Artificial IntelligenceNo Access

Research on Visual Cognition About Sharp Turn Sign Based on Driver’s Eye Movement Characteristic

Lidong Li

School of transportation, Wuhan University of Technology, Wuhan 430063, P. R. China

E-mail Address: Lilidong@163.com; support@iassu.science

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and

Qingnian Zhang

School of transportation, Wuhan University of Technology, Wuhan 430063, P. R. China

E-mail Address: zqnwhut@163.com

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https://doi.org/10.1142/S0218001417590121Cited by:9 (Source: Crossref)

Abstract

As a traffic language, sharp turn sign is a kind of important road infrastructure that indicates a sharp turning will show up at the coming road, warning drivers to slow down to ensure the driving safety. In this paper, real vehicle test was carried out on mountain road with an eye tracker equipment. At different driving speeds, parameters of eye movement characteristics in the visual cognition process of sharp turn signs were collected, including distribution of gaze points, fixation and saccade. Simultaneously, driver’s scan paths of recognizing sharp turn signs with different supporting forms were gathered. The results of the analysis of testing data showed that the dispersion of distribution of gaze points would increase with driving velocity. Saccade was the main method for driver to capture information of sharp turn signs. While driving speed was lower than 60km/h, fixation was also one of the methods. For the visual cognition process of sharp turn sign with cantilever, compared to post, the searching scope was wider both in horizontal and vertical directions. This study is beneficial to evaluate the rationality of sharp turn signs, promoting the using efficiency of signs and improving the driving safety on mountain road.

Keywords:

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