4 research outputs found

    Multimodal Features for Detection of Driver Stress and Fatigue: Review

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    Driver fatigue and stress significantly contribute to higher number of car accidents worldwide. Although, different detection approaches have been already commercialized and used by car producers (and third party companies), research activities in this field are still needed in order to increase the reliability of these alert systems. Also, in the context of automated driving, the driver mental state assessment will be an important part of cars in future. This paper presents state-of-the-art review of different approaches for driver fatigue and stress detection and evaluation. We describe in details various signals (biological, car and video) and derived features used for these tasks and we discuss their relevance and advantages. In order to make this review complete, we also describe different datasets, acquisition systems and experiment scenarios

    The Application of Physiological Metrics in Validating User Experience Evaluation on Automotive Human Machine Interface Systems

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    Automotive in-vehicle information systems have seen an era of continuous development within the industry and are recognised as a key differentiator for prospective customers. This presents a significant challenge for designers and engineers in producing effective next generation systems which are helpful, novel, exciting, safe and easy to use. The usability of any new human machine interface (HMI) has an implicit cost in terms of the perceived aesthetic perception and associated user experience. Achieving the next engaging automotive interface, not only has to address the user requirements but also has to incorporate established safety standards whilst considering new interaction technologies. An automotive (HMI) evaluation may combine a triad of physiological, subjective and performance-based measurements which are employed to provide relevant and valuable data for product evaluation. However, there is also a growing interest and appreciation that determining real-time quantitative metrics to drivers’ affective responses provide valuable user affective feedback. The aim of this research was to explore to what extent physiological metrics such as heart rate variability could be used to quantify or validate subjective testing of automotive HMIs. This research employed both objective and subjective metrics to assess user engagement during interactions with an automotive infotainment system. The mapping of both physiological and self-report scales was examined over a series of studies in order to provide a greater understanding of users’ responses. By analysing the data collected it may provide guidance within the early stages of in-vehicle design evaluation in terms of usability and user satisfaction. This research explored these metrics as an objective, quantitative, diagnostic measure of affective response, in the assessment of HMIs. Development of a robust methodology was constructed for the application and understanding of these metrics. Findings from the three studies point towards the value of using a combination of methods when examining user interaction with an in-car HMI. For the next generation of interface systems, physiological measures, such as heart rate variability may offer an additional dimension of validity when examining the complexities of the driving task that drivers perform every day. There appears to be no boundaries on technology advancements and with this, comes extra pressure for car manufacturers to produce similar interactive and connective devices to those that are already in use in homes. A successful in-car HMI system will be intuitive to use, aesthetically pleasing and possess an element of pleasure however, the design components that are needed for a highly usable HMI have to be considered within the context of the constraints of the manufacturing process and the risks associated with interacting with an in-car HMI whilst driving. The findings from the studies conducted in this research are discussed in relation to the usability and benefits of incorporating physiological measures that can assist in our understanding of driver interaction with different automotive HMIs
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