Traffic sign comprehension plays an important role in road and pedestrian safety. Thus, several studies have already been conducted on traffic sign comprehension, but those studies have focused on different sign factors ranging from driver’s characteristics, display condition, and ergonomic principles, to name a few, that can affect the observed level of comprehension. Currently, no existing framework would comprehensively show the systematic assessment of traffic sign comprehension. To bridge this gap, in this dissertation, the current study identified the influential factors considered in various traffic sign comprehension literature, grouped them into useful categories, and then developed a conceptual framework to comprehensively consolidate how this research field has progressed through the years. The framework consisted of eight categories: Design characteristics, non-Design characteristics, Cognitive Design Features, Evaluation Tool/Equipment, Test Format, Types of Statistical Analysis/Algorithms, Study population, and Target Users. This framework can be used as a guide in conducting future traffic sign comprehension research.
The current study also 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 non-drivers) 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 wrong and correct answers. To assess the signs’ acceptability in a matching test, a level of at least 67% accuracy must be obtained in a comprehension test. For 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 non-drivers. Traffic signs displayed in symbols had the lowest matching accuracy and the slowest matching time. When the 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 that must be considered by traffic sign designers. Also, the Philippines’ Department of Transportation can adopt the matching test of the current 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 the existing traffic signs worldwide.

Traffic sign comprehension plays an important role in road and pedestrian safety. Thus, several studies have already been conducted on traffic sign comprehension, but those studies have focused on different sign factors ranging from driver’s characteristics, display condition, and ergonomic principles, to name a few, that can affect the observed level of comprehension. Currently, no existing framework would comprehensively show the systematic assessment of traffic sign comprehension. To bridge this gap, in this dissertation, the current study identified the influential factors considered in various traffic sign comprehension literature, grouped them into useful categories, and then developed a conceptual framework to comprehensively consolidate how this research field has progressed through the years. The framework consisted of eight categories: Design characteristics, non-Design characteristics, Cognitive Design Features, Evaluation Tool/Equipment, Test Format, Types of Statistical Analysis/Algorithms, Study population, and Target Users. This framework can be used as a guide in conducting future traffic sign comprehension research.
The current study also 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 non-drivers) 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 wrong and correct answers. To assess the signs’ acceptability in a matching test, a level of at least 67% accuracy must be obtained in a comprehension test. For 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 non-drivers. Traffic signs displayed in symbols had the lowest matching accuracy and the slowest matching time. When the 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 that must be considered by traffic sign designers. Also, the Philippines’ Department of Transportation can adopt the matching test of the current 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 the existing traffic signs worldwide.

REFERENCES
Adams, A., Bochner, S., Bilik, L. (1998). The effectiveness of warning signs in hazardous workplaces: Cognitive and social determinants. Applied Ergonomics. 29, 247-254.
Akple, M., Sogbe, E., Atombo, C. (2020). Evaluation of road traffic signs, markings, and traffic rules compliance among drivers in Ghana. Case Studies on Transport Policy.
Al-Madani, H.M.N., Al-Janahi, A.R., Abdul Ghani, A.A. (1996). Motorists conception of posted regulatory and warning signs. 29th International Symposium on Automotive Technology and Automation. Florence, Italy, pp. 131–138.
Al-Madani, H.M.N. (2000). Influence of drivers comprehension of posted signs on their safety-related characteristics. Accident Analysis and Prevention. 32, 575–581.
Al-Madani, H., Al-Janahi, A. R. (2002b). Role of drivers’ personal characteristics in understanding traffic sign symbols. Accident Analysis and Prevention. 34, 185-196.
Al-Madani, H.; Al-Janahi, A.R. (2002). Assessment of drivers’ comprehension of traffic signs based on their traffic, personal and social characteristics. Transportation Research Part F: Psychology and Behavior.
Babic, D., Dijanic, H., Jakob, L., Babic, D., Garcia-Garzon, E. (2020). Driver eye movements in relation to unfamiliar traffic signs: An eye-tracking study. Applied Ergonomics.
Bañares, J. R., Caballes, S. A., Serdan, M. J., Liggayu, A. T., & Bongo, M. F. (2018). A comprehension-based ergonomic redesign of Philippine road warning signs. International Journal of Industrial Ergonomics. 65, 17-25.
