Traffic Sign Comprehension among Filipino Drivers and Nondrivers in Metro Manila

Author:

Robielos Rex Aurelius C.,Lin Chiuhsiang Joe

Abstract

The current study examined 73 existing traffic signs in Metro Manila for their matching accuracy, matching time, and cognitive design features. A total of 60 Filipinos (30 drivers and 30 nondrivers) were voluntarily recruited to perform a matching-based comprehension test. In a matching-based comprehension test, the traffic sign is matched with the most appropriate referent name which shows a clear-cut distinction between correct and incorrect answers. To assess a sign’s acceptability in a matching test, a level of at least 67% accuracy must be obtained in a comprehension test. For the matching accuracy, 27 of the 73 traffic signs did not comply with the 67% comprehension standard set by ISO 3864-1:2011. Drivers were found to have better matching accuracy for both regulatory and warning signs compared to nondrivers. Traffic signs displayed in symbols had the lowest matching accuracy and slowest matching time. When text was added to traffic signs displayed in symbols, matching accuracy and matching time improved significantly. However, signs displayed in text only obtained the highest matching accuracy and fastest matching time. The cognitive design features, which were the measurement of a sign’s design, were also assessed through their familiarity, concreteness, complexity, and semantic distance. Cognitive design features were found to be positively correlated to matching accuracy for both regulatory and warning signs, but negatively correlated to matching time for warning signs. For signs displayed in symbols, cognitive design features were also found to be correlated to matching accuracy and matching time. To improve comprehension and road safety, semantic distance, concreteness, and familiarity are the key cognitive design features which must be considered by traffic sign designers. Also, the Department of Transportation (Philippines) could adopt the matching test of this study as a mandatory retraining requirement for the renewal of a driver’s license. In addition, our matching-based comprehension test can also be applied and extended to evaluate existing traffic signs worldwide.

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Revolutionizing Signage Analysis: Leveraging YOLOv7 Object Detection for Comprehensive Classification and Assessment of Diverse Signage Types;Proceedings of the 2024 10th International Conference on Computing and Artificial Intelligence;2024-04-26

2. Ergonomic principles of road signs comprehension: A literature review;Transportation Research Part F: Traffic Psychology and Behaviour;2024-02

3. DRIVEMATE: Empowering Safe Driving Through Real-Time Traffic Sign Detection and Speech Feedback on Mobile Devices Using YOLOv5 Algorithm and TensorFlow Lite;Proceedings of the 8th International Conference on Sustainable Information Engineering and Technology;2023-10-24

4. Usability of Certain Symbols Indicating Automobile Safety Status Based on Youth Assessment;Applied Sciences;2023-08-29

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