Approach

The i-DREAMS project hinges upon the Task-Capability Interface Model (Fuller, 2000). Central in this model is the aspect of calibration, which stands for the idea that road users self-regulate their behaviour in function of personal estimations of the (im)balance between imposed task demand and available coping capacity. Both task demand and available coping capacity are multi-dimensional concepts dependent upon a multitude of (endogenous and exogenous) variables.

Research demonstrates perceptions of experienced task demand and available coping capacity are subjective (Michon, 1989). As a consequence, the personally estimated critical safety tolerance zone (i.e. the time/distance available to implement corrective actions safely) often does not correspond to objective safety margins. Also, studies show that what is ‘acceptable’ as a safety tolerance zone, is subjective with differences not only between individuals but within the same individual (across different situations and time) as well (Fuller, 2011). These phenomena together undermine the effectiveness of self-regulative actions, resulting in an increased crash risk.

According to experts working within the Control Theory Paradigm, important for a deeper understanding of frameworks such as the Task-Capability Interface Model, is the time window used for interpretation. As Horrey et al. (2015) explain, on the one hand, there is the ‘local’ perspective, considering the mechanisms contained by the Model to be operating constantly and in real-time while driving. On the other hand, the ‘general’ perspective, considers these mechanisms to be operating within a larger time frame, namely, across the multitude of individual trips which together constitute a person’s driving history. Furthermore, the ‘general’ perspective relates the mechanisms contained by the Model to factors more global and stable across time, such as age, experience, personality traits (e.g., sensation seeking, impulsivity), etc.

This difference between a ‘local’ and a ‘general’ interpretation of the Model has important implications for safety management. A ‘local’ or ‘in real-time’ interpretation of the Model implies that the closed-loop process of sampling, judging, and acting upon the world is constantly ongoing while driving, and that if a response on behalf of the driver is required, this is always a response to an acute, momentary need. Since human operators are vulnerable to the commission of errors when monitoring and processing information related to the objective ‘state-of-the-world’ their behavioural self-regulation will suffer from inadequacies. To lower the risk for such inadequacies, drivers need assistance while driving by instruments that allow a more accurate sampling and responding to the objective state-of- the world. In sum, a ‘local’ interpretation of the Task-Capability Interface Model implies that interventions aimed at increasing safety have to take place in real-time, while driving.

The important complement of the ‘general’ view to the ‘local view’, is in the more holistic idea that sampling, judging and acting upon the world while operating a vehicle is also dependent on factors more stable across time. Typically however, car assistance systems do not really take into account such stable factors. It is for instance, not common that such systems are tailored to features such as personality, driving experience, safety attitudes, etc. (e.g. Horrey et al., 2012; the gamECAR-project). In fact, research shows that in order to have impact on the influence of those more stable characteristics, other interventional approaches are required, often running over longer time episodes and targeting for a gradual and stepwise change process in the vehicle operator (e.g., Karlsson et al., 2017).

As for the conception of the i-DREAMS project, the above presented ideas have two implications. First of all, for interventions aimed at increasing driver safety to be effective, we need an as accurate as possible risk monitoring instrument. This issue will constitute the project’s first pillar (i.e. risk monitoring). Second, impact on driver safety can be expected to be higher, if proposed interventions in some way combine the local perspective (i.e. in-vehicle assistance with instant impact on driving) with the general perspective (i.e. longer-term support for a gradual change process in the vehicle operator). This will be the project’s second pillar (i.e. safety interventions). Altogether, the objective will be to develop, implement and test a technological solution (i.e. the i-DREAMS platform) that brings together the functionalities.