Civil and Project journal

The effect of quality control and smartening of traffic signs in reducing accidents

https://doi.org/10.22034/cpj.2024.432656.1250
Volume 6, Issue 1 - Serial Number 59
April 2024
Pages 62-78
Civil and Project journal

Document Type : Research Article

Authors

Ahamad Jawad Ramaki 1
Reza Amin 2
Ali Khodaii 3

1 Undergraduate student of civil Engineering, AmirKabir University of Technology, Tehran, Iran

2 M.Sc. graduate, Department of Civil & Environment, AmirKabir University of Technology, Tehran, Iran

3 Full professor, Department of Civil & Environment, AmirKabir University of Technology, Tehran

Abstract
Recognizing traffic signs is very important in the field of intelligent transportation systems, because it effectively increases the safety of our roads. By equipping drivers with vital information about potential hazards, this technology significantly reduces response time and helps making quick decisions while operating the vehicle. Due to the exponential growth of our population, unfortunately the increase in the number of vehicles has led to a painful increase in traffic fatalities and injuries. Although the expansion of the transportation network helps the traffic issue, this expansion may be inapplicable due to the High financial costs, geographic and environmental limitations, as well as a long period of time to improve transportation infrastructure. Quality control of traffic colors, shabrangs, glass beads and other traffic signs in accordance with national and international standards will significantly reduce the number of dead and injured. Managing a smart city with emphasis on waste reduction and efficient use of resources is the main responsibility of traffic and transportation activities. The use of complex processing techniques in cars to increase safety without interfering with driving has been proposed as part of the concept of a smart city. This study looks at a new approach that can help create a framework for placing street signs using Google images into a traffic management program. The findings show a reduction in travel time, an increase in the use of the fleet, better maintenance of vehicles, and a reduction in carbon dioxide emissions from passenger cars.

Keywords

Traffic signs
Smartening
Quality control
Reduction of dead
Traffic management
Subjects
Adrasi, M. Educational research and planning organization. Road keeping and maintenance
operation book (1397) first edition, Persian.
Ahmadi, Mohammad Mahdi, Providing an Evaluation model of urban traffic signs based on
automatic detection, Ninth National Conference of Electric Engineering, (1402), Persian.
Alizadeh, Sohand and Froheed & Amir Esmail, 1399, Analyzing the Effects of human factors in
understanding the Traffic signs Local study: Tehran city Drivers, Persian.
Al-Madani, H., and Al-Janahi, A. R. (2002). “Assessment of drivers’ comprehension of traffic
signs based on their traffic, personal and social characteristics.” Transportation Research Part F:
Traffic Psychology and Behaviour, Elsevier Ltd, 5(1), 63–76.
Amouzadeh Omrani, M., & Nazarian, P. (1399). Investigating the effect of smartening traffic signs
for traffic problems in cities, Civil and project journal, Persian.
Anguelov, D., Dulong, C., Filip, D., Frueh, C., Lafon, S., Lyon, R., ... & Weaver, J. (2010). Google
street view: Capturing the world at street level. Computer, 43(6), 32-38.
Baran, zeynab. Analysis of the effects of the optimal implementation of traffic signs on safety and
social behavior, (1391), Persian.
Bastidas, V., Bezbradica, M., & Helfert, M. (2017, June). Cities as enterprises: a comparison of
smart city frameworks based on enterprise architecture requirements. In International Conference on
Smart Cities (pp. 21-22). Springer, Cham.
Cintra, M. (2013). A crise do trânsito em São Paulo e seus custos. GV EXECUTIVO, 12(2), 52-
61.
Khosh akhlaq, Y., Mahmoodi feremani ,M., & Sobhani, N. (2022). Reducing casualties and road
accidents by controlling the quality of traffic signs and colors, Persian.
Mazurkiewicz, J. (2017). Intelligent Processing Methods Usage for Transport Systems Safety
Improvement. Procedia Engineering, 178, 162-171.
Pop, M. D., & Proștean, O. (2018). A comparison between smart city approaches in road traffic
management. Procedia social and behavioral sciences, 232, 22-36.
Rocha Filho, G. P., Meneguette, R. I., Neto, J. R. T., Valejo, A., Weigang, L., Ueyama, J., ... &
Villas, L. A. (2020). Enhancing intelligence in traffic management systems to aid in vehicle traffic
congestion problems in smart cities. Ad Hoc Networks, 107, 102265.
Sun, Q. C., Xia, J. C., Li, Y., Foster, J., Falkmer, T., & Lee, H. (2018). Unpacking older drivers’
maneuver at intersections: Their visual-motor coordination and underlying neuropsychological
mechanisms. Transportation research part F: traffic psychology and behaviour, 58, 11-18.
Vilchez, J. L. (2019). Mental representation of traffic signs and their classification: warning
signs.Transportation research part F: traffic psychology and behaviour, 64, 442-462.
Z.-L. Sun, H. Wang, W.-S. Lau, G. Seet, and D. Wang, "Application of BW-ELM model on traffic
sign recognition," Neurocomputing, vol. 128, pp. 153-159, 2014.
  • Receive Date 02 December 2023
  • Revise Date 31 December 2023
  • Accept Date 12 January 2024
  • First Publish Date 12 January 2024
  • Publish Date 20 March 2024

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