Ben-Bassat, T., Shinar, D., Caird, J.K., Dewar, R.E., Lehtonen, E., Sinclair, M., Zakowska, L., Simmons, S., Liberman, G., Pronin, M. (2021). Ergonomic design improves cross-cultural road sign comprehension. Transportation Research Part F: Psychology and Behavior. 78, 267-279.
Ben-Bassat, T., Shinar, D. (2015). The effect of context and drivers’ age on highway traffic signs comprehension. Transportation Research Part F: Traffic Psychology and Behavior. 33, 117–127.
Ben-Bassat, T., Shinar, D. (2006). Ergonomic guidelines for traffic sign design increase sign comprehension. Human Factors. 48(1), 182-195.
Berrio, S., Barrero, L., Zambrano, L., Papadimitriou, E. (2022). Ergonomic factors affecting comprehension levels of traffic signs: A critical review. International Journal of Transportation Science and Technology.
Brucal, D. M., Canuto, A. L., Garcia, C. A., Tangsoc, J. C. (2015). A study on the design of regulatory road signs using ergonomic principles of design and comprehension. Proceedings of the 19th Triennial Congress of the IEA, Melbourne.
Chan, K. L., Chan, A. H. S. (2011). Understanding industrial safety signs: Implications for occupational safety management. Industrial Management and Data Systems. 111, 1481-1510.
Charlton, S. G., Baas, P. H. (2006). Assessment of hazard warning signs used on New Zealand roads. New Zealand Government - NZ Transport Agency.
Chen, Xinqiang., Wu, Shubo., Shi, Chaojian., Huang, Yanguo., Yang, Yongsheng., Ke, Ruimin., Zhao, Jiansen. (2020). Sensing data supported traffic flow prediction via denoising schemes and ANN: A Comparison. IEEE Sensors Journal. Vol. 20, pp. 14317-14328.
Chi, C. F., Dewi, R. S. (2014). Matching performance of vehicle icons in graphical and textual formats. Applied Ergonomics. 45, 904-916.
Collins, B., Lerner, N. (1982). Assessment of fire-safety symbols. Human Factors: The Journal of Human Factors and Ergonomics Society.
Cooper, B.R. (1989). Comprehension of traffic signs by drivers and non-drivers. TRRL Research Report No. 167. Crowthorne, Berkshire: Transportation and Road Research Laboratory.
Crundall, D. (2016). Hazard prediction discriminates between novice and experienced drivers. Accident Analysis and Prevention. 86, 47-58.
Department of Public Works and Highways. (2012). Highway safety design standards Part 2: Road signs and pavement markings. Manila, Philippines.
Dewar, R. (1994). Design and evaluation of graphic symbols. Proceedings of Public Graphics, University of Utrecht. Department of Psycholonomics, Utrecht, Netherlands. 24.1-24.18.
Dewar, R. (1999). Design and evaluation of public information symbols. Visual information for everyday use: Design and research perspectives. Taylor and Francis. 285-303.
Dewar, R., Kline, D., Scheiber, F., Swanson, A. (1997). Symbol signing design for older drivers. Federal Highway Administration. US Department of Transportation.
Drory, A., Shinar, D. (1982). The effects of roadway environment and fatigue on sign perception. Journal of Safety Research. 13, 25–32.
Eisele, D., Petzoldt, T. (2021). Effects of traffic context on eHMI icon comprehension. Transportation Research Part F: Psychology and Behavior.
Federal Highway Administration – FHWA. (2003). Manual on Uniform Traffic Control Devices for Streets and Highways, 2003 Edition.
Filtness, A.J., Larue, G., Schramm, A., Fuller, J., Rakotonirainy, A., Han, C., Cairney, P. (2017). Safety implications of co-locating road signs: a driving simulator investigation. Transportation Research Part F: Traffic Psychology and Behavior.
Fisher, J. (1992). Testing the effect of road traffic signs information value on driver behavior. Human Factors. 34 (2), 231-237
Hawkins, H.G., Womal, K.N., Mounce, J.M. (1993). Driver comprehension of regulatory signs, warning signs, and pavement markings. Transportation Research Records. 1403, 67-82.
Hou, G., Yang, J. (2020). Measuring and examining traffic sign comprehension with event-related potentials. Cognition, Technology, and Work.
Hung, K. V., Huyen, L. T. (2011). Education influence in traffic safety: A case study in Vietnam. IATSS Research. 34, 87-93.
