为了避免现有驾驶分心研究方法的局限性，从注意力需求角度入手，探索了高速跟车过程中驾驶人安全驾驶所需的最低视觉注意力。在驾驶模拟器上进行试验，记录26名驾驶人在正常驾驶和视线遮挡驾驶2种状态下的视觉行为和视线遮挡行为数据，并进行统计分析。考虑驾驶人个体差异，初步探索了最低视觉注意力需求分布。结果表明：高速跟车驾驶状态下，驾驶人可以不需观察周围交通信息安全行驶35 m左右，视线遮挡距离与车速无关，可用于表征注意力需求。视线遮挡距离和遮挡频率存在个体差异，但驾驶人总体遮挡百分比基本不变。高速跟车过程中驾驶人的剩余注意力主要用于观察道路前方和其他区域。具体表现为视线遮挡驾驶状态下驾驶人对道路前方和其他区域的观察距离显著缩短，而观察频率基本不变，且仅需行驶25 m左右的时间驾驶人即可完成观察周围交通状况，说明观察频率对获取交通信息更为重要。驾驶人平均每行驶20~60 m（1.0~2.8 s）需要观察前方道路一次，每行驶80~220 m（4.1~8.6 s）需要观察车速表一次，每行驶140~300 m（6.7~13.5s）需要观察后视镜一次，每50~200 m（2.5~9.1 s）可以遮挡视线一次，但遮挡距离一般小于43.7 m（约2.4 s）。研究结果有助于提高分心预警系统的环境敏感性和车内人机界面设计的合理性。
Abstract
To avoid the limitations of current research methods for driving distraction, we explored the minimum required visual attention for safe driving under car-following condition on highway from the perspective of attention demand. An experiment was carried out on a driving simulator to record the visual behavior and vision occlusion data of 26 drivers under both normal and occluded driving conditions. An analysis of occlusion behavior and the difference of the visual behavior under the two driving conditions were conducted. The results show that safe driving can be achieved at about 35 m without sampling traffic information under car-following conditions on highway. The occlusion distance was independent of speed and can be used as an indicator of attention demand. Although there were individual differences in occlusion distance and occlusion frequencies, the drivers' overall occlusion percentage remained relatively stable. In combination with the results of visual behavior analysis, the drivers' spare capacity under car-following conditions on highway was mainly used to observe the forward road and other areas. Specifically, the drivers' glance distance to forward road and other areas were significantly shorter under conditions of vision occlusion, whereas the glance frequency did not change significantly. In addition, the drivers could sample sufficient information within only about 25m, which indicates that the glance frequency is more important for information sampling. In consideration of individual differences, the distribution of the minimum required visual attention was primarily explored. In addition, the pattern was set based on the results:the forward road, speedometer, and mirror need to be observed within at least less than 20-60 m (1.0-2.8 s), 80-220 m (4.1-8.6 s), and 140-300 m (6.7-13.5 s), respectively. In addition, the drivers could have a chance to occlude themselves every 50-200 m (2.5-9.1 s); however, the occlusion distance should be less than 43.7 m (2.4 s). The findings from this research can be utilized in context-sensitive distraction mitigation systems and better design of human-machine interface.
关键词
交通工程 /
驾驶分心 /
模拟驾驶试验 /
驾驶人注意力 /
视线遮挡 /
视觉行为
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Key words
traffic engineering /
driving distraction /
simulation driving test /
driver attention /
vision occlusion /
visual behavior
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中图分类号：
U491.254
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参考文献
[1] KLAUER S G,DINGUS T A,NEALE V L, et al. The Impact of Driver Inattention on Near-crash/Crash Risk:An Analysis Using the 100-Car Naturalistic Driving Study Data.Washington DC:NHTSA, 2006.
[2] MCEVOY S P, STEVENSON M R, WOODWARD M. The Impact of Driver Distraction on Road Safety:Results from a Representative Survey in Two Australian States[J]. Injury Prevention, 2006, 12(4):242-247.
[3] REGAN M A, STRAYER D L. Towards an Understanding of Driver Inattention:Taxonomy and Theory.[J]. Annals of Advances in Automotive Medicine, 2014, 58:5-14.
[4] YOUNG R A. A Tabulation of Driver Distraction Definitions[R]. Toyota:Toyota Collaborative Safety Research Center, 2012:1-24.
[5] FOLEY J P, YOUNG R, ANGELL L, et al. Towards Operationalizing Driver Distraction[C]//BOYLE L, CARNEY C, LEE J D, et al. Driving Assessment 2013:Proceedings of the 7th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design. Iowa City:University of Iowa, 2013:57-63.
[6] REGAN M A, HALLETT C, GORDON C P. Driver Distraction and Driver Inattention:Definition, Relationship and Taxonomy[J]. Accident Analysis & Prevention, 2011, 43(5):1771-1781.
[7] HORBERRY T, ANDERSON J, REGAN M A, et al. Driver Distraction:The Effects of Concurrent In-vehicle Tasks, Road Environment Complexity and Age on Driving Performance[J]. Accident Analysis & Prevention, 2006, 38(1):185-191.
[8] ROCKWELL T H. Spare Visual Capacity in Driving-revisited:New Empirical Results for an Old Idea[C]//International Ergonomics Association.Vision in Vehicles Ⅱ. Proceedings of the Second International Conference on Vision in Vehicles. Burlington:Elsevier, 1988:317-324.
[9] AHLSTROM C, KIRCHER K. Review of Real-time Visual Driver Distraction Detection Algorithms[C]//ACM. Proceedings of the 7th International Conference on Methods and Techniques in Behavioral Research. New York:ACM, 2010:310-313.
