261
Views
0
CrossRef citations to date
0
Altmetric
Research Articles

Driver behavior and mental workload for takeover safety in automated driving: ACT-R prediction modeling approach

ORCID Icon, ORCID Icon & ORCID Icon
Pages 381-389 | Received 21 Nov 2023, Accepted 27 Dec 2023, Published online: 22 Jan 2024

References

  • Anderson JR, Bothell D, Byrne MD, Douglass S, Lebiere C, Qin Y. 2004. An integrated theory of the mind. Psychol Rev. 111(4):1036–1060. doi:10.1037/0033-295X.111.4.1036.
  • Borojeni SS, Wallbaum T, Heuten W, Boll S. 2017. Comparing shape-changing and vibro-tactile steering wheels for take-over requests in highly automated driving. Paper presented at: The Proceedings of the 9th International Conference on Automotive User Interfaces and Interactive Vehicular Applications; Oldenburg, Germany.
  • Bueno M, Dogan E, Selem FH, Monacelli E, Boverie S, Guillaume A. 2016, November. How different mental workload levels affect the take-over control after automated driving. Paper presented at: 2016 IEEE 19th international conference on intelligent transportation systems (ITSC) (pp. 2040–2045); Rio de Janeiro, Brazil.
  • Campbell GE, Bolton AE. 2006. HBR validation: interpreting lessons learned from multiple academic disciplines, applied communities, and the AMBR project. In: Gluck KA, Pew RW, editors. Modeling human behavior with integrated cognitive architectures: comparison, evaluation and validation. Mahwah (NJ): Lawrence Erlbaum & Associates. p. 365–395.
  • Cina M, Rad AB. 2023. Categorized review of drive simulators and driver behavior analysis focusing on ACT-R architecture in autonomous vehicles. Sustainable Energy Technol Assess. 56:103044. doi:10.1016/j.seta.2023.103044.
  • Dargahi Nobari K, Albers F, Bartsch K, Braun J, Bertram T. 2022. Modeling driver-vehicle interaction in automated driving. Forsch Ingenieurwes. 86(1):65–79. doi:10.1007/s10010-021-00576-6.
  • De Waard D. 1996. The measurement of drivers’ mental workload [Thesis]. NL: Groningen Universit, Traffic Research Center.
  • D'Mello S, Graesser A. 2011. The half-life of cognitive-affective states during complex learning. Cogn Emot. 25(7):1299–1308. doi:10.1080/02699931.2011.613668.
  • Du N, Zhou F, Pulver EM, Tilbury DM, Robert LP, Pradhan AK, Yang XJ. 2020. Predicting driver takeover performance in conditionally automated driving. Accid Anal Prev. 148:105748. doi:10.1016/j.aap.2020.105748.
  • Eriksson A, Stanton NA. 2017. Takeover time in highly automated vehicles: noncritical transitions to and from manual control. Hum Factors. 59(4):689–705. doi:10.1177/0018720816685832.
  • Greenlee ET, DeLucia PR, Newton DC. 2018. Driver vigilance in automated vehicles: hazard detection failures are a matter of time. Hum Factors. 60(4):465–476. doi:10.1177/0018720818761711.
  • Hajek W, Gaponova I, Fleischer KH, Krems J. 2013. Workload-adaptive cruise control–A new generation of advanced driver assistance systems. Transport Res Part F Traffic Psychol Behav. 20:108–120. doi:10.1016/j.trf.2013.06.001.
  • Jeong H, Liu Y. 2019. Effects of non-driving-related-task modality and road geometry on eye movements, lane-keeping performance, and workload while driving. Transport Res Part F Traffic Psychol Behav. 60:157–171. doi:10.1016/j.trf.2018.10.015.
  • Jin M, Lu G, Chen F, Shi X, Tan H, Zhai J. 2021. Modeling takeover behavior in level 3 automated driving via a structural equation model: considering the mediating role of trust. Accid Anal Prev. 157:106156. doi:10.1016/j.aap.2021.106156.
  • Jo S, Myung R, Yoon D. 2012. Quantitative prediction of mental workload with the ACT-R cognitive architecture. Int J Ind Ergon. 42(4):359–370. doi:10.1080/14639220210159735.
  • Just MA, Carpenter PA, Miyake A. 2003. Neuroindices of cognitive workload: neuroimaging, pupillometric and event-related potential studies of brain work. Theoret Issues Ergon Sci. 4(1–2):56–88. doi:10.1080/14639220210159735.
  • Kramer AF. 1991. Physiological metrics of mental workload: A review of recent progress. Multiple-task Performance. London (UK): CRC Press. p. 279–328.
