Duurzaamheid en comfort, van ontwerp naar praktijk

Praktijkevaluatie van duurzame kantoren waarbij de relatie tussen het ontwerpproces en de prestatie in de praktijk wordt onderzocht.InstallatiesBuilding TechnologyArchitectur

Relationship between motor vehicle collisions and results of perimetry, useful field of view, and driving simulation in drivers with glaucoma

Purpose: To examine the relationship between Motor Vehicle Collisions (MVCs) indrivers with glaucoma and standard automated perimetry (SAP), Useful Field of View(UFOV), and driving simulator assessment of divided attention.Methods: A cross-sectional study of 153 drivers from the Diagnostic Innovations inGlaucoma Study. All subjects had SAP and divided attention was assessed using UFOVand driving simulation using low-, medium-, and high-contrast peripheral stimulipresented during curve negotiation and car following tasks. Self-reported history ofMVCs and average mileage driven were recorded.Results: Eighteen of 153 subjects (11.8%) reported a MVC. There was no difference invisual acuity but the MVC group was older, drove fewer miles, and had worsebinocular SAP sensitivity, contrast sensitivity, and ability to divide attention (UFOV anddriving simulation). Low contrast driving simulator tasks were the best discriminatorsof MVC (AUC 0.80 for curve negotiation versus 0.69 for binocular SAP and 0.59 forUFOV). Adjusting for confounding factors, longer reaction times to driving simulatordivided attention tasks provided additional value compared with SAP and UFOV, witha 1 standard deviation (SD) increase in reaction time (approximately 0.75 s) associatedwith almost two-fold increased odds of MVC.Conclusions: Reaction times to low contrast divided attention tasks during drivingsimulation were significantly associated with history of MVC, performing better thanconventional perimetric tests and UFOV.Translational Relevance: The association between conventional tests of visualfunction and MVCs in drivers with glaucoma is weak, however, tests of dividedattention, particularly using driving simulation, may improve risk assessment.Biomechatronics & Human-Machine Contro

A risk field-based metric correlates with driver's perceived risk in manual and automated driving: A test-track study

Quantifying drivers’ perceived risk is important in the design and evaluation of the behaviour of automated vehicles (AVs) and in predicting takeovers by the driver. A ‘Driver's Risk Field’ (DRF) function has been previously shown to be able to predict manual driving behaviour in several simulated scenarios. In this paper, we tested if the DRF-based risk estimate (rˆ) could predict manual driving behaviour and the driver's perceived risk during automated driving. To ensure that the participants perceived realistic levels of risk, the experiment was conducted in a test vehicle. Eight participants drove five laps manually and experienced 12 different laps of automated driving on a test track. The test track consisted of three sections (which were sub-divided into 12 sectors): curve driving (9 sectors), parked car (1 sector), and 90-degree intersections (2 sectors). If the driver verbally expressed risk or performed a takeover, that particular sector was labelled as risky. The results show that the DRF risk estimate (rˆ) predicted manual driving behaviour (ρsteering=0.69, ρspeed=0.64), as well as correlated with the driver's perceived risk in curve driving (r2 = 0.98) and while negotiating a car parked outside the lane boundary (r2=0.59). In conclusion, the DRF-based risk estimate (rˆ) is predictive of manual driving behaviour and perceived risk in automated driving. Future research should include tactical and strategic components to the driving task.Human-Robot Interactio

Does the Projected-Hand-Illusion Help in Teleoperation?

A body illusion, commonly known in the form of the “Rubber Hand Illusion”, is an illusion wherein visual inputs on an inanimate object and simultaneous tactile inputs on a part of the body lead to a situation where the inanimate object is identified as the body part. This study investigated the possibility of inducing a body illusion during a teleoperated reaching task, to see if this leads to increased telepresence and improved accuracy. Three conditions were presented in random order; the Direct Control (DC) condition, where the participant’s hand is shown on the screen, the Projected Hand Illusion (PHI) condition, showing the slave device consisting of a 3D-printed hand designed to induce a body illusion, and the no Projected Hand Illusion (nPHI) condition, showing the slave device consisting of a 3D-printed object of appropriate shape but designed to not induce a body illusion. Reaching performance was interpreted in terms of position error, for which a significant difference was found between conditions PHI and nPHI. In the nPHI condition, participants kept more distance to the obstacle than in the PHI condition. Potential causes for this difference are an increased perception of risk due to a difference in visual perception, or subtle visual differences in between the two conditions.Control & SimulationHuman-Robot InteractionControl & Operation

