Abstract
In the way of smoothing driver interaction with highly automated vehicles, we designed an immersive (VR + serious game) training program with a focus on improving drivers’ mental model. Then, we tackled the usability flaws and upgraded the preliminary serious game (PSG) to usability-improved serious game (USG). Three groups of participants-no-training, PSG and USG- were tested to explore the effects of immersive training on drivers performance and experiences in highly automated driving. The results showed that both training programs significantly improved driving performance and resulted in faster takeover time (TOT), longer time-to-collision (TTC), and fewer number of the collision. Moreover, the participants in training groups reported less erratic acceptance and more calibrated trust compared to the control group. Although improving usability in USG led to better flow experience (enjoyment and engagement) and lower cognitive load during the learning process, it did not contribute significantly to training transferability.
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References
Miller, D., et al.: Behavioral measurement of trust in automation: the trust fall. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting. SAGE Publications Sage, Los Angeles (2016)
Hergeth, S., et al.: Keep your scanners peeled: gaze behavior as a measure of automation trust during highly automated driving. Hum. Factors 58(3), 509–519 (2016)
Beggiato, M., et al.: Learning and development of trust, acceptance and the mental model of ACC. A longitudinal on-road study. Transp. Res. Part F Traffic Psychol. Behav. 35, 75–84 (2015)
De Winter, J.C., et al.: Effects of adaptive cruise control and highly automated driving on workload and situation awareness: a review of the empirical evidence. Transp. Res. Part F Traffic Psychol. Behav. 27, 196–217 (2014)
Stanton, N.A., Young, M.S.: Driver behaviour with adaptive cruise control. Ergonomics 48(10), 1294–1313 (2005)
Payre, W., et al.: Impact of training and in-vehicle task performance on manual control recovery in an automated car. Transp. Res. Part F Traffic Psychol. Behav. 46, 216–227 (2017)
Rudin-Brown, C.M., Parker, H.A.: Behavioural adaptation to adaptive cruise control (ACC): implications for preventive strategies. Transp. Res. Part F Traffic Psychol. Behav. 7(2), 59–76 (2004)
Saffarian, M., de Winter, J.C., Happee, R.: Automated driving: human-factors issues and design solutions. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting. Sage Publications Sage, Los Angeles (2012)
Sportillo, D., Paljic, A., Ojeda, L.: Get ready for automated driving using virtual reality. Accid. Anal. Prev. 118, 102–113 (2018)
Mettler, T., Pinto, R.: Serious games as a means for scientific knowledge transfer—a case from engineering management education. IEEE Trans. Eng. Manage. 62(2), 256–265 (2015)
van der Kuil, M.N., et al.: A usability study of a serious game in cognitive rehabilitation: a compensatory navigation training in acquired brain injury patients. Front. Psychol. 9, 846 (2018)
Winn, B.M.: The design, play, and experience framework. In: Handbook of Research on Effective Electronic Gaming in Education, pp. 1010–1024. IGI Global (2009)
Hoogendoorn, R., van Arerm, B., Hoogendoom, S.: Automated driving, traffic flow efficiency, and human factors: literature review. Transp. Res. Rec. 2422(1), 113–120 (2014)
Goodrich, M.A., Boer, E.R.: Model-based human-centered task automation: a case study in ACC system design. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 33(3), 325–336 (2003)
Lee, J.D., Hoffman, J.D., Hayes, E.: Collision warning design to mitigate driver distraction. In: Proceedings of the SIGCHI Conference on Human factors in Computing Systems. ACM (2004)
Neisser, U., Cognition and Reality: Principles and Implications of Cognitive Psychology. WH Freeman/Times Books/Henry Holt & Co. (1976)
Olsen, T., Procci, K., Bowers, C.: Serious games usability testing: how to ensure proper usability, playability, and effectiveness. In: International Conference of Design, User Experience, and Usability. Springer (2011)
Tolentino, G.P., et al.: Usability of serious games for health. In: Third International Conference on Games and Virtual Worlds for Serious Applications (VS-GAMES). IEEE (2011)
Pinelle, D., Wong, N., Stach, T.: Heuristic evaluation for games: usability principles for video game design. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM (2008)
Federoff, M.A.: Heuristics and Usability Guidelines for the Creation and Evaluation of Fun in Video Games. Citeseer (2002)
Nielsen, J.: 10 usability heuristics for user interface design. Nielsen Norman Group 1(1) (1995)
Chang, C.-C., et al.: Is game-based learning better in flow experience and various types of cognitive load than non-game-based learning? Perspective from multimedia and media richness. Comput. Hum. Behav. 71, 218–227 (2017)
Csikszentmihalyi, M.: Flow: The Psychology of Optimal Performance. Harper and Row, New York (1990)
SAE: SAE levels of driving automation (2016). https://www.sae.org/standards/content/j3016_201609/
Abraham, H., Reimer, B., Mehler, B.: Learning to use in-vehicle technologies: consumer preferences and effects on understanding. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting. SAGE Publications, Los Angeles (2018)
Alicandri, E., Roberts, K., Walker, J.: A validation study of the DOT/FHWA highway simulator (HYSIM). Federal Highway Administration (1986)
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Ebnali, M., Kian, C., Ebnali-Heidari, M., Mazloumi, A. (2020). User Experience in Immersive VR-Based Serious Game: An Application in Highly Automated Driving Training. In: Stanton, N. (eds) Advances in Human Factors of Transportation. AHFE 2019. Advances in Intelligent Systems and Computing, vol 964. Springer, Cham. https://doi.org/10.1007/978-3-030-20503-4_12
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