However, subjective immersion was significantly enhanced by the experience of hard and impossible demand. The amplitude of late component ERPs to oddball stimuli were significantly reduced when demand increased from easy to hard/impossible levels. We conclude that ERPs to irrelevant stimuli represent a valid method of operationalising immersion.

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The effects of executive load on working memory performance during sleep inertia after morning or afternoon naps were assessed using a mixed design with nap/wake as a between-subjects factor and morning/afternoon condition as a within-subject factor. Thirty-two healthy adults (mean 22.5 ± 3.0 years) attended two laboratory sessions after a night of restricted sleep (6 hrs), and at first visit, were randomly assigned to the Nap or Wake group. Working memory (n-back) and subjective workload were assessed approximately 5 and 25 minutes after 90-minute morning and afternoon nap opportunities and at the corresponding times in the Wake condition. Actigraphically assessed nocturnal sleep duration, subjective sleepiness, and psychomotor vigilance performance before daytime assessments did not vary across conditions. Afternoon naps showed shorter EEG assessed sleep latencies, longer sleep duration, and more Slow Wave Sleep than morning naps. Working memory performance deteriorated, and subjective mental workload increased at higher executive loadings. After afternoon naps, participants performed less well on more executive-function intensive working memory tasks (i.e., 3-back), but waking and napping participants performed equally well on simpler tasks. After some 30 minutes of cognitive activity, there were no longer performance differences between the waking and napping groups. Subjective Task Difficulty and Mental Effort requirements were less affected by sleep inertia and dissociated from objective measures when participants had napped in the afternoon. We conclude that executive functions take longer to return to asymptotic performance after sleep than does performance of simpler tasks which are less reliant on executive functions.

This article reports on a study to investigate how the driving behaviour of autonomous vehicles influences trust and acceptance. Two different designs were presented to two groups of participants (n = 22/21), using actual autonomously driving vehicles. The first was a vehicle programmed to drive similarly to a human, “peeking” when approaching road junctions as if it was looking before proceeding. The second design had a vehicle programmed to convey the impression that it was communicating with other vehicles and infrastructure and “knew” if the junction was clear so could proceed without ever stopping or slowing down. Results showed non-significant differences in trust between the two vehicle behaviours. However, there were significant increases in trust scores overall for both designs as the trials progressed. Post-interaction interviews indicated that there were pros and cons for both driving styles, and participants suggested which aspects of the driving styles could be improved. This paper presents user information recommendations for the design and programming of driving systems for autonomous vehicles, with the aim of improving their users’ trust and acceptance.

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As part of a large UK-funded autonomous vehicle project (UK Autodrive), we examined pedestrian attitudes and road-crossing intentions using a real autonomous vehicle (AV) in an indoor arena. Two conceptual external human-machine interfaces (HMIs) were presented to display the vehicle's manoeuvring intentions. Participants experienced a simulated road-crossing task to assess their interactions with the AV. Although neither HMI concept was entirely free of criticism, there were objective performance differences for a projectionbased HMI concept, as well as critical subjective opinions in pedestrian responses to specific manoeuvring contexts. These provided insight into pedestrians' safety concerns towards a vehicle where bi-directional communication with a driver is no longer possible, with suggestions for future vehicle HMI concepts.

Previous research has demonstrated changes in neurovascular activation of the prefrontal cortex to increased working memory load. The primary purpose of the current paper was to investigate overload of working memory capacity using functional near-infrared spectroscopy (fNIRS) within the framework of motivational intensity theory. A secondary goal was to explore the influence of the correlation-based signal improvement (CBSI) as a method for correcting the influence of systemic variables. In study one, 30 participants (15 female, mean age = 21.09 years, s.d. = 2.9 years) performed a verbal version of the -back working memory task under four levels of demand (easy, hard, very hard, and impossible). In contrast to the raw data, CBSI-transformed fNIRS data indicated that neurovascular coupling was highest at hard demand when the task was challenging but success was possible. The second study ( ; 15 female, mean age = 22.4 years, s.d. = 5.3) replicated the working memory manipulation with the addition of low versus high levels of financial reward. Analyses of CBSI-transformed levels of oxygenated (HbO) and deoxygenated (HHb) hemoglobin replicated the first study at right lateral regions of the prefrontal cortex (BA46). HHb_CBSI data were significantly reduced at impossible demand for participants receiving the higher level of financial reward. The study is the first to support predictions from the motivational intensity model using neurovascular data. In addition, the application of CBSI to fNIRS data was found to improve the sensitivity of HbO and Hbb to the independent variables.

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