Since I do not have any particular knowledge in cognitive science. My first goal was to learn about this domain. So I read a lot of scientific papers about emotions; Which physiological or behavioral signals we can use, how to analyze these signals, how we can condition someone to make him feel a specific emotion... Obviously, I mainly focused my researches on frustration and drivers mental state but also on the body posture (since my machine learning analysis should focus in priority on the driver's position on the seat).
The first article justifies that we care about drivers' frustration. In this paper, Shinar [1] analyzes the frustration-aggression model introduced by Dollard et al. [2] and some other studies models which states that drivers' aggression are more related to the driver's culture and establish that most of the "real" aggression are due to the driver's frustration.
Several interesting papers dealing with frustration monitoring are written in the context of learners using AutoTutor (for examples: Kapoor et al. [3] and D'Mello et al. [4]). Even if they do not speak about drivers, these papers are really useful for me, because they show some methods used to detect the learner's frustration with some sensors very similar to the one I will use. In particular, [4] used the body posture of the learner on its seat to predict his mental state.
Other papers are dealing with drivers' frustration but not with body posture. Bořil et al. [5] use only a speech analysis (not sure that I use this kind of data) to predict drivers' mental state on a simulator (as in my case). While Malta et al. [6] deal with pedal actuation, Electrodermal activity (EDA) (I could use this one) and speech recognition.
In all these papers the results show that we could be able to efficiently monitor the drivers mental state in real life.
References
[1] Aggressive driving: the contribution of the drivers and the situation, D. Shinar, 1998
[2] Frustration and aggression, J. Dollard, L. W. Doob, N. P. Miller, O. H. Mowrer, R. R. Sears, 1939
[3] Automatic prediction of frustration, A. Kapoor, W. Burleson, R. W. Picard, 2006
[4] Automatic detection of learner's affect from gross body language, S.D'Mello, A. Graesser, 2009
[5] Analysis and detection of cognitive load and frustration in drivers’ speech, H. Bořil, S. O. Sadjadi, T. Kleinschmidt, J. H. L. Hansen
[6] Analysis of real-world driver’s frustration, L. Malta, C. Miyajima, N. Kitaoka, K. Takeda
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