Constraint-based decision support for multi-objective arrival traffic planning

Aerospace Engineerin

What determines drivers’ speed?: A replication of three behavioural adaptation experiments in a single driving simulator study

We conceptually replicated three highly cited experiments on speed adaptation, by measuring drivers’ experienced risk (galvanic skin response; GSR), experienced task difficulty (self-reported task effort; SRTE), and safety margins (time-to-line-crossing; TLC) in a single experiment. The three measures were compared using a nonparametric index that captures the criteria of constancy during self-paced driving and sensitivity during forced-paced driving. In a driving simulator, 24 participants completed two forced-paced and one self-paced run. Each run held four different lane width conditions. Results showed that participants drove faster on wider lanes, thus confirming the expected speed adaptation. None of the three measures offered persuasive evidence for speed adaptation because they failed either the sensitivity criterion (GSR) or the constancy criterion (TLC, SRTE). An additional measure, steering reversal rate, outperformed the other three measures regarding sensitivity and constancy, prompting a further evaluation of the role of control activity in speed adaptation.Human-Robot InteractionControl & SimulationBiomechatronics & Human-Machine Contro

A topology of shared control systems: Finding common ground in diversity

Shared control is an increasingly popular approach to facilitate control and communication between humans and intelligent machines. However, there is little consensus in guidelines for design and evaluation of shared control, or even in a definition of what constitutes shared control. This lack of consensus complicates cross fertilization of shared control research between different application domains. This paper provides a definition for shared control in context with previous definitions, and a set of general axioms for design and evaluation of shared control solutions. The utility of the definition and axioms are demonstrated by applying them to four application domains: automotive, robot-assisted surgery, brain–machine interfaces, and learning. Literature is discussed for each of these four domains in light of the proposed definition and axioms. Finally, to facilitate design choices for other applications, we propose a hierarchical framework for shared control that links the shared control literature with traded control, co-operative control, and other human–automation interaction methods. Future work should reveal the generalizability and utility of the proposed shared control framework in designing useful, safe, and comfortable interaction between humans and intelligent machines.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Human-Robot InteractionBiomechatronics & Human-Machine Contro

System provided with an assistance-controller for assisting an operator of the system, control-operation assisting device, control-operation assisting method, driving-operation assisting device, and driving-operation assisting method

A target-travel-path generating circuit calculates a target travel path along which the controlled object can travel in the future from the current controlled object position, an ideal-control-signal calculating circuit calculates a control profile S to travel along the target travel path P, and a difference calculating circuit calculates a difference d between the ideal control magnitude S and a current control magnitude S. An operation system assistance controller controls the operation system based on the magnitude of the calculated difference d to assist the control operation of the operator, the control-operation-state of the operator, the environment-state, and the required operation-precision. Accordingly, it is possible to provide the operator with control operation assistance that is a function of the magnitude of the difference d from an ideal control state, the control-operation-state of the operator, the environment-state, and the required operation-precision, and thus, a control-operation assistance control can be outputted that is suitable for the conditions that characterize the state of the operator, the environment, and the controlled object.Biomechanical EngineeringMechanical, Maritime and Materials Engineerin

Manual control cybernetics: State-of-the-art and current trends

Manual control cybernetics aims to understand and describe how humans control vehicles and devices using mathematical models of human control dynamics. This “cybernetic approach” enables objective and quantitative comparisons of human behavior, and allows a systematic optimization of human control interfaces and training associated with manual control. Current cybernetics theory is primarily based on technology and analysis methods formalized in the 1960s and has shown to be limited in its capability to capture the full breadth of human cognition and control. This paper reviews the current state-of-the-art in our knowledge of human manual control, points out the main fundamental limitations in cybernetics, and proposes a possible roadmap to advance the theory and its applications. Central in this roadmap will be a shift from the current linear time-invariant modeling approach that is only truly valid for human behavior under tightly controlled and stationary conditions, to methods that facilitate the analysis of adaptive, and possibly time-varying, human behavior in realistic control tasks. Examples of key current developments in the field of cybernetics—human use of preview, predictable discrete maneuvering, skill acquisition and training, time-varying human modeling, and neuromuscular system modeling—that contribute to this shift are presented in this paper. The new foundations for cybernetics that will emerge from these efforts will impact all domains that involve humans in manual and semiautomatic control.Control & OperationsControl & SimulationHuman-Robot Interactio