Background: Hyperloop is a new technological concept for a very fast magnetic levitation train that would travel through soft vacuum tubes and could achieve a speed of up to 1,200 km/h. As a new transportation system, it might bring some challenges related to human factors that should be tested and considered when designing and propagating Hyperloop. Aim: This paper used literature review to identify potential physiological and social challenges. Some of these challenges might be high speed, high acceleration /deceleration, large magnetic forces, safety concerns, air pressure, motion sickness and cost as potential human-related challenges. Methods: In this case, the method of literature review aimed to evaluate the potential physiological effect of these factors on the passengers. It investigated physiological consequences of very high speed, high acceleration/deceleration, and a high magnetic field, as well as human factors of the Maglev trains. Results: The literature identified high acceleration/deceleration, high speed and high magnetic field as potential risks or sources of discomfort for the passengers. Conclusion: To the knowledge of the authors, it is the first attempt to identify social and physiological challenges related to the Hyperloop trains concept. It is aimed to inform the development and policies to achieve the safest and most comfortable transportation form.

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Automation offers the potential to mitigate or reduce the risks related to driving. There are some new challenges for drivers related to semi-automated driving. Some of them are associated with suboptimal mental workload or prolonged need for sustained attention. This paper presents the results of an experiment investigating differences in manual driving before and after the automated phase in the scenario simulating a time-course of semi-automated driving. Sample size: 52 participants with two experimental sessions each day and night session. The experiment used a driving simulator to create a semi-automated driving scenario comprising manual driving, the automated phase, and manual driving. The following questionnaires were collected: Karolinska Sleepiness Scale, TakeOver Readiness Scale (developed for this research project, included in Appendix), Samn-Perelli Fatigue Scale, and NASA-TLX. Driving performance significantly decreased after the automated phase (e.g., standard deviation of the steering wheel angle was 255.73 before vs. 287.11 after automation) and the effect was more profound during the night. Participants were sleepier and more fatigued after the automated phase, and assessed mental workload as lower. The results of the questionnaires did not correlate with driving performance. The results of the experiment suggest that manual driving could deteriorate after the automated phase, and that driver might not be able to assess their fitness to drive at the moment of takeover of manual driving.