基于认知机制的有条件自动驾驶接管中的人因问题

doi:10.3724/SP.J.1042.2020.00150

摘要/Abstract

摘要：

自动驾驶能在很大程度上缓解现代交通问题并提升驾驶舒适度。有条件自动驾驶下, 驾驶员可执行非驾驶相关任务但需要在系统无法处理的状况下接管车辆。在这一关键过程中, 驾驶员需要进行注意转换并获得情境意识以成功接管。已有研究表明, 接管请求、非驾驶相关任务、驾驶情景及驾驶员因素是影响接管过程重要因素。未来可从认知机制角度研究各因素对接管过程产生的影响, 以及探究接管过程中各因素之间可能存在的交互作用。

关键词: 自动驾驶, 接管过程, 注意, 情境意识

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

中图分类号:

B849: U471

马舒, 章薇, 史金磊, 杨振. (2020). 基于认知机制的有条件自动驾驶接管中的人因问题. 心理科学进展 , 28(1), 150-160.

MA Shu, ZHANG Wei, SHI Jinlei, YANG Zhen. (2020). The human factors of the take-over process in conditional automated driving based on cognitive mechanism. Advances in Psychological Science, 28(1), 150-160.

图/表 1

参考文献 60

1	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.
2	周荣刚 . (2017). (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.
3	Bazilinskyy, P., & de Winter,J. C.F . ( 2015). Auditory interfaces in automated driving: An international survey. Peer J Computer Science,1, e13.
4	Bazilinskyy P. & Winter J. C.F, . ( 2017). Analyzing crowdsourced ratings of speech-based take-over requests for automated driving. Applied Ergonomics, 64, 56-64.
5	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.
6	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.
7	Begg ,D.( 2014). A 2050 vision for London: What are the implications of driverless transport? Retrieved from
8	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.
9	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.
10	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.
11	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.
12	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.
13	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.
14	Endsley , M.( 1995). Toward a theory of situation awareness in dynamic systems. Human Factors, 37( 1), 32-64.
15	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.
16	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.
17	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.
18	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.
19	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.
20	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.
21	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.
22	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 .
23	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.
24	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.
25	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.
26	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.
27	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.
28	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.
29	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.
30	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.
31	Meng ,F., &Spence C. , ( 2015). Tactile warning signals for in-vehicle systems. Accident Analysis & Prevention, 75, 333-346.
32	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.
33	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.
34	Naujoks F., Forster, Y, Wiedemann K., & Neukum A . ( 2017). A human-machine interface for cooperative highly automated driving. In 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.
35	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.
36	Parasuraman R., &Riley V. , ( 1997). Humans and automation: Use, misuse, disuse, abuse. Human Factors, 39( 2), 230-253.
37	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.
38	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.
39	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.
40	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.
41	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.
42	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.
43	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.
44	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.
45	SAE International . ( 2016). Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles (Standard No.J3016). Retrieved from
46	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.
47	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.
48	Summala H., Lamble D., Laakso M . ( 1998). Driving experience and perception of the lead car’s braking when looking at in-car targets. Accident Analys is & Prevention, 30( 4), 401-407.
49	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.
50	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.
51	Wan J.Y., &Wu C.X, . ( 2018 a). 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.
52	, 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.
53	Wang W.H . ( 2001). Driving behavior shaping model in road traffic system. Journal of Beijing Institute of Technology, 10( 3), 331-336.
54	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.
55	Wickens C.D . ( 2008). Multiple resources and mental workload. Human Factors, 50( 3), 449-455.
56	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.
57	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.
58	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.
59	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.
60	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.

编辑推荐 0

Metrics

阅读次数

全文

2610

HTML			PDF

最新录用	在线预览	正式出版	最新录用	在线预览	正式出版
0	0	57	0	0	2553

来源	本网站	其他网站

次数	1529	1081
比例	59%	41%

摘要

1156

最新录用	在线预览	正式出版

0	0	1156

来源	本网站	其他网站

次数	1110	46
比例	96%	4%

[1]	贾云丞, 程刚, 丁芳媛, 陈加, 龙女, 陈玉荣, 林楠. 对中性婴儿面孔注意偏向与表情不确定性的关系[J]. 心理科学进展, 2024, 32(9): 1393-1407.
[2]	陈雁, 李晶. 人际同步对孤独症儿童合作行为的影响及干预促进[J]. 心理科学进展, 2024, 32(4): 639-653.
[3]	刘一鸣, 罗浩诚, 傅世敏. 视觉意识是离散还是连续模式?基于注意瞬脱的整合性视角[J]. 心理科学进展, 2024, 32(2): 264-275.
[4]	张湘一, 吴一琳. 视觉注意对决策的影响及其作用机制[J]. 心理科学进展, 2024, 32(11): 1829-1843.
[5]	孙猛, 刘泽军, 贾茜, 尚晨阳, 张钦. 情绪T2对抗注意瞬脱：理解情绪优先加工的窗口[J]. 心理科学进展, 2024, 32(1): 58-74.
[6]	张子霄, 何生, 张杰栋. 注意转移中的知觉抑制[J]. 心理科学进展, 2023, 31(suppl.): 18-18.
[7]	周攀, 刘小燕, 李天添, 王玲. 与位置相关的价值统计学习对注意的影响[J]. 心理科学进展, 2023, 31(suppl.): 51-51.
[8]	裴英名, 任衍具. 与工作记忆保持项目语义相关的干扰对搜索固定与变化目标的影响[J]. 心理科学进展, 2023, 31(suppl.): 75-75.
[9]	邱余波, 潘嘉蔚, 吴静岚, 高在峰. 通过社会注意线索转移工作记忆中的注意焦点[J]. 心理科学进展, 2023, 31(suppl.): 76-76.
[10]	祝松楠, 张琪. 刺激的不同呈现模式下显著干扰物的注意抑制机制[J]. 心理科学进展, 2023, 31(suppl.): 77-77.
[11]	谢燕, 曲折. 工作记忆容量对不同显著性干扰子的抑制功能的调控作用[J]. 心理科学进展, 2023, 31(suppl.): 78-78.
[12]	吴禧芊, 张西磊, 蒋毅, 王亮. 注意是无意识恐惧表达的必要条件：一项视觉ERP研究[J]. 心理科学进展, 2023, 31(suppl.): 79-79.
[13]	郑贵萍, 江镕, 孟明. 多目标追踪过程中刺激眼间切换的注意成本[J]. 心理科学进展, 2023, 31(suppl.): 80-80.
[14]	卢和和, 林子涵, 朱莎莎, 蒋柯. 情绪面孔识别的注意瞬脱效应[J]. 心理科学进展, 2023, 31(suppl.): 83-83.
[15]	肖芬妮, 孟迎芳. 目标探测促进知觉加工?视觉工作记忆中的注意促进效应[J]. 心理科学进展, 2023, 31(suppl.): 86-86.