Hung, C. (2014). Manual de señalización vial y dispositivos de seguridad. Secretaría de Comunicaciones y Transportes, 770.
ISO 3864-1. (2011). Safety colors and safety signs, Part 1: Design principles for safety signs and safety markings. ISO: Geneva, Switzerland.
ISO 9186-1. (2007). Graphical symbols-test methods - Part 1: Methods for testing comprehensibility. ISO: Geneva, Switzerland.
Jamson, S., Mrozek, M. (2017). Is three the magic number? the role of ergonomic principles in cross-country comprehension of road traffic signs. Ergonomics.
Kaplan, S., Bortei-Doku, S., Prato, C. (2018). The relation between the perception of safe traffic and the comprehension of road signs in conditions of ambiguous and redundant information. Transportation Research Part F: Psychology and Behavior.
Kirmizioglu, E., Tuydes-Yaman, H. (2011). Comprehensibility of traffic signs among urban drivers in Turkey. Accident Analysis and Prevention.
Kowalewski, S., Kluge, J., Ziefle, M. (2013). Integrating potential users into the development of a medical wristwatch in four steps. Communications in Computer and Information Science. 374, 183-186.
Koyuncu, M., Amado, S. (2008). Effects of stimulus type, duration, and location on priming of road signs: Implications for driving. Transportation Research Part F: Traffic Psychology and Behavior. 11(2), 108-125.
Kraft, W.H., Homburger, W.S., Pline, J.L. (2009). Traffic Engineering Handbook, sixth ed. Institute of Transportation Engineers, Washington, D.C.
Kummetha, V., Kondyli, A., Devos, H. (2021). Evaluating driver comprehension of the roadway environment to retain accountability of safety during driving automation. Transportation Research Part F: Psychology and Behavior.
Lai, C. J. (2010). Effects of color scheme and message lines of variable message signs on driver performance. Accident Analysis and Prevention. 42(4), 1003-1008.
Lee, Y. M., Sheppard, E. (2016). The effect of motion and signaling on drivers’ ability to predict intentions of other road users. Accident Analysis and Prevention. 95, 202-208.
Lesch, M. F. (2003). Comprehension, and memory for warning symbols: Age-related differences and impact of training. Journal of Safety Research. 34(5), 495-505.
Lesch, M. F. (2008). Warning symbols as reminders of hazards: Impact of training. Accident Analysis and Prevention. 40(3), 1005-1012.
Liu, Y. C., Ho, C. H. (2012). The effects of age on symbol comprehension in central rail hubs in Taiwan. Applied Ergonomics. 43(6), 1016-1025.
Liu, Xiaohan., Qu, Xiaobo., Ma, Xiaolei. (2021). Improving flex-route transit services with modular autonomous vehicles. Transportation Research Part E: Logistics and Transportation Review. 149:102331.
Mayhorn, C. B., Wogalter, M. S., Bell, J. L., Shaver, E. F. (2004). What does code red mean? Ergonomics in Design: The Quarterly of Human Factors Applications. 12(4), 12-14.
McDougall, S. J. P., Curry, M. B., De Bruijn, O. (1999). Measuring symbol and icon characteristics: Norms for concreteness, complexity, meaningfulness, familiarity, and semantic distance for 239 symbols. Behavior Research Methods, Instruments, and Computers. 31(3), 487-519.
Megalingam, R., Thanigundala, K., Musani, S., Nidamanuru, H., Gadde, L. (2022). Indian traffic sign detection and recognition using deep learning. International Journal of Transportation Science and Technology.
Metropolitan Manila Development Authority. (2017). Accomplishment Report of 2017. Mandaluyong, Philippines.
Ng, A., Chan, A. (2008). The effects of driver factors and sign design features on the comprehensibility of traffic signs. Journal of Safety Research.
Ng, A. W. Y., Chan, A. H. S. (2007). The guessability of traffic signs: Effects of prospective-user factors and sign design features. Accident Analysis and Prevention. 39(6), 1245-1257.
Ng, A. W. Y., Chan, A. H. S. (2009). What makes an icon effective? AIP Conference Proceedings. 1098, 104-114.
Ou, Y. K., Liu, Y. C. (2012). Effects of sign design features and training on comprehension of traffic signs in Taiwanese and Vietnamese user groups. International Journal of Industrial Ergonomics. 42(1), 1-7.
