Abstract
One demand for road is the ensurance of self-explaining, under which means road users can make correct subjective classifications and expectations of road environment. Based on quantification of driver’s driving cognitive behavior and the self- explaining road theory, this paper designs road environments with different self-interpretation levels as experimental scenes. Through a driving simulation experiment, the changing process of driver’s cognitive workload level is simulated based on Hidden Markov Model. The Hidden Markov Model identifies the driving intention under the combined working conditions, thereby judging driving awareness of the road environment, and evaluating the self-interpretation level of each experimental scene.
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References
Nagayama Y (1978) Role of visual perception in driving. Iatss Research
Mazet C, Dubois D (1988) Mental organizations of road situations: theory of cognitive categorization and methodological consequences. In: SWOV conference: traffic safety theory and research methods. Amsterdam (1988)
Theeuwes J, Godthelp H (1995) Self-explaining roads. Saf Sci 19(2–3):217–225
Brackstone MA, Waterson BJ (2004) Are we looking where we are going? An exploratory examination of eye movement in high speed driving. In: Meeting of the Transportation Research Board
Ranney TA (1994) Models of driving behavior: a review of their evolution. Accid Anal Prev 26(6):733
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Wang, W., Hou, S., Jiang, X., Cheng, Q. (2020). Research on Drivers’ Cognitive Level at Different Self-explaining Intersections. In: Wang, W., Baumann, M., Jiang, X. (eds) Green, Smart and Connected Transportation Systems. Lecture Notes in Electrical Engineering, vol 617. Springer, Singapore. https://doi.org/10.1007/978-981-15-0644-4_64
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DOI: https://doi.org/10.1007/978-981-15-0644-4_64
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