A study on the visual recognition patterns of multi-information guide signs based on eye movement data analysis

• Published in: Accident analysis and prevention Vol. 205; p. 107637
• Main Authors: Huang, Lihua, Zhao, Xiaohua, Liuxuan, Lv, Jianhui, Lai
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.09.2024
• Subjects: Adult; Automobile Driving; Eye movement data; Eye Movements; Eye-Tracking Technology; Female; Humans; Indoor experiment; Location Directories and Signs; Male; Multi-information guide signs; Pattern Recognition, Visual - physiology; TOPSIS; Visual Perception; Visual recognition pattern; Young Adult; Eye movement data; Indoor experiment; TOPSIS; Multi-information guide signs; Visual recognition pattern
• ISSN: 0001-4575; 1879-2057; 1879-2057
• DOI: 10.1016/j.aap.2024.107637

•The 28 eye-movement indicators used in the study effectively evaluate drivers’ visual recognition characteristics, capturing microscopic biopsychological features.•An increase in the number of sign road names leads to diminished visual recognition efficiency and heightened visual recognition difficulty and fatigue.•It is advisable to restrict the number of sign road names to a maximum of six per sign under typical circumstances, with nine being the limit under special conditions.•Each type of multi-information sign exhibits its unique visual recognition pattern, with the upper part of the sign layout being easier to recognize and the lower part being more challenging.•The study advises prioritizing road information based on practical usage conditions to minimize visual recognition risks. A two-factor experiment was devised to assess the appropriateness of the quantity and arrangement of information on multi-information guide signs at unique, spacious exits on elevated expressway sections. This experiment investigated 77 signs containing varying amounts of road name information and different placements of destination road names. The research entailed an indoor experiment that incorporated eye-tracking technology and involved the analysis of a total of twenty-eight indicators. A comprehensive index system was developed, identifying three key aspects: visual recognition efficiency, visual recognition difficulty, and visual fatigue. Utilizing repeated measure analysis of variances, the impact of these two factors was examined to identify significant indicators and establish a comprehensive assessment indicator system. The Technique for Order of Preference by Similarity to Ideal Solution method, in conjunction with the coefficient of entropy weight, was employed to assess the effectiveness of these two factors. The findings demonstrated that the 28 eye-movement indicators utilized in this study effectively constitute a valuable indicator system for evaluating drivers’ visual recognition characteristics. These indicators capture the subtle psychophysical traits inherent in the process of recognizing signs, including visual recognition efficiency, difficulty, and fatigue. Regarding the first experimental factor, the number of sign road names significantly influences drivers’ visual recognition characteristics (Sig < 0.05). Specifically, an increase in the number of sign road names leads to diminished visual recognition efficiency and heightened visual recognition difficulty and fatigue. Consequently, it is advisable to restrict the number of sign road names to a maximum of six per sign under typical circumstances, with nine being the limit under special conditions. As for the second experimental factor, the placement of the destination road name within the sign layout exerts a significant impact on visual recognition characteristics (Sig < 0.05). Each type of multi-information sign exhibits a distinct visual recognition pattern. Generally, the upper portion of the sign is more easily recognized, while the lower part poses greater recognition challenges. Therefore, to mitigate visual recognition risks, it is recommended that road information placement be prioritized based on actual usage conditions.