  • Lin QF, Lyu Y, Zhang KF, Ma XW. 2021. Effects of non- driving related tasks on readiness to take over control in conditionally automated driving. Traffic Inj Prev. 22(8):629–633. doi:10.1080/15389588.2021.1969373.
  • Mehler B, Reimer B, Coughlin J, Dusek J. 2009. Impact of incremental increases in cognitive workload on physiological arousal and performance in young adult drivers. Transport Res Record. 2138(1):6–12. doi:10.3141/2138-02.
  • Park J, Zahabi M. 2022. A review of human performance models for prediction of driver behavior and interactions with in-vehicle technology. Hum Factors. doi:10.1177/00187208221132740.
  • Rendon-Velez E, Van Leeuwen PM, Happee R, Horváth I, Van der Vegte WF, De Winter JCF. 2016. The effects of time pressure on driver performance and physiological activity: a driving simulator study. Transport Res Part F Traffic Psychol Behav. 41:150–169. doi:10.1016/j.trf.2016.06.013.
  • Ryu K, Myung R. 2005. Evaluation of mental workload with a combined measure based on physiological indices during a dual task of tracking and mental arithmetic. Int J Ind Ergon. 35(11):991–1009. doi:10.1016/j.ergon.2005.04.005.
  • Salvucci DD. 2006. Modeling driver behavior in a cognitive architecture. Hum Factors. 48(2):362–380. doi:10.1518/001872006777724417.
  • Salvucci DD, Taatgen NA. 2008. Threaded cognition: an integrated theory of concurrent multitasking. Psychol Rev. 115(1):101–130. doi:10.1037/0033-295X.115.1.101.
  • Salvucci DD, Gray R. 2004. A two-point visual control model of steering. Perception. 33(10):1233–1248. doi:10.1068/p5343.
  • Scharfe-Scherf MSL, Wiese S, Russwinkel N. 2022. A cognitive model to anticipate variations of situation awareness and attention for the takeover in highly automated driving. Information. 13(9):418. doi:10.3390/info13090418.
  • Society of Automotive Engineer (SAE) International J3016. 2018. Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicle automated driving systems. Warrendale (PA): SAE International.
  • Tan X, Zhang Y. 2022. A computational cognitive model of driver response time for scheduled freeway exiting takeovers in conditionally automated vehicles. Hum Factors. doi:10.1177/00187208221143028.
  • van Leeuwen P, Landman R, Buning L, Heffelaar T, Hogema J, van Hemert JM, de Winter JCF, Happee R. 2017. Towards a real-time driver workload estimator: an on-the-road study. In Advances in human aspects of transportation. Cham: Springer. p. 1151–1164.
  • Wan JY, Wu CX. 2018. The effects of lead time of take-over request and nondriving tasks on taking-over control of automated vehicles. IEEE Trans Human-Mach Syst. 48(6):582–591. doi:10.1109/THMS.2018.2844251.
  • Wandtner B, Schömig N, Schmidt G. 2018. Effects of non-driving related task modalities on takeover performance in highly automated driving. Hum Factors. 60(6):870–881. doi:10.1177/0018720818768199.
  • Wickens CD, Lee JD, Liu Y, Gordon-Becker SE. 2004. An introduction to human factors engineering. Upper Saddle River (NJ): Pearson Prentice Hall.
  • Wu Y, Kihara K, Takeda Y, Sato T, Akamatsu M, Kitazaki S, Nakagawa K, Yamada K, Oka H, Kameyama S. 2021. Eye movements predict driver reaction time to takeover request in automated driving: A real-vehicle study. Transport Res Part F Traffic Psychol Behav. 81:355–363. doi:10.1016/j.trf.2021.06.017.
  • Yoon SH, Lee SC, Ji YG. 2021. Modeling takeover time based on non-driving-related task attributes in highly automated driving. Appl Ergon. 92:103343. doi:10.1016/j.apergo.2020.103343.
  • Zhang B, de Winter J, Varotto S, Happee R, Martens M. 2019. Determinants of take-over time from automated driving: a meta- analysis of 129 studies. Transp Res Part F Traffic Psychol Behav. 64:285–307. doi:10.1016/j.trf.2019.04.020.
  • Zhu J, Ma Y, Zhang Y, Zhang Y, Lv C. 2023. Takeover quality prediction based on driver physiological state of different cognitive tasks in conditionally automated driving. Adv Eng Inf. 57:102100. doi:10.1016/j.aei.2023.102100.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.