Author(s)

I-Ching Lin¹, Ya- Hui Hsieh^2*

Affiliation(s)

¹School of Computer Science and Engineering, Guangzhou Institute of Science and Technology, Guangzhou 510540, Guangdong, China.

²School of Network Communication, Guangdong University of Finance & Economics, Guangzhou 510320, Guangdong, China.

Corresponding Author

Ya- Hui Hsieh

ABSTRACT

Traffic accidents represent a significant public safety concern in Taiwan region, particularly in Taichung City, where accident rates have consistently increased over the past five years. The research aims to explore accident hotspots, analyze the relationship between driving behavior and accident types, construct an analytical model of influencing factors, and propose effective accident prevention measures. Using a multifaceted approach that combines literature review and empirical data analysis, this study identifies key determinants of traffic accidents, including human factors, economic conditions, vehicle types, and road attributes. The findings reveal that human factors, particularly violations of traffic rules and age-related vulnerabilities, significantly influence accident severity. Additionally, economic disparities correlate with accident distribution, highlighting the need for tailored policy interventions. The study concludes with practical recommendations for enhancing traffic safety through improved education, stricter law enforcement, and infrastructure development. By integrating these strategies, local and central governments can effectively reduce the incidence of traffic accidents and their associated social costs.

KEYWORDS

Human factors in traffic accidents; Road attributes; Law enforcement; Economic impact

CITE THIS PAPER

I-Ching Lin, Ya- Hui Hsieh. Understanding traffic accidents: an in-depth analysis of human factors, economic impacts, and transmission pathways in Taichung city. Journal of Trends in Applied Science and Advanced Technologies. 2025, 2(1): 53-63. DOI: https://doi.org/10.61784/asat3017.

REFERENCES

[1] Reason J. Human error. Cambridge University Press, 1990.

[2] Allahyari T, Saraji GN, Adi J, et al. Cognitive failures, driving errors and driving accidents. International Journal of Occupational Safety and Ergonomics, 2008, 14(2):149-158.

[3] Bishai D, Quresh A, James P, et al. National road casualties and economic development. Health Economics, 2006, 15(1):65-81.

[4] Bougueroua M, Carnis L. Economic development, mobility and traffic accidents in Algeria. Accident Analysis & Prevention, 2016, 92:168-174.

[5] Van Beeck EF, Borsboom GJ, Mackenbach JP. Economic development and traffic accident mortality. International Journal of Epidemiology, 2000, 29(3):503-509.

[6] Klaitman SS, Solomonov E, Yaloz A, et al. The incidence of road traffic crashes among young people aged 15-20 years: differences in behavior, lifestyle and sociodemographic indices in the Galilee and the Golan. Frontiers in Public Health, 2018, 6:202.

[7] M’bailara K, Atzeni T, Contrand B, et al. Emotional reactivity: Beware its involvement in traffic accidents. Psychiatry Research, 2018, 262:290-294.

[8] Rahmadiyani R. Factors affecting fatigue driving: demographics, attitudes, and perceived barriers. Journal of Transportation Safety, 2023, 15(1):20-35.

[9] Akinyemi Y. Relationship between economic development and road traffic crashes and casualties: empirical evidence from Nigeria. Transportation Research Procedia, 2020, 48:218-232.

[10] Agyemang B, Semevoh R. Regression analysis of road traffic accidents and population growth in Ghana. International Journal of Business and Social Research, 2013, 3(10):41-47.

[11] Gomes SV. The influence of the infrastructure characteristics in urban road accidents occurrence. Accident Analysis & Prevention, 2013, 60:289-297.

[12] Dumitrascu DI. Influence of road infrastructure design over the traffic accidents: a simulated case study. Infrastructures, 2024, 9(9):154.

[13] Pai CW, Saleh W. An analysis of motorcyclist injury severity in traffic crashes at T-junctions. Accident Analysis and Prevention, 2007, 39(6):1197-1207.

[14] Strawderman L, Huang SH, Jing L. Sign saturation and driver behavior: a study on warning effectiveness. Transportation Research Record, 2005, 1937(1):49-56.

[15] Girotto E, de Andrade SM, González AD, et al. Professional experience and traffic accidents/near-miss accidents among truck drivers. Accident Analysis & Prevention, 2016, 95:299-304.

[16] Lawton BP, Hallmark SL, Basulto-Elias G, et al. Road intersections and crash frequency in Ghana. Journal of Safety Research, 2024, 80:45-57.

[17] Prayudyanto MN, Goeritno A, Al Ikhsan SH, et al. Designing a model of the early warning system on the road curvature to prevent the traffic accidents. International Journal of Safety and Security Engineering, 2022, 12(3):291-298.

[18] Dragutinovic N, Twisk D. The effectiveness of road safety education. Accident Analysis and Prevention, 2006, 38(1):25-34.

[19] Twisk DA, Vlakveld WP, Commandeur JJ, et al. Five road safety education programmes for young adolescent pedestrians and cyclists: a multi-programme evaluation in a field setting. Accident Analysis & Prevention, 2014, 66:55-61.

[20] Qaid H, Widyanti A, Salma SA, et al. Speed choice and speeding behavior on Indonesian highways: extending the theory of planned behavior. IATSS Research, 2022, 46(2):193-199.

[21] Lin DJ, Yang JR, Liu HH, et al. Analysis of environmental factors on intersection accidents. Sustainability, 2022, 14(3):1764.

[22] Goniewicz K, Goniewicz M, Paw?owski W, et al. Road accident rates: strategies and programmes for improving road traffic safety. European Journal of Trauma and Emergency Surgery, 2016, 42(4):433-438.

[23] Lin HA, Chan CW, Wiratama BS, et al. Evaluating the effect of drunk driving on fatal injuries among vulnerable road users in Taiwan region: a population-based study. BMC Public Health, 2022, 22(1):2059.

[24] Shin D, Washington S, van Schalkwyk I. The impact of traffic enforcement on driver behavior. Accident Analysis and Prevention, 2015, 82:13-22.