Paninti, J. F. (1989). Redesign and evaluation of selected work zone sign symbols. Transportation Research Record. 1213, 47-55.
Payrea, W., Diels, C. (2019). Designing in-vehicle signs for connected vehicle features: Does appropriateness guarantee comprehension? Applied Ergonomics.
Picha, D. L., Hawkins, H. G., Womack, K. N., Rhodes, L. R. (1995). Motorist understanding of alternative design for traffic symbols. Final Report to the Federal Highway Administration. Texas Transportation Institute, Texas A&M University, College Station, TX, USA.
Ramakrishnan, A. S., L. Cranston, R., Rosiles, A., Wagner, D., Mital, A. (2000). Study of symbols coding in airway facilities. International Journal of Industrial Ergonomics. 25(1), 39-50.
Robielos, R.A.C., Lin, C. J. (2022). Traffic Sign Comprehension Among Filipino Drivers and Nondrivers in Metro Manila. Applied Sciences, 12, 8337.
Roca, J., Castro, C., Bueno, M., Moreno-Ríos, S. (2011). A driving-emulation task to study the integration of goals with obligatory and prohibitory traffic signs. Applied Ergonomics.
Rosson, M. B., Carroll, J. M. (2002). Usability engineering: scenario-based development of human-computer interaction. In Interface. 446, 119-125.
Schulz, P., Labudda, K., Bertke, V., Bellgardt, S., Boedeker, S., Spannhorst, S., Kreisel, S., Driessen, M., Beblo, T., Toepper, M. (2019). Age effects on traffic sign comprehension. IATTS Research.
Shinar, D., Vogelzang, M. (2013). Comprehension of traffic signs with symbolic versus text displays. Transportation Research Part F: Traffic Psychology and Behavior. 18, 72-82.
Shinar, D., Dewar, R. E., Summala, H., Zakowska, L. (2003). Traffic sign symbol comprehension: A cross-cultural study. Ergonomics. 46(15), 1549-1565.
Taamneh, M., Alkheder, S. (2018). Traffic sign perception among Jordanian drivers: An evaluation study. Transport Policy.
Vignali, V., Bichicchi, A., Simone A, Lantieri C, Dondi, G., Costa, M. (2019). Road sign vision and driver behavior in work zones. Transportation Research Part F: Traffic Psychology Behavior.
Wang, A. H., Chi, C. C. (2003). Effects of hazardous material symbol labeling and training on comprehension according to three types of educational specialization. International Journal of Industrial Ergonomics. 31(5), 343-355.
Wiseman, S., MacLeod, C. M., & Lootsteen, P. J. (1985). Picture recognition improves with subsequent verbal information. Journal of Experimental Psychology: Learning, Memory, and Cognition, 11, 588 – 595.
Wogalter, M. S., Sojourner, R. J., Brelsford, J. W. (1997). Comprehension and retention of safety pictorials. Ergonomics. 40(5), 531-542.
Wolff, J. S., Wogalter, M. S. (1998). Comprehension of pictorial symbols: Effects of context and test method. Human Factors. 40(2), 173-186.
Yaoa, X., Zhaoa, X., Liub, H., Huanga, L., Mac, J., Yind, J. (2019). An approach for evaluating the effectiveness of traffic guide signs at intersections. Accident Analysis and Prevention.
Zakowska, L. (2001). Perception and recognition of traffic signs in relation to drivers’ characteristics and safety-a case study in Poland. Road user characteristics with emphasis on lifestyles, quality of life, and safety. Proceedings of 14th ICTCT Workshop - International Cooperation of Theories and Concepts on Traffic Safety. 35-48.
Zegeer, C.V., Bushell, M. (2012). Pedestrian crash trends and potential countermeasures from around the world. Accident Analysis and Prevention, 44, 3-11.
Zhang, T., Zhou, X., Wang, P., Chan, C. (2022). An efficient framework for developing a video-based driving simulation for traffic sign evaluation. Journal of Safety Research.
Zhang, T., Chan, A.H.S. (2013). Traffic sign comprehension: A review of influential factors and future directions for research. Proceeding of the International Multi-Conference of Engineers and Computer Scientists. Hong Kong. 13-15 March 2013.
Ziefle, M., Pappachan, P., Jakobs, E. M., Wallentowitz, H. (2008). Visual and auditory interfaces of advanced driver assistant systems for older drivers. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5105, 62-69.