THE APPLICATION OF ARTIFICIAL INTELLIGENCE FOR ENHANCING TRAFFIC SAFETY
DOI:
https://doi.org/10.24867/32DS04SavicKeywords:
Artificial intelligence, traffic safety, machine learning, computer vision, autonomous vehiclesAbstract
The paper focuses on the application of artificial intelligence (AI) in traffic safety, particularly emphasizing the use of machine learning and computer vision technologies. It explores key methods that enable the prediction of traffic accidents, identification of risky drivers, real-time hazard detection, and automated traffic management systems. The work also highlights the role of sensors and IoT data in improving safety and efficiency, as well as the contribution of autonomous vehicles to reducing road traffic risks.
References
[1] Romanowska, A., & Budzyński, M. (2022). Investigating the impact of weather conditions and time of day on traffic flow characteristics. Weather, Climate, and Society, 14(3), 823-833.
[2] Bartels, H., Wahl, S., & Gebhardt, C. (2020). The use of radar-based precipitation data for predicting traffic accidents with logistic regression models. Natural Hazards and Earth System Sciences Discussions.
[3] Yuan, Z., Wu, X., Wang, Y., & Liu, X. (2024). RealTime Monitoring Method for Traffic Surveillance Scenarios Based on Enhanced YOLOv7. Applied Sciences, 14(16), 7383.
[4] Lee, C.-C., & Wu, X. (2022). Design and Implementation of an ML and IoT Based Adaptive TrafficManagement System for Smart Cities. Sensors, 22(8), 2908.
[5] Luo, H., Cai, L., & Li, C. (2023). Rail Surface Defect Detection Based on An Improved YOLOv5s. Applied Sciences, 13(12), 7330.
[6] Khan, M. A., Hossain, M. S., & Muhammad, G. (2020). Artificial Intelligence of Things (AIoT) for Smart Cities and Transportation Systems. IEEE Transactions on Intelligent Transportation Systems, 22(8), 5341-5351.
[7] Zhang, Y., & Li, X. (2020). AI for Urban Infrastructure Development and Traffic Flow Prediction. IEEE Transactions on Sustainable Cities, 15(3), 234-245.
[8] Vasudevan, M., Townsend, H., & Samach, M. (2022). Artificial Intelligence (AI) for Intelligent Transportation Systems (ITS): Challenges and Potential Solutions.
[9] Jevinger, Å., Zhao, C., Persson, J. A., & Davidsson, P. (2024). Artificial Intelligence for Improving Public Transport: A Mapping Study. Public Transport, 16(1), 99- 158.
[10] Skitmore, M., Qu, Z., Skulmoski, G., & Chen, J. (2024). The Application of Machine Learning and Deep Learning in Intelligent Transportation: A Scientometric Analysis and Qualitative Review of Research Trends. Sustainability, 16(14), 5879.
[11] Primena kompjuterskog vida https://viso.ai/applications/computer-vision-applications/ (pristupljeno u oktobru 2024)
[12] Optimizovani okvir za detekciju vozila koristeći kombinaciju oduzimanja pozadine i CNN https://www.mdpi.com/1424-8220/22/3/1193 (pristupljeno u oktobru 2024)
[13] Snimak ekrana alata zasnovanog na formi koji prikazuje statistiku protoka saobraćaja u realnom vremenu prikupljenu iz video strima u Norveškoj https://link.springer.com/article/10.1007/s11042-023- 14418- (pristupljeno u oktobru 2024)
