Developing Character Height Model for Tibetan–Chinese Bilingual Guide Signs Using Driving Simulation
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 149, Issue 12
Abstract
As one of Tibet’s most vital traffic safety devices, guide signs are usually Tibetan–Chinese bilingual. Therefore, drivers need effective recognition of Tibetan–Chinese bilingual traffic signs for safe driving. This study aims to determine two design parameters of the Tibetan–Chinese bilingual guide signs: Tibetan character height () and aspect (height to width) ratio. Two highway facilities were selected for the simulation experiment: a general highway intersection and a high-grade highway exit ramp. To incorporate drivers’ visual recognition characteristics, 20 Tibetan drivers and 20 Han drivers were invited to wear head-mounted eye trackers for a dynamic driving simulation experiment of visual identification of guide signs. Four layout designs were used to analyze Tibetan and Han drivers’ visual recognition characteristics. The regression model for was first developed based on the visibility theory of guide signs. Then, the character-height design values for the Tibetan–Chinese bilingual guide signs were established for different speed limits. The results of this study should help to optimize the design of traffic signs in Tibet and improve highway traffic safety.
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Data Availability Statement
All data, models, or code generated or used during the study are proprietary or confidential in nature and may only be provided with restrictions.
Acknowledgments
The authors thank two anonymous reviewers for their thorough and helpful comments. This study is supported by General Program of Natural Science Foundation, Yunnan Province, China (Grant No. 2019FB072) and Shanxi Provincial Innovation Center Project for Digital Road Design Technology (Grant No. 202104010911019).
Author contributions: The authors confirm their contribution to the paper as follows: study conception and design: Fei Chen and Jianchuan Cheng; data collection: Danni Zhang and Chenzhu Wang; supervision: Said Easa; analysis and interpretation of results: Danni Zhang and Wenjie Li; draft manuscript preparation: and Danni Zhang, Fei Chen, Wenjie Li, Chenzhu Wang, and Said Easa. All authors reviewed the results and approved the final version of the manuscript.
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Received: Mar 23, 2023
Accepted: Aug 8, 2023
Published online: Oct 5, 2023
Published in print: Dec 1, 2023
Discussion open until: Mar 5, 2024
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