Driver heterogeneity in willingness to give control to conditional automation

Abstract

Drivers with varying locus of control may exhibit differences in their choices between manually controlling dynamic driving tasks and monitoring the automated vehicle where they act as a “fallback-ready user”. Additionally, response variations in relinquishing control to automated driving are evident, as drivers have diverse preferences for the extent of utilizing driving automation in different situations influenced by their perceived understanding of the automated features. In this study, the driver's willingness to give (WTG) control in conditionally automated driving is objectively assessed in a virtual reality based driving-rig, through their choice to give away driving control and through the extent to which automated driving is adopted during a trip in a mixed-traffic environment. Within- and across-class unobserved heterogeneity and locus of control variations are taken into account. The binary choice of giving away control is estimated through the mixed logit (MIXL) and mixed latent class (LCML) model, having the binary logit as a base mode. The significant latent segments of the locus of control are developed into internalizers and externalizers by the latent class model (LCM) based on the taste heterogeneity identified from the MIXL model. The obtained results highlighted the significant factors influencing the choice and levels of automated driving adoption. Results suggest that drivers choose to ‘giveAway’ control of the vehicle when greater concentration/attentiveness is required (e.g., in the nighttime) or when they are interested in performing a non-driving-related task (NDRT). In addition, it is observed that internalizers demonstrate more heterogeneity compared to externalizers toward the binary choice of WTG in conditional automation.