Andreas Lüdtke

Modeling Pilot and Driver Behavior for Human Error Simulation

In order to reduce human errors in the interaction with in safety critical assistance systems it is crucial to consequently include the characteristics of the human operator already in the early phases of the design process. In this paper we present a cognitive architecture for simulating man-machine interaction in the aeronautics and automotive domain. Though both domains have their own characteristics we think that it is possible to apply the same core architecture to support pilot as well driver centered design of assistance systems. This text shows how phenomena relevant in the automobile or aviation environment can be integrated in the same cognitive architecture.

Simulating Perceptive Processes of Pilots to Support System Design

In this paper we present an approach towards supporting the ergonomic design of aircraft cockpits by predicting the probability that pilots might miss relevant information due to routine learning effects combined with non-adequate placement of display instruments. The approach is based on an executable cognitive pilot model. We focus on the cognitive interaction between (1) rule-based processing of flight procedures, (2) the pilots mental model of the current situation and (3) pilots attention. The cognitive model is coupled with a formal cockpit design to simulate human-machine interaction during flight procedures. As an example we analyze the perception of automatic flight mode changes.

Wege aus der Ironie in Richtung ernsthafter Automatisierung

Automatisierung wurde in der Vergangenheit und wird auch heute noch oft unter der Annahme betrieben, dass der Mensch das schwachste Glied der Kette ist und dass er deshalb nach und nach vollstandig ersetzt werden muss. Dies hat zu einigen Ironien gefuhrt, die eine neue Qualitat von Fehlerarten hervorgebracht haben, die haufig lapidar als „Fehlbedienungen“ abgetan werden. Der Text zeigt auf, dass diese Ironien aus einer unzureichenden Auseinandersetzung mit dem Faktor Mensch resultieren. Es wird argumentiert, dass Automatisierung ohne Einbeziehung des Menschen nicht erfolgreich betrieben werden kann. Die Rolle des Menschen muss explizit gestaltet werden und diese Rolle wegentwickeln zu wollen ist keine Losung. Der Text argumentiert fur die Auflosung einer starren Zuweisung von Aufgaben auf Mensch und Maschine. Eine optimale Aufgabenaufteilung kann nicht a-priori festgelegt werden, sondern muss zu jedem Zeitpunkt anhand festgelegter Verteilungsstrategien auf Basis situativer Erfordernisse neu bestimmt werden. Diese Flexibilitat kann durch eine neue Perspektive auf die Mensch–Maschine Beziehung unterstutzt werden: das Mensch–Maschine Team (MMT). Die Teamperspektive stellt die Entwickler vor neue Entwurfsherausforderungen. Der Text zeigt, dass diesen mit einem ingenieurmasigen modellbasierten Vorgehen begegnet werden kann. Abschliesend wird innerhalb dieses Vorgehens exemplarisch die Methodik des Ecological Interface Designs fur den Entwurf der Mensch–Maschine Schnittstelle vorgestellt.

Cognitive modelling of pilot errors and error recovery in flight management tasks

This paper presents a cognitive modelling approach to predict pilot errors and error recovery during the interaction with aircraft cockpit systems. The model allows execution of flight procedures in a virtual simulation environment and production of simulation traces. We present traces for the interaction with a future Flight Management System that show in detail the dependencies of two cognitive error production mechanisms that are integrated in the model: Learned Carelessness and Cognitive Lockup. The traces provide a basis for later comparison with human data in order to validate the model. The ultimate goal of the work is to apply the model within a method for the analysis of human errors to support human centred design of cockpit systems. As an example we analyze the perception of automatic flight mode changes.

Automated UI evaluation based on a cognitive architecture and UsiXML

In this paper, we will present a method for automated UI evaluation. Based on a formal UI description in UsiXML, the cognitive architecture CASCaS will be used to predict human performance on the UI, in terms of task execution time, workload and possible human errors. In addition, the UsabilityAdviser tool can be used to check the UI description against a set of usability rules. This approach fits well into the human performance and error analysis proposed in the European project HUMAN, where virtual testers (CASCaS) are used to evaluate assistant systems and their HMI. A first step for realizing this approach has been made by implementing a 3D rendering engine for UsiXML.

Modelling and Validating Pilots’ Visual Attention Allocation During the Interaction with an Advanced Flight Management System

This paper presents the results of our analysis of human pilot behaviour and of a cognitive pilot model. We have performed experiments in a flight simulator including a new 4D flight management system (FMS) in order to gather information about the interaction of human pilots with the new FMS and to validate the performance of the cognitive pilot model. This paper focuses on the visual attention allocation of human pilots and on the validation of the visual perception component of the pilot model.

Modelling Aspects of Longitudinal Control in an Integrated Driver Model

Simulating and predicting behaviour of human drivers with Digital Human Driver Models (DHDMs) has the potential to support designers of new (partially autonomous) driver assistance systems (PADAS) in early stages with regard to understanding how assistance systems affect human driving behaviour. This paper presents the current research on an integrated driver model under development at OFFIS within the EU project ISi-PADAS. We will briefly show how we integrate improvements into CASCaS, a cognitive architecture used as framework for the different partial models which form the integrated driver model. Current research on the driver model concentrates on two aspects of longitudinal control (behaviour a signalized intersections and allocation of visual attention during car following). Each aspect is covered by a dedicated experimental scenario. We show how experimental results guide the modelling process.

Detection of Pilot Errors in Data by Combining Task Modeling and Model Checking

In this paper we show a consistent approach of using Hierarchical Task Analysis together with model checking to identify pilot errors during the interaction with cockpit automation systems in aircraft. Task analysis is used to model flight procedures which describe how to operate a specific system in a particular situation. Afterwards model checking is used to identify deviations from these procedures in empirical simulator data. We envision applying this method to automatically detect pilot errors during flight tests or pilot training.

Human error analysis based on a semantically defined cognitive pilot model

In this paper an approach to formal analysis of potential human errors in the interaction with mode-based systems in modern aircraft cockpits is presented. We developed a cognitive model of pilot behaviour that is integrated with system design models in order to predict human errors and the resulting safety impact due to cognitive adaptation to frequently experienced flight scenarios during pilot-cockpit interaction. The paper focuses on the definition of a formal semantics for the pilot model as a basis for formal verification of pilot-system interaction. It is shown how formal verification can support debugging formal specifications of nominal flight procedures as well as producing Human Error Fault Trees.

Design of a Human-Machine Interface for Truck Platooning

Despite the advantages that truck platooning has for fuel consumption, road safety, and use of existing road infrastructure, it does not simplify the job for the drivers. Truck drivers have to maintain a reasonable level of situation awareness while having a very limited vision of the road and dealing with considerable amount of information. This paper presents the first iteration of the development process of a platooning human-machine interface (HMI). The results indicate what information is required to be presented to the drivers at each phase of platooning.