doi:

DOI: 10.3724/SP.J.1042.2020.00150

Advances in Psychological Science (心理科学进展) 2020/28:1 PP.150-160

The human factors of the take-over process in conditional automated driving based on cognitive mechanism


Abstract:
Automated driving can largely reduce modern traffic problems and improve driving comfort. During conditional automated driving (Level 3), drivers are allowed to engage in non-driving related tasks but need to take over the vehicle timely once the system reached its limitation. In this critical process, drivers have to shift their attention and acquire situational awareness in order to take over successfully. Existing studies have shown that take-over requests, non-driving related tasks, driving situations and driver-related factors were all critical factors in the take-over process. In the future, we can investigate the cognitive mechanism of the influence of various factors on the take-over process and explore possible interactions between these factors.

Key words:automated driving,take-over process,attention,situation awareness

ReleaseDate:2019-12-28 14:18:58



克里斯托弗D·威肯斯, 贾斯廷G·霍兰兹, 西蒙·班伯里, 雷杰·帕拉休拉曼. (2014). 工程心理学与人的作业 (张侃主译). 北京:机械工业出版社.

周荣刚. (2014). 驾驶中移动电话的使用:基于自我调整行为的研究视角. 心理科学进展, 22(8), 1328-1337.

Bazilinskyy, P., & de Winter, J. C. F. (2015). Auditory interfaces in automated driving:an international survey. Peer J Computer Science, 1, e13.

Bazilinskyy, P., & de Winter, J. C. F. (2017). Analyzing crowdsourced ratings of speech-based take-over requests for automated driving. Applied Ergonomics, 64, 56-64.

Bazilinskyy, P., Petermeijer, S. M., Petrovych, V., Dodou, D., & de Winter, J. C. F. (2018). Take-over requests in highly automated driving:a crowdsourcing survey on auditory, vibrotactile, and visual displays. Transportation Research Part F:Traffic Psychology and Behaviour, 56, 82-98.

Beattie, D., Baillie, L., & Halvey, M. (2015). A comparison of artificial driving sounds for automated vehicles. In Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 451-462). New York, NY, USA:Association Computing Machinery.

Begg, D. (2014). A 2050 vision for London:what are the implications of driverless transport? Retrieved from https://trid.trb.org/view/1319762.

Belz, S. M., Robinson, G. S., & Casali, J. G. (1999). A new class of auditory warning signals for complex systems:auditory icons. Human Factors:The Journal of the Human Factors and Ergonomics Society, 41(4), 608-618.

Borojeni, S. S., Chuang, L., Heuten, W., & Boll, S. (2016). Assisting drivers with ambient take-over requests in highly automated driving. In P. Green, S. Boll, G. Burnett, J. Gabbard, & S. Osswald (Eds.), Proceedings of the 8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (pp. 237-244). New York, NY, USA:Assoc Computing Machinery.

Bueno, M., Dogan, E., Selem, F. H., Monacelli, E., Boverie, S., & Guillaume, A. (2016). How different mental workload levels affect the take-over control after automated driving. In 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC) (pp. 2040-2045). New York, NY, USA:IEEE.

Choi, J. K., & Ji, Y. G. (2015). Investigating the importance of trust on adopting an autonomous vehicle. International Journal of Human-Computer Interaction, 31(10), 692-702.

Clark, H., McLaughlin, A. C., Williams, B., & Feng, J. (2017). Performance in takeover and characteristics of non-driving related tasks during highly automated driving in younger and older drivers. Proceedings of the Human Factors and Ergonomics Society Annual Meeting (pp. 37-41). Santa Monica, CA:Human Factors and Ergonomics Society.

de Winter, J. C. F., Happee, R., Martens, M. H., & Stanton, N. A. (2014). Effects of adaptive cruise control and highly automated driving on workload and situation awareness:a review of the empirical evidence. Transportation Research Part F:Traffic Psychology and Behaviour, 27, 196-217.

Endsley, M. (1995). Toward a theory of situation awareness in dynamic systems. Human Factors, 37(1), 32-64.

Eriksson, A., Banks, V. A., & Stanton, N. A. (2017). Transition to manual:comparing simulator with on-road control transitions. Accident Analysis & Prevention, 102, 227-234.

Forster, Y., Naujoks, F., Neukum, A., & Huestegge, L. (2017). Driver compliance to take-over requests with different auditory outputs in conditional automation. Accident Analysis & Prevention, 109, 18-28.

Gold, C., Berisha, I., & Bengler, K. (2015). Utilization of drivetime-performing non-driving related tasks while driving highly automated. Proceedings of the Human Factors and Ergonomics Society Annual Meeting (pp. 1666-1670). Santa Monica, CA:Human Factors and Ergonomics Society.

Gold, C., Damböck, D., Lorenz, L., & Bengler, K. (2013). "Take over!" how long does it take to get the driver back into the loop? Proceedings of the Human Factors and Ergonomics Society Annual Meeting (pp. 1938-1942). Santa Monica, CA:Human Factors and Ergonomics Society.

