Dashboard Reachability and Usability Tests: A Cheap and Effective Method for Drivers' Comfort Rating 2014-01-0455

General comfort may be defined as the “level of well-being” perceived by humans in a working environment. The state-of-the-art about evaluation of comfort/discomfort shows the need for an objective method to evaluate the “effect in the internal body” and “perceived effects” in main systems of comfort perception.

In the early phases of automotive design, the seating and dashboard command can be virtually prototyped, and, using Digital Human Modeling (DHM) software, several kinds of interactions can me modeled to evaluate the ergonomics and comfort of designed solutions. Several studies demonstrated that DHM approaches are favorable in virtual reachability and usability tests as well as in macro-ergonomics evaluations, but they appear insufficient in terms of evaluating comfort. Comfort level is extremely difficult to detect and measure; in fact, it is affected by individual perceptions and always depends on the biomechanical, physiological, and psychological state of the tester during task execution. These parameters cannot be modeled using software and instead have to be tested on physical models.

A seating buck is often used to prototype a driver's seat, and virtual, mixed, and augmented reality devices help designers to improve ergonomics and comfort of a human-machine interface (HMI). In such environments, both postural and cognitive comfort can be evaluated, but often, testers' opinions are affected by devices, their interaction with designers, and especially, posture analysis systems. One solution to this kind of perception alteration can be found in non-invasive acquisition methods, such as acoustic, magnetic, or optical methods. Each has its own advantages and disadvantages, but all share the same characteristics: they are expensive and difficult to calibrate and use.

This paper presents a new method for objectifying and evaluating postural and cognitive comfort levels based on human posture analysis and a questionnaire to evaluate cognitive performance. The posture acquisition method employs commercial low-cost cameras on tripods. The comfort evaluation methods, previously developed at the University of Salerno, are based on several experimental test campaigns, statistical processing, and biomedical studies. The method was tested in terms of reachability and usability for automotive drivers and was performed in a B-segment car (FIAT Grande Punto).

A sensitivity analysis was performed to correlate the low resolution of the photographic acquisition with the consequent errors in the comfort evaluation. Posture acquisition errors were analyzed using DHM (DELMIA) software.