Page 347 - 《软件学报》2026年第3期
P. 347

1310                                                       软件学报  2026  年第  37  卷第  3  期


                      request in conditional automation. Electronics, 2020, 9(12): 2087. [doi: 10.3390/electronics9122087]
                 [39]   Yoon SH, Kim YW, Ji YG. The effects of takeover request modalities on highly automated car control transitions. Accident Analysis &
                      Prevention, 2019, 123: 150–158. [doi: 10.1016/j.aap.2018.11.018]
                 [40]   Eriksson  A,  Stanton  NA.  Takeover  time  in  highly  automated  vehicles:  Noncritical  transitions  to  and  from  manual  control.  Human
                      Factors, 2017, 59(4): 689–705. [doi: 10.1177/0018720816685832]
                 [41]   Jarosch O, Kuhnt M, Paradies S, Bengler K. It’s out of our hands now! Effects of non-driving related tasks during highly automated
                      driving on drivers’ fatigue. In: Proc. of the 9th Int’l Driving Symp. on Human Factors in Driver Assessment, Training and Vehicle
                      Design. 2017. 319–325.
                 [42]   Chen HL, Zhao XH, Li ZL, Li HJ, Gong JG, Wang QH. Study on the influence factors of takeover behavior in automated driving based
                      on survival analysis. Transportation Research Part F: Traffic Psychology and Behaviour, 2023, 95: 281–296. [doi: 10.1016/j.trf.2023.04.
                      012]
                 [43]   Lin QF, Lyu Y, Zhang KF, Ma XW. Effects of non-driving related tasks on readiness to take over control in conditionally automated
                      driving. Traffic Injury Prevention, 2021, 22(8): 629–633. [doi: 10.1080/15389588.2021.1969373]
                 [44]   Griffith M, Akkem R, Maheshwari J, Seacrist T, Arbogast KB, Graci V. The effect of a startle-based warning, age, sex, and secondary
                      task on takeover actions in critical autonomous driving scenarios. Frontiers in Bioengineering and Biotechnology, 2023, 11: 1147606.
                      [doi: 10.3389/fbioe.2023.1147606]
                 [45]   Li CM, Li XN, Lv M, Chen F, Ma XX, Zhang L. How does approaching a lead vehicle and monitoring request affect drivers’ takeover
                      performance? A simulated driving study with functional MRI. Int’l Journal of Environmental Research and Public Health, 2021, 19(1):
                      412. [doi: 10.3390/ijerph19010412]
                 [46]   Wang QH, Chen HL, Gong JG, Zhao XH, Li ZL. Studying driver’s perception arousal and takeover performance in autonomous driving.
                      Sustainability, 2022, 15(1): 445. [doi: 10.3390/su15010445]
                 [47]   Li  S,  Blythe  P,  Guo  WH,  Namdeo  A.  Investigating  the  effects  of  age  and  disengagement  in  driving  on  driver’s  takeover  control
                      performance in highly automated vehicles. Transportation Planning and Technology, 2019, 42(5): 470–497. [doi: 10.1080/03081060.
                      2019.1609221]
                 [48]   Harari RE, Lamb R, Fathi R, Hulme K. Virtual reality tour for first-time users of highly automated cars: Comparing the effects of virtual
                      environments with different levels of interaction fidelity. Applied Ergonomics, 2021, 90: 103226. [doi: 10.1016/j.apergo.2020.103226]
                 [49]   Zhou HP, Itoh M, Kitazaki S. How does explanation-based knowledge influence driver take-over in conditional driving automation?
                      IEEE Trans. on Human-machine Systems, 2021, 51(3): 188–197. [doi: 10.1109/THMS.2021.3051342]
                 [50]   Feldhütter A, Kroll D, Bengler K. Wake up and take over! The effect of fatigue on the take-over performance in conditionally automated
                      driving. In: Proc. of the 21st Int’l Conf. on Intelligent Transportation Systems (ITSC). Maui: IEEE, 2018. 2080–2085. [doi: 10.1109/
                      ITSC.2018.8569545]
                 [51]   Jarosch O, Bellem H, Bengler K. Effects of task-induced fatigue in prolonged conditional automated driving. Human Factors, 2019,
                      61(7): 1186–1199. [doi: 10.1177/0018720818816226]
                 [52]   Rangesh A, Deo N, Greer R, Gunaratne P, Trivedi MM. Predicting take-over time for autonomous driving with real-world data: Robust
                      data augmentation, models, and evaluation. arXiv:2107.12932, 2021.
                 [53]   Guettas A, Ayad S, Kazar O. Driver state monitoring system: A review. In: Proc. of the 4th Int’l Conf. on Big Data and Internet of
                      Things. Rabat: ACM, 2019. 28. [doi: 10.1145/3372938.3372966]
                 [54]   Lu ZJ, de Winter JCF. A review and framework of control authority transitions in automated driving. Procedia Manufacturing, 2015, 3:
                      2510–2517. [doi: 10.1016/j.promfg.2015.07.513]
                 [55]   Petermeijer SM, de Winter JCF, Bengler KJ. Vibrotactile displays: A survey with a view on highly automated driving. IEEE Trans. on
                      Intelligent Transportation Systems, 2016, 17(4): 897–907. [doi: 10.1109/TITS.2015.2494873]
                 [56]   Borowsky A, Zangi N, Oron-Gilad T. Interruption management in the context of take-over-requests in conditional driving automation.
                      IEEE Trans. on Human-machine Systems, 2022, 52(5): 1015–1024. [doi: 10.1109/THMS.2022.3194006]
                 [57]   Zeeb K, Buchner A, Schrauf M. What determines the take-over time? An integrated model approach of driver take-over after automated
                      driving. Accident Analysis & Prevention, 2015, 78: 212–221. [doi: 10.1016/j.aap.2015.02.023]
                 [58]   Wickens CD. Multiple resources and mental workload. Human Factors, 2008, 50(3): 449–455. [doi: 10.1518/001872008X288394]
                 [59]   Meteier Q, Capallera M, Ruffieux S, Angelini L, Abou Khaled O, Mugellini E, Widmer M, Sonderegger A. Classification of drivers’
                      workload using physiological signals in conditional automation. Frontiers in Psychology, 2021, 12: 596038. [doi: 10.3389/fpsyg.2021.
                      596038]
                 [60]   Kim J, Kim HS, Kim W, Yoon D. Take-over performance analysis depending on the drivers’ non-driving secondary tasks in automated
                      vehicles. In: Proc. of the 2018 Int’l Conf. on Information and Communication Technology Convergence (ICTC). Jeju: IEEE, 2018.
                      1364–1366. [doi: 10.1109/ICTC.2018.8539431]
                 [61]   Kim J, Kim HS, Kim W, Lee SJ, Yoon D. Investigation on the effect of mental workload on the time-related take-over performance. In:
   342   343   344   345   346   347   348   349   350   351   352