single-jc.php

JACIII Vol.16 No.1 pp. 96-107
doi: 10.20965/jaciii.2012.p0096
(2012)

Paper:

A Study on the Possibility of Applying Subliminal Visual Cue for Guiding Subject’s Attention

Hiroshi Takahashi and Hirohiko Honda

Shonan Institute of Technology, 1-1-25 Tsujido-Nishikaigan, Fujisawa, Kanagawa 251-8511, Japan

Received:
May 23, 2011
Accepted:
October 13, 2011
Published:
January 20, 2012
Keywords:
driver assistance systems, human machine interaction, subliminal perception, attention guidance
Abstract
This paper presents a new warning method for increasing drivers’ sensitivity for recognizing hazardous factors in the driving environment. The method is based on a subliminal effect. In this study, the presentation of a visual cue at a lower contrast ratio than that of the background scenery was investigated as subliminal visual information instead of flashing information quickly. This method was chosen in consideration of its use in real-world driving situations where changes in ambient brightness are among the biggest visual disturbances experienced by drivers. Accordingly, it is necessary to have amethod that is applicable in the context of dynamic changes in brightness. The results of many experiments performed with a threedimensional head-mounted display show that the response time for detecting a flashing mark tended to decrease when a subliminal mark was shown in advance. A priming effect is observed for subliminal visual information. This paper also proposes a scenario for implementing this method in real vehicles.
Cite this article as:
H. Takahashi and H. Honda, “A Study on the Possibility of Applying Subliminal Visual Cue for Guiding Subject’s Attention,” J. Adv. Comput. Intell. Intell. Inform., Vol.16 No.1, pp. 96-107, 2012.
Data files:
References
  1. [1] D. Bruin, J. Kroon, R. Klaveren et al., “Design and Test of a Cooperative Adaptive Cruise Control System,” Proc. of 2004 IEEE Intelligent Vehicles Symposium, pp. 392-396, 2004.
  2. [2] S. Ishida et al., “Development, Evaluation and Introduction of a Lane Keeping Assistance System,” Proc. of 2004 IEEE Intelligent Vehicles Symposium, pp. 943-945, 2004.
  3. [3] F. Tsuji et al., “Development of a Support System for Nighttime Recognition of Pedestrians,” Preprint of JSAE Scientific Lecture Series, 20055287, 2005.
  4. [4] Y. Sato and E. Kato, “An estimation of the hazard-controllability of Distance Warning System (DWS’s) for motor vehicles,” Int. Symposium on Automobile Technique & Automation, 94SF009, pp. 81-88, 1994.
  5. [5] A. Ishibashi, “Human Factors and Error Countermeasures,” J. of National Institute of Public Health, Vol.51, No.4, pp. 232-244, 2002.
  6. [6] G. J. S. Wilde, “Target Risk 2: A New Psychology of Safety and Health,” Pde Pubns, 2001.
  7. [7] M. Kokubun et al., “Analysis of Drivers’ Risk Sensitivity Characteristics,” Trans. of the Human Interface Society, Vol.5, No.1, pp. 27-36, 2003.
  8. [8] M. Zimmermann, “Neurophysiology of Sensory Systems,” pp. 68-166, 1977.
  9. [9] T. Norretranders, “The User illusion: Cutting Consciousness Down to Size,” Penguin Groupe (USA), 1999.
  10. [10] J. Karremans, “Beyond vicary’s fantasies: the impact of subliminal priming and brand choice [Electronic Version],” J. of Experimental Social Psychology, Vol.42, pp. 792-798, 2006.
  11. [11] E. Bertolazzi, F. Biral, M. Da Lio et al., “Supporting Drivers in Keeping Safe Speed and Safe Distance: The SASPENCE Subproject Within the European Framework Programme 6 Integrating Project PReVENT,” IEEE Trans. on Intelligent Transportation Systems, Vol.99, pp. 1-14, 2009.
  12. [12] H. Okuyama, “Emergency Brake of Collision Mitigation System: Pre-Crash Safety system for Large Tracks,” IEICE technical report, Vol.106, No.519, pp. 5-8, 2007.
  13. [13] H. Takahashi, “A Problem and Breakthrough of Environmental Sensing for Vehicles,” The 25th Annual Conf. of the Robotics Society of Japan, 2E11/ JSAE20074523, 2007 (in Japanese).
  14. [14] M. Brackstone and M. McDonald, “Barriers to motorway traffic operations and their potential solution,” Proc., IV2001, pp. 221-226, 2001.
  15. [15] T. Acarman, U. Ozguner et al., “Non-standard safety enhancement,” Proc. IV2001, pp. 417-422, 2001.
  16. [16] H. Takahashi, H. Nishiuchi, and H. Sato, “Error detections for vision based vehicle detection,” Proc. Annual Conf. of Japan J. Industrial and Applied Mathematics, pp. 107-114, 2002.
  17. [17] J. D. Moss and E. R. Muth, “Characteristics of Head-Mounted Displays and Their Effects on Simulator Sickness Human Factors,” The J. of the Human Factors and Ergonomics Society June 2011, 53, pp. 308-319, first published on April 27, 2011.
  18. [18] B. Kolb and I. Q. Whishaw, “Fundamentals of Human Neuropsychology,” Worth Pub, Washington, U.S.A., 2003.
  19. [19] E. Rosen and U. Sander, “Pedestrian fatality risk as a function of car impact speed,” J. of Accident Analysis and Prevention, Vol.41, No.3, pp. 536-542, 2009.
  20. [20] H. Takahashi et al., “A Study on Predicting Hazard Factors for Safe Driving,” IEEE Trans. on Industrial Electronics, Vol.54, No.2, pp. 781-789, 2007.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Apr. 18, 2024