I. Modelling

UCEID-The Best of Both Worlds: Combining Ecological Interface Design with User-Centred Design in a Novel Human Factors Method Applied to Automated Driving


Human factors (HF) methods exist to tackle problems relating to the interaction between human and other elements of the system - i.e. existing methods of design, evaluation, and procurement have failed to address. These types of problems are often resistant to purely technical interventions, resulting in less effective system performance (Stanton et al. 2013). With ever-increasing rates of technological advancement, it is more difficult for companies to compete on functionality, reliability, or cost (Green and Jordan 1999). HF methods offer a means to provide a competitive edge by harnessing technology to enable people to accomplish meaningful, real-world tasks.

HF methods fall into a range of categories that are relevant for application at different parts of the design process (Stanton et al. 2013). The UCEID process includes a combination of ‘data collection’, ‘task analysis’, and ‘cognitive work analysis (CWA)’ techniques. Figure 1.1 shows how different methods are suitable at different stages of the design process. The UCEID method is positioned early in the design process to allow ‘analytical prototyping’, the means of applying HF insights to systems or designs that are yet to exist in physical form. It covers a combination of ‘identify needs’ and ‘developing concept’ stages of the design process taking the analyst to ‘initial design concept’ stage, not final concept. A key finding from inclusive user-centred design (UCD) advises an active process of linked iteration between technology prototypes and user trials is necessary to meet the dual needs of diverse user demographics and technology delivery requirements (Langdon et al. 2014) (see Figure 1.1).

Why Use UCEID?

UCEID is a novel HF method that integrates relationships between ecological interface design (EID) (Mcllroy and Stanton 2015) and inclusive human-centred design

Diagram to show where the UCEID method fits into the design process in relation to other HF methods. (Amended from Stanton et al. 2013.)

FIGURE 1.1 Diagram to show where the UCEID method fits into the design process in relation to other HF methods. (Amended from Stanton et al. 2013.)

by combining the existing methodology from the CWA framework (Rasmussen, Pejtersen and Goodstein 1994; Vicente 1999; Jenkins et al. 2008) and inclusive UCD (Czajkowski et al. 2001; Langdon and Thimbleby 2010). EID is based on Gibsonian methodology that aims to make constraints of the system and environment explicit, so that the appropriate action is apparent to the system user (Mcllroy and Stanton 2015). While both EID and UCD emphasise the user at each stage of the design process, they differ in their approach. UCD has a greater focus on end user wants, needs, and limitations within single-user actions, whereas EID focuses on incorporating user wants and needs within a complex system, constrained by the values and purpose of the overall system. Some of the values relate to stakeholders that may at times be in conflict with the end user wants and needs. Both methods aim to provide the user with a visual ‘mental model’ to guide possible action (Norman 2013), but EID’s remit within complex systems extends to providing a mental model that enables the user to troubleshooting unanticipated events (Burns and Hajdukiewicz 2004). UCDs focus on usability and can ensure solutions to meet the EID remit are easy to use and learn. EIDs focus on values and constraints based on the overall purpose of the system, and can ensure that the design solutions proposed by UCD are relevant and systematically prioritised. The UCEID approach engages with stakeholders, subject matter experts, and users to produce outputs that generate design requirements. Initial design concepts are then produced following a design workshop and concept filtering activity.

The UCEID method is best suited to complex sociotechnical systems where the user plays a critical role in the interaction. Domains that are complex exude some of the following qualities: high risk, dynamic, uncertain, w'ith interconnected parts. Vehicle-initiated, vehicle-to-driver takeover in an SAE Level 3 (SAE International 2018) autonomous vehicle fits the criteria of a complex sociotechnical system and will be used to illustrate the application of this method.


The UCEID method is compiled from a rich range of activities, starting with defining the scenario and aims of analysis, and ending with the generation of design concepts. Following the recommended criteria for depicting a method (Stanton et al. 2013), Figure 1.2 depicts a step-by-step process that can be followed ‘like a recipe’. The flowchart in Figure 1.2 describes the sequence of 16 steps (rectangles), including literature review, data collection, thematic analysis, CWA, consolidation and ideas generation, and filtering and checking. Steps within boxes can be undertaken in parallel, and decision points (diamonds) and feedback loops occur at different points in the process. The type of activity is shown by the line style (Figure 1.2). Not all aspects of the method need to be done at once, or to the same level of detail. The method can be reapplied following testing cycles as the user needs and domain constraints become more clearly specified. This section will summarise the different types of activities in the UCEID flowchart to provide the reader with examples of the types of outputs at different stages. Before embarking on the specific activities, the aims of analysis, target scenario, and boundaries of analysis need to be clearly defined - e.g. analysis of ‘transfer of control in autonomous vehicles' for the scenario ‘planned transfer of control from vehicle to driver on a highway in a SAE Level 3 vehicle'.

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