IMPLEMENTING HUMAN FACTORS WITHIN THE DESIGN PROCESS OF ADVANCED DRIVER ASSISTANCE SYSTEMS (ADAS)
The emerging trend in driver support systems is aimed at reducing requirements placed on the driver. By equipping vehicles with sensors, navigation and motion planning, the driving task is shared between human actors and the supporting assistance systems. Ultimately, by adding and improving cognition and control techniques, this could lead to autonomous vehicles in which the driving task is controlled by the vehicle and the responsibility is shifted towards the vehicle and its manufacturer.
Although legal issues and high infrastructural demands will prevent the introduction of such autonomous vehicles in the near future, research has already provided (semi-) automated concept cars in which no (or minimal) intervention of human actors is required.
Meanwhile, different assistance systems are already supporting the driver by means of sensory information (e.g. visibility aids or lane departure warnings), correction (e.g. anti-lock braking system or traction control) or even control (e.g. automatic parking).
A serious implication of the growing amount of these assistance systems in modern day cars is the unknown effect different types and quantities of information can have on the driving performance. Different studies have provided evidence of reduced users’ workload while supported by assistance systems (e.g. Stanton and Young, 2005). However, these studies did not take into account what effect a combination of support systems (and hence, with different configurations and amounts of information) can have on the drivers’ performance. Information which is of prior importance in order to produce safe and efficient cars in the future.