Following the participatory design process, there was a need to generate more detailed design specifications for the in-vehicle assistive devices, to enable user testing using driving simulation. During the design refinement workshop, stakeholders accepted a proposed refinement to the Intelligent Level Crossing and the GPS Average Speed concept, which was to generate the detailed designs for the in-vehicle devices using the Ecological Interface Design (EID) approach. This was proposed by the researchers to provide an additional link between the initial systems analyses (i.e. CWA) and the design concepts.

In addition, given the assessment that the designs generated through the participatory process did not radically change rail level crossing (e.g. as reflected by poor alignment with STS principles), an additional design workshop was held with the research team to generate more revolutionary concepts.

In-Vehicle Interface Design Using EID Principles

EID is a design strategy that uses the abstraction hierarchy from WDA, coupled with principles from the skills, rule and knowledge taxonomy (Rasmussen 1983, Vicente and Rasmussen 1992).

In this taxonomy, skill-based behavior is the lowest level of cognitive control and refers to sensory-motor performance, which occurs in skilled activity without the requirement for conscious processing. Rule-based behaviour involves the application of stored rules, based on past experience, to make decisions. Finally, the highest level of cognitive control is knowledge-based behaviour, which is engaged during decision-making in unfamiliar situations where it is not possible to draw upon past experience. In these situations, reasoning is used to understand the situation and select an appropriate course of action.

The principles of EID specify that an interface should not require an operator to employ a higher level of cognitive control than necessary for the demands of the task. Further, the interface should support each level of cognitive control (i.e. skill, rule and knowledge-based behaviour). The underlying philosophy of EID is that the design (i.e. display or interface) should make the system constraints explicit to its end users. As with CWA, the focus is on the overall system and its constraints. As such, EID aims to make the interface transparent; its goal is to support direct perception and action, while correspondingly providing support for problem-solving activities (Vicente and Rasmussen 1990).

EID has been applied to the design of interfaces within varied domains ranging from nuclear process control (e.g. Burns et al. 2008) and health care (e.g. Watson and Sanderson 2007), to road transport (e.g. Young and Birrell 2012). Experimental evaluations have demonstrated that ecological interfaces elicit better performance than traditional interfaces (for reviews, see Burns and Hajdukiewicz [2004] and Vicente [2002]).

Although EID was not initially considered as a candidate approach for rail level crossing design due to our focus being the design of the physical environment and the infrastructure, it was incorporated into the process following the inclusion of in-vehicle interfaces in two proposed design concepts. The initially proposed designs for the in-vehicle interfaces provided warnings about approaching rail level crossing and approaching trains using symbolic representations (e.g. pictorial images of a warning sign shown on the interface). Such representations are perceived as signs, which activate rule-based processing (Rasmussen 1983). They are limited as they require the observer to understand conventions (e.g. by drawing on experience or training), and they cannot be used to look beyond what is presented to engage in troubleshooting or problem solving when there is a failure or other disturbance.

Separate detailed design workshops were undertaken to revise the designs of in-vehicle interfaces for the Intelligent Level Crossing and the GPS Average Speed concepts. In each workshop, the WDA was reviewed to identify the key constraints that should be displayed to the driver; then options for representing these constraints were generated and refined, and a final selection was made by the research team.

For the Intelligent Level Crossing concept, the key constraints identified were the train itself (its position, speed and direction of travel), the approaching vehicle (its position, speed and direction of travel) and the relationship in time and space between the two. It was determined that the display should dynamically represent the field of safe travel for the road user (Gibson and Crooks 1938). Field of safe travel theory posits that drivers operate by perceiving a dynamic space around their vehicle which, based on the surrounding traffic and hazards, is judged to be safe to occupy. Drivers seek to preserve an acceptable ratio between the available stopping distance and the boundary of the perceived safe field ahead. Drawing on this notion, we designed a visual representation of the dynamic field of safe travel, which would be presented ahead of the vehicle in the form of a green ‘tongue’ that shrinks in size and eventually disappears as the vehicle approaches the crossing while the train is also approaching (see Figure 8.1a for an early design sketch). This visual tracking would support skill-based behaviour, whereas additional features such as a symbolic representation of the train appearing on the interface to indicate an approaching train, and auditory messages stating the direction of train approach, would assist in supporting rule- and knowledge-based behaviour.

Design sketches for in-vehicle assistive devices using EID principles

FIGURE 8.1 Design sketches for in-vehicle assistive devices using EID principles.

  • (a) Early design sketch for the urban Intelligent Level Crossing in-vehicle interface and
  • (b) Early design sketch of the GPS Average Speed in-vehicle interface.

For the GPS Average Speed concept, the key innovation was speed management of the vehicle as it approached the crossing, advising users to make small speed adjustments over a long distance so they could avoid coming to a complete stop for the train. Here, the key constraints were speed and position of the train and road vehicle, with the display providing guidance on the speed required for the driver to avoid arriving at the crossing at the same time as a train. In order to best support skill- based visual tracking, the design interface was overlaid onto the driver’s speedometer (see Figure 8.1b for an early design sketch of the interface). This would provide the driver with an interval of desired or safe speeds (a green zone shown on the display), and a lower and upper speed limit, with the upper limit considered undesirable or unsafe (a red zone shown on the display). These zones would be dynamically updated by analysing the road vehicle’s position and speed, compared with the train’s position and speed. Again, to also support rule- and knowledge-based behaviour, a train symbol was shown on the display when the speed guidance was active, to convey that the train approach was the reason for the guidance. In addition, an auditory tone would be used to alert the user when the speed guidance becomes active and another tone would be sounded when the vehicle was travelling at a speed within the designated red zone.

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