD vehicles within one decade from now. However, how the automation should interact with human drivers remains an open question. The objective of this thesis is to design, develop and evaluate interaction principles for AD systems that can cooperate with a human driver. Considering the complexity of such a human-machine system, this thesis begins with proposing two general cooperation principles and a hierarchical cooperative control architecture to lay a common basis for interaction and system design in the defined use cases. Since the proposed principles address a dynamic driving environment involving manually driven vehicles, the AD vehicle needs to understand it and to share its situational awareness with the driver for efficient cooperation. This thesis first proposes a representation formalism of the driving scene in the Frenet frame to facilitate the creation of the spatial awareness of the AD system. An adaptive vehicle longitudinal trajectory prediction method is also presented. Based on maneuver detection and jerk estimation, this method yields better prediction accuracy than the method based on constant acceleration assumption. As case studies, this thesis implements two cooperation principles for two use cases respectively. In the first use case of highway merging management, this thesis proposes a cooperative longitudinal control framework featuring an ad-hoc maneuver planning function and a model predictive control (MPC) based trajectory generation for transient maneuvers. This framework can automatically handle a merging vehicle, and at the mean time it offers the driver a possibility to change the intention of the system. In another use case concerning highway lane positioning and lane changing, a shared steering control problem is formulated in MPC framework. By adapting the weight on the stage cost and implementing dynamic constraints online, the MPC ensures seamless control transfer between the system and the driver while conveying potential hazards through haptic feedback. Both of the designed systems are evaluated through user tests on driving simulator. Finally, human factors issue and user’s perception on these new interaction paradigms are discussed.

This contributed book contains the short papers presented at the 1st International Conference on Hybrid Societies 2023. Organized by the DFG-funded Collaborative Research Centre 'Hybrid Societies' at Chemnitz University of Technology.:Flourishing from, for, and with Social Machines: Considering the Eudaimonics of Hybrid Societies - Banks J. How do vehicle size, speed, TTC, age and sex affect cyclists’ gap acceptance when interacting with (automated) vehicles? - Springer-Teumer S., Trommler D., Krems J.F. Assessing Driver Uncertainty Respecting Response Actions in Lane Change Maneuvers - Yan F., Eilers M., Baumann M. Using Functionally Anthropomorphic Eyes to Indicate Robotic Motion - Schweidler P. & Onnasch L. Living Labs as Third Spaces: Low-threshold participation, empowering hospitality, and the social infrastructures of continuous presence - Pentzold C., Rothe I., Bischof A. Artificial Morality - Armbruster D., Mandl S., Strobel A. Reducing Prejudice via Virtual Reality: A Meta-Analysis of Experimental Evidence - Stein J.-P., Gnambs T., Appel M. Policy Learning with Spiking Neural Network for Robot Manipulation Tasks - Abdelaal O. M. & Röhrbein F. / Dieser Konferenzband enthält die Kurzbeiträge, die auf der 1st International Conference on Hybrid Societies 2023 vorgestellt wurden. Veranstaltet vom DFG-geförderten Sonderforschungsbereich 'Hybrid Societies' der Technischen Universität Chemnitz.:Flourishing from, for, and with Social Machines: Considering the Eudaimonics of Hybrid Societies - Banks J. How do vehicle size, speed, TTC, age and sex affect cyclists’ gap acceptance when interacting with (automated) vehicles? - Springer-Teumer S., Trommler D., Krems J.F. Assessing Driver Uncertainty Respecting Response Actions in Lane Change Maneuvers - Yan F., Eilers M., Baumann M. Using Functionally Anthropomorphic Eyes to Indicate Robotic Motion - Schweidler P. & Onnasch L. Living Labs as Third Spaces: Low-threshold participation, empowering hospitality, and the social infrastructures of continuous presence - Pentzold C., Rothe I., Bischof A. Artificial Morality - Armbruster D., Mandl S., Strobel A. Reducing Prejudice via Virtual Reality: A Meta-Analysis of Experimental Evidence - Stein J.-P., Gnambs T., Appel M. Policy Learning with Spiking Neural Network for Robot Manipulation Tasks - Abdelaal O. M. & Röhrbein F.

An ergonomically designed work environment may decrease work related musculoskeletal disorders, lead to less sick leaves and increase production time for operators and companies all around the world. Volvo Construction Equipment wants to deepen the knowledge and investigate more carefully how operators are actually sitting whilst operating the machines, how this affects placement of controls and furthermore optimize controls placements accordingly. The purpose is to enhance their product development process by suggesting guidelines for control placement with improved ergonomics based on operators’ sitting postures. The goal is to deliver a process which identifies and transfers sitting postures to RAMSIS and uses them for control placement recommendations in the cab and operator environments. Delimitations concerns: physical ergonomics, 80% usability of the resulted process on the machine types, and the level of detail for controls and their placements. Research, analysis, interviews, test driving of machines, video recordings of operators and the ergonomic software RAMSIS has served as base for analysis. The analysis led to (i) the conclusion that sitting postures affect optimal ergonomic placement of controls, though not ISO-standards, (ii) the conclusion that RAMSIS heavy truck postures does not seem to correspond to Volvo CE’s operators’ sitting postures and (iii) and to an advanced engineering project process suitable for all machine types and applicable in the product development process. The result can also be used for other machines than construction equipment. The resulted process consists of three independent sub-processes with step by step explanations and recommendations of; (i) what information that needs to be gathered, (ii) how to identify and transfer sitting postures into RAMSIS, (iii) how to use RAMSIS to create e design aid for recommended control placement. The thesis also contains additional enhancements to Volvo CE’s product development process with focus on ergonomics. A conclusion is that the use of motion capture could not be verified to work for Volvo Construction Equipment, though it was verified that if motion capture works, the process works. Another conclusion is that the suggested body landmarks not could be verified that they are all needed for this purpose except for those needed for control placement. Though they are based on previous sitting posture identification in vehicles and only those that also occur in RAMSIS are recommended, and therefore they can be used. This thesis also questions the most important parameters for interior vehicle design (hip- and eye locations) and suggests that shoulder locations are just as important. The thesis concluded five parameters for control categorization, and added seven categories in addition to those mentioned in the ISO-standards. Other contradictions and loopholes in the ISO-standards were identified, highlighted and discussed. Suggestions for improving the ergonomic analyses in RAMSIS can also be found in this report. More future research mentioned is more details on control placement as well as research regarding sitting postures are suggested. If the resulted process is delimited to concern upper body postures, other methods for posture identification may be used.