Eye-Tracking Evaluation of Exit Advance Guide Signs in Highway Tunnels in Familiar and Unfamiliar Drivers.

Markov chain exit advance guide sign eye-tracking evaluation familiar and unfamiliar drivers highway tunnel safety

Journal

International journal of environmental research and public health
ISSN: 1660-4601
Titre abrégé: Int J Environ Res Public Health
Pays: Switzerland
ID NLM: 101238455

Informations de publication

Date de publication:
25 06 2021
Historique:
received: 15 05 2021
revised: 21 06 2021
accepted: 23 06 2021
entrez: 2 7 2021
pubmed: 3 7 2021
medline: 4 8 2021
Statut: epublish

Résumé

As a component of the traffic control plan, traffic signs on highways offer drivers necessary information. Unfortunately, many signs are unfamiliar to or misunderstood by drivers, especially when lacking a setting method; this includes exit advance guide signs in tunnels. These are generally set in roadbed sections, but space limitations in tunnels dictate that they must be set differently. To evaluate the effect of the setting method, an experiment was designed and conducted, during which the eye movements of 44 drivers with different familiarity levels were tracked. Twenty-two of the drivers had not previously participated in any experiment involving exit advance guide signs in highway tunnels, while 22 of them had. Time period data were analyzed, including data from before the sign appeared, when it appeared, and when it disappeared. Based on area division and Markov theory, attributes related to gaze transition were obtained, including one- and two-step gaze transition probabilities and area gaze probabilities. The results showed that gaze transition was confirmed to be significantly different between the three periods and between the drivers. Features extracted from eye movement characteristics, gaze transition paths, and gaze areas demonstrated that visual attention is more dispersed in familiar drivers during the lane-change intention period. Therefore, signs should be placed on the left wall of the highway tunnel.

Identifiants

pubmed: 34202025
pii: ijerph18136820
doi: 10.3390/ijerph18136820
pmc: PMC8297310
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

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Auteurs

Ting Shang (T)

School of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China.

Hao Lu (H)

School of Economics & Management, Chongqing Jiaotong University, Chongqing 400074, China.

Peng Wu (P)

School of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China.

Yi Wei (Y)

School of Economics & Management, Chongqing Jiaotong University, Chongqing 400074, China.

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Classifications MeSH