Objective: The present research compared and contrasted the workload associated with using in-vehicle information systems commonly available in five different automotive original equipment manufacturers (OEMs) with that of CarPlay and Android Auto when used in the same vehicles. Background: A growing trend is to provide access to portable smartphone-based systems (e.g., CarPlay and Android Auto) that support an expansion of various in-vehicle infotainment system features and functions. Method/Results: The study involved on-road testing of 24 participants in each configuration of five vehicles crossed with the three different infotainment systems: the embedded portion of the native OEM systems, CarPlay, and Android Auto. Our analysis found that workload was significantly greater for the embedded portion of the native OEM systems than for CarPlay and Android Auto. The strengths and weaknesses of each CarPlay and Android Auto traded off in such a way that the overall demand associated with using the two systems did not differ. Conclusion: CarPlay and Android Auto provided more functionality and resulted in lower levels of workload than the embedded portion of the native OEM infotainment systems. Application: Potential applications of this research include refinements to CarPlay and Android Auto to address variations in workload as a function of task type, the modality of interaction, and OEM implementation of the system.

Background New automobiles provide a variety of features that allow motorists to perform a plethora of secondary tasks unrelated to the primary task of driving. Despite their ubiquity, surprisingly little is known about how these complex multimodal in-vehicle information systems (IVIS) interactions impact a driver’s workload. Results The current research sought to address three interrelated questions concerning this knowledge gap: (1) Are some task types more impairing than others? (2) Are some modes of interaction more distracting than others? (3) Are IVIS interactions easier to perform in some vehicles than others? Depending on the availability of the IVIS features in each vehicle, our testing involved an assessment of up to four task types (audio entertainment, calling and dialing, text messaging, and navigation) and up to three modes of interaction (e.g., center stack, auditory vocal, and the center console). The data collected from each participant provided a measure of cognitive demand, a measure of visual/manual demand, a subjective workload measure, and a measure of the time it took to complete the different tasks. The research provides empirical evidence that the workload experienced by drivers systematically varied as a function of the different tasks, modes of interaction, and vehicles that we evaluated. Conclusions This objective assessment suggests that many of these IVIS features are too distracting to be enabled while the vehicle is in motion. Greater consideration should be given to what interactions should be available to the driver when the vehicle is in motion rather than to what IVIS features and functions could be available to motorists. Electronic supplementary material The online version of this article (10.1186/s41235-019-0166-3) contains supplementary material, which is available to authorized users.

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Despite driver assistance systems being engineered to enhance safety, recent studies show the potential for some of these systems and deficient human–machine interfaces to cause unintended consequences on safety. The NHTSA, the Alliance of Automotive Manufacturers, and the European Commission have all released best practices and human factors guidelines for the development and assessment of function-aspecific interfaces. However, given their broad scope, none of these documents provides a rating and benchmarking tool for assessing design aspects pertinent to a wide spectrum of assistance systems, ranging from rearview cameras to lane keeping assist systems. In this article we detail the development of a scale for assessing the human–machine interfaces of 10 different assistance systems. The scale contains 59 items, developed through multiple iterations, in which a total of 94 distinct assistance systems available on vehicles of different makes and models underwent evaluation. For each system included, we provide a description of its characteristics, a list of items for assessment, and relevant references. Widely accepted industry (ISO, SAE) standards, design guidelines, and assessment methodologies were considered for the development of this scale. The adoption of this scale required at least two evaluators to rate each system against specific assessment items using the following 4-point scale: No Concern (3 points), Minor Concerns (2 points), Serious Concerns (1 point), Not Applicable (0 points). Final ratings resulting from this evaluation will aid evaluators in the benchmarking process, and in determining what specific design aspects of the systems assessed merit further attention.

The detection response task (DRT) and its variations provide a new tool for measuring cognitive workload in complex task environments such as driving. A number of previous investigations have clearly established the utility of the DRT for assessing cognitive demand in tasks that do not contain a visual–manual interaction component. However, the potential utility of the DRT for assessing the cognitive demand of primarily visual–manual tasks has not yet been established. Additionally, the various task demands required by the DRT have raised concerns over potential task interference. The aim of this study was to evaluate these important research needs by assessing the performance of common in-vehicle tasks using voice recognition, steering wheel controls, and the center stack touch screen. Tasks were completed both with and without the DRT. Results indicated the presence of the DRT increased task completion time but the effect was surprisingly modest. These findings should be of interest to researchers and practitioners involved in the assessment of cognitive load in complex task environments.