Music and Simulated Urban Driving Dataset
Checks for univariate outliers were conducted using standardised scores (z > ± 3.29) and for multivariate outliers using the Mahalanobis distance test (p < .001; Tabachnick & Fidell, 2019). Parametric assumptions that underlie within-subjects ANOVA (Tabachnick & Fidell, 2019) were assessed (e.g., Q-Q plots and the Shapiro–Wilk test for normality). Initial analyses for the psychological measures (i.e., RSME, NASA-TLX and Affect Grid) were conducted using mixed-model Condition × Personality (M)ANOVAs and significant F tests were followed up with pairwise/multiple comparisons. Where the assumption of sphericity was violated, Greenhouse–Geisser-adjusted F tests were used.
Three types of behavioural data were acquired from the urban driving simulation: (a) a risk-rating (on the scale from 1 [safe driving] to 4 [reckless driving]) derived from video data (without any audible sound) and pertaining to driving performance in the entire trial. Three members of the research team conducted the ratings and inter-rater reliabilities were computed; (b) course completion time (min); (c) mean speed (mph), and (d) accelerator and brake pedal positions (i.e., 0 = no pressure applied, 1 = maximum braking).
Funding
Riding Along In My Automobile: Musically-Induced Emotions and Driving Behaviour
Economic and Social Research Council
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