Gold, C., Körber, M., Hohenberger, C., Lechner, D., & Bengler, K. (2015). Trust in automation-before and after the experience of take-over scenarios in a highly automated vehicle. In T. Ahram, W. Karwowski, & D. Schmorrow (Eds.), In Procedia Manufacturing 6th International Conference on Applied Human Factors and Ergonomics (AHFE) and the Affiliated Conferences (Vol. 3, pp. 3025-3032). Amsterdam:Elsevier.

Gold, C., Körber, M., Lechner, D., & Bengler, K. (2016). Taking over control from highly automated vehicles in complex traffic situations:the role of traffic density. Human Factors, 58(4), 642-652.

Gugerty, L. J. (1997). Situation awareness during driving:explicit and implicit knowledge in dynamic spatial memory. Journal of Experimental Psychology Applied, 3(1), 42-66.

Ito, T., Takata, A., & Oosawa, K. (2016). Time required for take-over from automated to manual driving (No.2016-01-0158). SAE Technical Paper Series. Retrieved from http://papers.sae.org/2016-01-0158.

Jamson, A. H., Merat, N., Carsten, O. M., & Lai, F. C. (2013). Behavioural changes in drivers experiencing highly-automated vehicle control in varying traffic conditions. Transportation Research Part C:Emerging Technologies, 30, 116-125.

Kiefer, R. J., Flannagan, C. A., & Jerome, C. J. (2006). Time-to-collision judgments under realistic driving conditions. Human Factors:The Journal of the Human Factors and Ergonomics Society, 48(2), 334-345.

Körber, M., Gold, C., Lechner, D., & Bengler, K. (2016). The influence of age on the take-over of vehicle control in highly automated driving. Transportation Research Part F:Traffic Psychology & Behaviour, 39, 19-32.

Körber, M., Prasch, L., & Bengler, K. (2018). Why do I have to drive now? Post hoc explanations of takeover requests. Human factors, 60(3), 305-323.

Kyriakidis, M., Happee, R., & de Winter, J. C. F. (2015). Public opinion on automated driving:results of an international questionnaire among 5000 respondents. Transportation Research Part F:Traffic Psychology and Behaviour, 32, 127-140.

Langlois, S., & Soualmi, B. (2016). Augmented reality versus classical HUD to take over from automated driving:an aid to smooth reactions and to anticipate maneuvers. In Proceedings of the 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC) (pp.1571-1578). New York, NY:IEEE.

Lorenz, L., Kerschbaum, P., & Schumann, J. (2014). Designing take-over scenarios for automated driving:how does augmented reality support the driver to get back into the loop? In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (pp. 1681-1685). Santa Monica, CA:Human Factors and Ergonomics Society.

Lu, Z., Coster, X., & de Winter, J. C. F. (2017). How much time do drivers need to obtain situation awareness? a laboratory-based study of automated driving. Applied Ergonomics, 60, 293-304.

Meng, F., & Spence, C. (2015). Tactile warning signals for in-vehicle systems. Accident Analysis & Prevention, 75, 333-346.

Miller, D., Sun, A., Johns, M., Ive, H., Sirkin, D., Aich, S., & Ju, W. (2015). Distraction becomes engagement in automated driving. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (pp. 1676-1680). Santa Monica, CA:Human Factors and Ergonomics Society.

Mok, B. K. J., Johns, M., Lee, K. J., Miller, D., Sirkin, D., Ive, P., & Ju, W. (2015). Emergency, automation off:unstructured transition timing for distracted drivers of automated vehicles. In 2015 IEEE Conference on Intelligent Transportation Systems (ITSC) (pp. 2458-2464). New York, NY:IEEE.

Naujoks, F., Forster, Y, Wiedemann, K., & Neukum, A. (2017). A human-machine interface for cooperative highly automated driving. N.A. Stanton, S. Landry, G. DiBucchianico, & A. Vallicelli (Eds.), Advances in Human Aspects of Transportation:Vol. 484:Advanced in Intelligent System and Computing (pp.585-595). Cham, Switzerland:Springer.

Neubauer, C., Matthews, G., & Saxby, D. (2012). The effects of cell phone use and automation on driver performance and subjective state in simulated driving. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (pp. 1987-1991). Santa Monica, CA:Human Factors and Ergonomics.

Parasuraman, R., & Riley, V. (1997). Humans and automation:use, misuse, disuse, abuse. Human Factors:The Journal of the Human Factors and Ergonomics Society, 39(2), 230-253.

Petermeijer, S. M., Bazilinskyy, P., Bengler, K., & de Winter, J. C. F. (2017). Take-over again:investigating multimodal and directional tors to get the driver back into the loop. Applied Ergonomics, 62, 204-215.

Petermeijer, S. M., Cieler, S., & de Winter, J. C. F. (2017). Comparing spatially static and dynamic vibrotactile take-over requests in the driver seat. Accident Analysis & Prevention, 99, 218-227.

Petermeijer, S. M., de Winter, J. C. F., & Bengler, K. J. (2016). Vibrotactile displays:a survey with a view on highly automated driving. IEEE Transactions on Intelligent Transportation Systems, 17(4), 897-907.