[10] LEE J D, MOECKLI J, BROWN T, et al. Detection of Driver Distraction Using Vision-based Algorithms//NHTSA. Proceedings of the 23rd International Technical Conference on the Enhanced Safety of Vehicles (ESV). Washington DC:NHTSA, 2013:1-10.
[11] LIANG Y, LEE J D, YEKHSHATYAN L. How Dangerous is Looking Away from the Road? Algorithms Predict Crash Risk from Glance Patterns in Naturalistic Driving[J]. Human Factors, 2012, 54(6):1104-1116.
[12] NHTSA. Visual-manual NHTSA Driver Distraction Guidelines for In-vehicle Electronic Devices[R]. Washington DC:NHTSA, 2012.
[13] 刘卓凡,付锐,程文冬,等.驾驶人视觉分心与认知分心研究综述[J].中国安全科学学报, 2015,25(7):29-34. LIU Zhuo-fan, FU Rui, CHENG Wen-dong, et al. Overview of Researches on Drivers' Visual Distraction and Cognitive Distraction[J]. China Safety Science Journal, 2015, 25(7):29-34.
[14] 马勇,付锐.驾驶人视觉特性与行车安全研究进展[J].中国公路学报,2015,28(6):82-94. MA Yong, FU Rui. Research and Development of Drivers Visual Behavior and Driving Safety[J]. China Journal of Highway and Transport, 2015, 28(6):82-94.
[15] 马艳丽,顾高峰,高月娥,等.基于驾驶绩效的车载信息系统操作分心判定模型[J].中国公路学报,2016,29(4):123-129. MA Yan-li, GU Gao-feng, GAO Yue-e, et al. Driver Distraction Judging Model Under In-vehicle Information System Operation Based on Driving Performance[J]. China Journal of Highway and Transport, 2016, 29(4):123-129.
[16] KIRCHER K, AHLSTROM C. Minimum Required Attention:A Human-centered Approach to Driver Inattention[J]. Human Factors, 2017, 59(3):471-484.
[17] TIVESTEN E, DOZZA M. Driving Context and Visual-manual Phone Tasks Influence Glance Behavior in Naturalistic Driving[J]. Transportation Research Part F, 2014, 26:258-272.
[18] ENGSTRÖM J, BÄRGMAN J, NILSSON D, et al. Great Expectations:A Predictive Processing Account of Automobile Driving[J]. Theoretical Issues in Ergonomics Science, 2018, 19(2):156-194.
[19] SIVAK M. The Information That Drivers Use:Is It Indeed 90% Visual?[J]. Perception, 1996, 25(9):1081-1089.
[20] FULLER R. Towards A General Theory of Driver Behaviour[J]. Accident Analysis & Prevention, 2005, 37(3):461-472.
[21] VAN DER HORST R. Occlusion as a Measure for Visual Workload:An Overview of TNO Occlusion Research in Car Driving[J]. Applied Ergonomics, 2004, 35(3):189-196.
[22] LETHAUS F, RATAJ J. Do Eye Movements Reflect Driving Manoeuvres?[J]. IET Intelligent Transport Systems, 2007, 1(3):199-204.
[23] PETTITT M A, BURNETT G E, BAYER S, et al. Assessment of the Occlusion Technique as a Means for Evaluating the Distraction Potential of Driver Support Systems[J]. IEE Proceedings Intelligent Transport Systems. IET Digital Library, 2006, 153(4):259-266.
[24] PEKKANEN J LAPPI O, ITKONEN T H, et al. Task-difficulty Homeostasis in Car Following Models:Experimental Validation Using Self-paced Visual Occlusion[J]. PLoS One, 2017, 12(1):e0169704.
[25] CHEN H W. A Model of Information Sampling Using Visual Occlusion[D]. Toronto:University of Toronto, 2013.
[26] ISO 15007-1:2014, Road Vehicles-Measurement of Driver Visual Behaviour With Respect to Transport Information and Control Systems-Part 1:Definitions and Parameters[S].
[27] SENDERS J W, KRISTOFFERSON A B, LEVISON W H, et al. The Attentional Demand of Automobile Driving[J]. Highway Research Record, 1966(195):15-33.
[28] WORTELEN B, BAUMANN M, LUDTKE A. Dynamic Simulation and Prediction of Drivers' Attention Distribution[J]. Transportation Research Part F, 2013, 21:278-294.
[29] BROSTRÖM R, BENGTSSON P, AUST M L. Individual Glance Strategies and Their Effect on the NHTSA Visual Manual Distraction Test[J]. Transportation Research Part F, 2016, 36:83-91.
[30] AHLSTROM C, KIRCHER K. Changes in Glance Behaviour when Using a Visual Eco-driving System-A Field Study[J]. Applied Ergonomics, 2017, 58:414-423.
[31] BIRRELL S A, FOWKES M. Glance Behaviours when Using an In-vehicle Smart Driving Aid:A Real-world, On-road Driving Study[J]. Transportation Research Part F, 2014, 22:113-125.
[32] SULLIVAN B, JOHNSON L, ROTHKOPF C A, et al. The Role of Uncertainty and Reward on Eye Movements in a Virtual Driving Task[J]. Journal of Vision, 2012, 12(13):1-17.
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脚注
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基金
国家自然科学基金项目（61473046）；中央高校基本科研业务费专项资金项目（310822161006）；陕西省教育厅专项科研计划项目（16JK1375）
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