Abstract
The present chapter discusses the ability of a moving driver simulator to assess the trust of drivers in conditionally automated driving functions. This process includes extracting the right scenarios, the method for creating objective assessment criteria, and the technical solution of a simulator setup. The linking of different sensors and hardware interfaces, as well as time synchronisation, are discussed. Limitations of a driver simulator are analysed. The examined study of 60 participants, including the testing method and its strengths and weaknesses, is described and critically reflected.
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References
TrustVehicle, European Union’s Horizon 2020 research and innovation programme under grant agreement No 723324, 2017. HORIZON 2020 Grant Agreement
General Data Protection Regulation (GDPR) Compliance Guidelines, 2020. https://gdpr.eu/. Accessed 22 Apr 2020
AVL-DRIVE™, 2020. https://www.avl.com/-/avl-drive-4. Accessed 06 Apr 2020
National Transport Commission Clarifying control of automated vehicles, 2017. https://www.ntc.gov.au/sites/default/files/assets/files/Discussion-Paper-Clarifying-control-of-automated-vehicles.pdf. Accessed 29 Jan 2020
SAE International, 2020. https://www.sae.org/about/. Accessed 06 Apr 2020
Perkins, C., Del-Colle, A.: Fatal Tesla Model S Crash While In Autopilot Triggers NHTSA Investigation, 2016. https://www.roadandtrack.com/new-cars/car-technology/news/a29791/tesla-autopilot-fatal-crash-report. Accessed 30 Jan 2020
Hallerbach, S., Xia, Y., Eberle, U., et al.: Simulation-based identification of critical scenarios for cooperative and automated vehicles. SAE Intl. J. CAV 1(2), 93–106 (2018). https://doi.org/10.4271/2018-01-1066
Holzinger, J., Bogner, E.: Objective assessment of advanced driver assistance systems. ATZ Worldw. 119(9), 16–19 (2017). https://doi.org/10.1007/s38311-017-0089-x
On-Road Automated Driving (ORAD) committee Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles (3016)
Waymo, On the Road to Fully Self-Driving. Waymo Safety Report, 2017. https://storage.googleapis.com/sdc-prod/v1/safety-report/Safety%20Report%202018.pdf. Accessed 30 Jan 2020
Hoeger, R., Amditis, A., Kunert, M., Hoess, A., Flemisch, F., Krueger, H.-P., Bartels, A., Beutner, A.: Highly Automated Vehicles for Intelligent Transport: HAVEit Approach (2008)
Basu, C., Yang, Q., Hungerman, D., et al.: Do You Want Your Autonomous Car To Drive Like You? 2017. https://doi.org/10.1145/1235
Koglbauer, I., Holzinger, J., Eichberger, A., et al.: Autonomous emergency braking systems adapted to snowy road conditions improve drivers’ perceived safety and trust. Traffic Inj. Prev. 19(3), 332–337 (2018). https://doi.org/10.1080/15389588.2017.1407411
Cruden.: Automotive driving simulators, 2020. https://www.cruden.com/automotive-driving-simulators/. Accessed 14 Apr 2020
Model.CONNECT™.: IODP Portfolio, 2020. https://www.avl.com/web/guest/-/model-connect. Accessed 14 Apr 2020
VTD—VIRES Virtual Test Drive, 2020. https://vires.com/vtd-vires-virtual-test-drive/. Accessed 14 Apr 2020
AVL VSM™ vehicle simulation, 2020. https://www.avl.com/-/avl-vsm-4. Accessed 14 Apr 2020
Holzinger, J., Schöggl, P., Schrauf, M., et al.: Objective assessment of driveability while automated driving. ATZ Worldw. 116(12), 24–29 (2014). https://doi.org/10.1007/s38311-014-0250-8
Klüver, M., Herrigel, C., Heinrich, C., et al.: The behavioral validity of dual-task driving performance in fixed and moving base driving simulators. Trans. Res. Part F Traffic Psychol. Behav. 37, 78–96 (2016). https://doi.org/10.1016/j.trf.2015.12.005
Stanney, K.M., Kennedy, R.S., Drexler, J.M., et al.: Motion sickness and proprioceptive aftereffects following virtual environment exposure. Appl. Ergonom. 30(1), 27–38 (1999). https://doi.org/10.1016/S0003-6870(98)00039-8
Index, The NASA TLX Tool: Task Load TLX @ NASA Ames—Home, 2020. https://humansystems.arc.nasa.gov/groups/TLX/. Accessed 14 Apr 2020
Jordan, P.W., Thomas, B., McClelland, I.L., et al.: Usability Evaluation in Industry. Chapman and Hall/CRC, Boca Raton (2014)
UNESCO Institute for Statistics, 2012. International standard classification of education. ISCED 2011. UNESCO Institute for Statistics, Montreal, Quebec
Vallat, R.: pingouin.rm_anova—pingouin 0.3.3 documentation, 2020. https://pingouin-stats.org/generated/pingouin.rm_anova.html. Accessed 25 Mar 2020
De Winter, J., Van-Leeuwen, P.M., Happee, R.: Advantages and Disadvantages of Driving Simulators: A Discussion (2012)
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The project leading to this chapter has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 723324.
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Clement, P., Danzinger, H., Quinz, P., Hillbrand, B., Hartavi, A.E., Kasikci, K.Z. (2021). Assessment Concept for TrustVehicles. In: Watzenig, D., Schicker, LM. (eds) Enhanced Trustworthiness and End User Acceptance of Conditionally Automated Vehicles in the Transition Period. Lecture Notes in Intelligent Transportation and Infrastructure. Springer, Cham. https://doi.org/10.1007/978-3-030-60861-3_6
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