Task analysis for error identification: Theory, method and validation

This paper presents the underlying theory of Task Analysis for Error Identification. The aim is to illustrate the development of a method that has been proposed for the evaluation of prototypical designs from the perspective of predicting human error. The paper presents the method applied to representative examples. The methodology is considered in terms of the various validation studies that have been conducted, and is discussed in the light of a specific case study

An evaluation of US systems for facial composite production

Witness and victims of serious crime are normally requested to construct a facial composite of a suspect’s face. While modern systems for constructing composites have been evaluated extensively in the UK, this is not the case in the US. In the current work, two popular computerized systems in the US, FACES and Identikit 2000, were evaluated against a ‘reference’ system, PRO-fit, where performance is established. In Experiment 1, witnesses constructed a composite with both PRO-fit and FACES using a realistic procedure. The resulting composites were very poorly named, but the PRO-fit emerged best in ‘cued’ naming and two supplementary measures: composite sorting and likeness ratings. In Experiment 2, PRO-fit was compared with Identikit 2000, a sketch-like feature system. Spontaneous naming was again very poor, but both cued naming and sorting suggested that the systems were similar. The results support previous findings that modern systems do not produce identifiable composites

Mapping Cumulative Environmental Risks: Examples from The EU NoMiracle Project

We present examples of cumulative chemical risk mapping methods developed within the NoMiracle project. The different examples illustrate the application of the concentration addition (CA) approach to pesticides at different scale, the integration in space of cumulative risks to individual organisms under the CA assumption, and two techniques to (1) integrate risks using data-driven, parametric statistical methods, and (2) cluster together areas with similar occurrence of different risk factors, respectively. The examples are used to discuss some general issues, particularly on the conventional nature of cumulative risk maps, and may provide some suggestions for the practice of cumulative risk mapping

An Ontological Approach to Inform HMI Designs for Minimizing Driver Distractions with ADAS

ADAS (Advanced Driver Assistance Systems) are in-vehicle systems designed to enhance driving safety and efficiency as well as comfort for drivers in the driving process. Recent studies have noticed that when Human Machine Interface (HMI) is not designed properly, an ADAS can cause distraction which would affect its usage and even lead to safety issues. Current understanding of these issues is limited to the context-dependent nature of such systems. This paper reports the development of a holistic conceptualisation of how drivers interact with ADAS and how such interaction could lead to potential distraction. This is done taking an ontological approach to contextualise the potential distraction, driving tasks and user interactions centred on the use of ADAS. Example scenarios are also given to demonstrate how the developed ontology can be used to deduce rules for identifying distraction from ADAS and informing future designs