Petermeijer, S. M., Doubek, F., & de Winter, J. C. F. (2017). Driver response times to auditory, visual, and tactile take-over requests:a simulator study with 101 participants. In A. Basu, W. Pedrycz, & X. Zabuli (Eds.), Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp.1505-1510). Banff, Canada:IEEE.

Petermeijer, S. M., Hornberger, P., Ganotis, I., de Winter, J. C. F., & Bengler, K. J. (2017). The design of a vibrotactile seat for conveying take-over requests in automated driving. In N. A. Stanton (Eds.), Advances in Intelligent Systems and Computing (pp. 618-630). Cham, Switzerland:Springer.

Politis, I., Brewster, S., & Pollick, F. (2015). Language-based multimodal displays for the handover of control in autonomous cars. In Proceedings of the 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (pp. 3-10). New York, NY, USA:ACM.

Prewett, M. S., Elliott, L. R., Walvoord, A. G., & Coovert, M. D. (2012). A meta-analysis of vibrotactile and visual information displays for improving task performance. IEEE Transactions on Systems, Man and Cybernetic Part C:Applications and Reviews, 42(1), 123-132.

Radlmayr, J., Gold, C., Lorenz, L., Farid, M., & Bengler, K. (2014). How traffic situations and non-driving related tasks affect the take-over quality in highly automated driving. In Proceedings of the Human Factors and Ergonomics Society 58th Annual Meeting (pp. 2063-2067). Santa Monica, CA:Human Factors and Ergonomics.

SAE International. (2016). Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles (Standard No. J3016). Retrieved from https://saemobilus.sae.org/content/j3016_201609.

Samuel, S., Borowsky, A., Zilberstein, S., & Fisher, D. L. (2016). Minimum time to situation awareness in scenarios involving transfer of control from an automated driving suite. Transportation Research Record:Journal of the Transportation Research Board, 2602(1), 115-120.

Scott, J., Gray, R. (2008). A comparison of tactile, visual, and auditory warnings for rear-end collision prevention in simulated driving. Human Factors, 50(2), 264-275.

Summala, H., Lamble, D., Laakso, M. (1998). Driving experience and perception of the lead car's braking when looking at in-car targets. Accident Analysis & Prevention, 30(4), 401-407.

Telpaz, A., Rhindress, B., Zelman, I., & Tsimhoni, O. (2015). Haptic seat for automated driving:preparing the driver to take control effectively. In Proceedings of the 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications-Automotive UI'15 (pp. 23-30). Nottingham, UK:ACM.

Vlakveld, W., van Nes, N., de Bruin, J., Vissers, L., & van der Kroft, M. (2018). Situation awareness increases when drivers have more time to take over the wheel in a Level 3 automated car:a simulator study. Transportation Research Part F:Traffic Psychology and Behaviour, 58, 917-929.

Wan, J. Y., & Wu, C. X. (2018a). The effects of lead time of take-over request and non-driving tasks on taking-over control of automated vehicles. IEEE Transactions on Human-Machine Systems, 48(6), 582-591.

Wan, J. Y., & Wu, C. X. (2018b). The effects of vibration patterns of take-over request and non-driving tasks on taking-over control of automated vehicles. International Journal of Human-Computer Interaction, 34(11), 987-998.

Wang, W. H. (2001). Driving behavior shaping model in road traffic system. Journal of Beijing Institute of Technology, 10(3):331-336.

Wege, C., Will, S., & Victor, T. (2013). Eye movement and brake reactions to real world brake-capacity forward collision warnings-a naturalistic driving study. Accident Analysis & Prevention, 58(3), 259-270.

Wickens, C. D. (2008). Multiple resources and mental workload. Human Factors:The Journal of the Human Factors and Ergonomics Society, 50(3), 449-455.

Wiedemann, K., Naujoks, F., Wörle, J., Kenntner-Mabiala, R., Kaussner, Y., Neukum, A. (2018). Effect of different alcohol levels on take-over performance in conditionally automated driving. Accident Analysis & Prevention, 115, 89-97.

Wintersberger, P., von Sawitzky, T., Frison, A. K., & Riener, A. (2017). Traffic augmentation as a means to increase trust in automated driving systems. In Proceedings of the 12th Biannual Conference on Italian SIGCHI Chapter:Towards the Mediterranean (p. 17). New York, NY:Association for Computing Machinery.

Wright, T. J., Samuel, S., Borowsky, A., Zilberstein, S., & Fisher, D. L. (2016). Experienced drivers are quicker to achieve situation awareness than inexperienced drivers in situations of transfer of control within a level 3 autonomous environment. In Proceedings of the Human Factors and Ergonomics Society 60th Annual Meeting (pp. 270-273). Santa Monica, CA:Human Factors and Ergonomics Society.

Zeeb, K., Buchner, A., & Schrauf, M. (2015). What determines the take-over time? an integrated model approach of driver take-over after automated driving. Accident Analysis & Prevention, 78, 212-221.

Zeeb, K., Buchner, A., & Schrauf, M. (2016). Is take-over time all that matters? the impact of visual-cognitive load on driver take-over quality after conditionally automated driving. Accident Analysis & Prevention, 92, 230-239.