eISSN: 3087-4068 editor@aimjournals.com
All Journals
Submit your article

International Research Journal of Advanced Engineering and Technology

Open Access Peer Review International
Open Access

Emerging Trends in Ai-Based Road Safety Systems: Challenges, Opportunities, And Future Research Directions

DOI https://doi.org/10.55640/irjaet-v03i07-02
pdf
Dr. Neha Upadhyay 1 ,
4 Lakshmi Narain College of Technology (MCA), LNCT Campus, Kalchuri Nagar, Raisen Road, P.O. Kolua, Bhopal, Madhya Pradesh, India – 462022

Abstract

Traffic accidents are still a major threat to public safety, causing a lot of deaths, damage to property, and problems in society around the world. Intelligent, data-driven, and proactive traffic management systems have been made possible by the fast development of AI and ML, which has revolutionized traditional road safety practice. This paper presents a comprehensive review of recent AI-based approaches for enhancing road safety, with emphasis on accident prediction, driver behavior analysis, and connected vehicle technologies. In addition, the review examines the major factors contributing to road accidents and discusses the Safe System approach as a framework for improving transportation safety. Current challenges, including data quality, model interpretability, cybersecurity, privacy preservation, and regulatory constraints, are critically analyzed to highlight existing research limitations. Furthermore, emerging research directions explored as potential solutions for developing robust, scalable, and trustworthy intelligent transportation systems. The findings indicate that AI-driven technologies have considerable potential to improve accident prevention, traffic efficiency, and decision-making while supporting the development of safer and more sustainable road transportation systems.

Keywords

Road Safety, Intelligent Transportation Systems (ITS), Accident Prediction

References

K. Anastasiadou and F. Kehagia, “Road Safety Improvement and Sustainable Urban Mobility: Identification and Prioritization of Factors and Policies Through a Multi-Criteria Approach,” Urban Sci., vol. 9, no. 4, p. 93, Mar. 2025, doi: 10.3390/urbansci9040093.
J. P. EHSANI, J. P. MICHAEL, and E. J. MacKENZIE, “The Future of Road Safety: Challenges and Opportunities,” Milbank Q., vol. 101, no. S1, pp. 613–636, Apr. 2023, doi: 10.1111/1468-0009.12644.
X. Li, K. Song, and J. Shi, “Degradation generation and prediction based on machine learning methods: A comparative study,” Eksploat. i Niezawodn. – Maint. Reliab., vol. 27, no. 1, Aug. 2024, doi: 10.17531/ein/192168.
A. Boukerche and J. Wang, “Machine Learning-based traffic prediction models for Intelligent Transportation Systems,” Comput. Networks, vol. 181, p. 107530, Nov. 2020, doi: 10.1016/j.comnet.2020.107530.
Y. Yang, K. He, Y. peng Wang, Z. zhou Yuan, Y. hao Yin, and M. ze Guo, “Identification of dynamic traffic crash risk for cross-area freeways based on statistical and machine learning methods,” Phys. A Stat. Mech. its Appl., 2022, doi: 10.1016/j.physa.2022.127083.
F. J. Morales et al., “A machine learning methodology to predict alerts and maintenance interventions in roads,” Road Mater. Pavement Des., 2021, doi: 10.1080/14680629.2020.1753098.
S. Singamsetty, “AI-powered Satellite Image Processing for Global Air Traffic Surveillance Techniques Using NCNN–EGSA Optimization Techniques,” in Machine Learning Based Air Traffic Surveillance System Using Image Processing, 2026. doi: 10.1108/978-1-80592-062-520251010.
R. Palwe, “The Role of User Experience Design in Advancing Digital Sustainability,” Int. J. Sci. Res., vol. 14, no. 10, pp. 1168–1176, 2025.
K. Dixit, “An Intelligent Decision Support System for Tourists Management Via Global Tourism Analysis,” Int. J. Sci. Res. Sci. Technol., vol. 11, no. 4, pp. 755–765, Oct. 2024.
Z. Du, M. Deng, N. Lyu, and Y. Wang, “A review of road safety evaluation methods based on driving behavior,” Journal of Traffic and Transportation Engineering (English Edition). 2023. doi: 10.1016/j.jtte.2023.07.005.
X. Wang, X. Wu, M. Abdel-Aty, and P. J. Tremont, “Investigation of road network features and safety performance,” Accid. Anal. Prev., 2013, doi: 10.1016/j.aap.2013.02.026.
W. E. Marshall, “Understanding international road safety disparities: Why is Australia so much safer than the United States?,” Accid. Anal. Prev., 2018, doi: 10.1016/j.aap.2017.11.031.
H. M. Hassan and H. Al-Faleh, “Exploring the risk factors associated with the size and severity of roadway crashes in Riyadh,” J. Safety Res., 2013, doi: 10.1016/j.jsr.2013.09.002.
A. Mehdizadeh et al., “A review of data analytic applications in road traffic safety. Part 1: Descriptive and predictive modeling,” Sensors (Switzerland). 2020. doi: 10.3390/s20041107.
V. K. Sharma, “Cloud Computing & IoT: 5G Focused IoT with Cloud Solutions,” Int. J. AI, BigData, Comput. Manag. Stud., vol. 6, no. 3, 2025, doi: 10.63282/3050-9416.IJAIBDCMS-V6I3P103.
H. K. Yadav, “Design and Implement Machine Learning Based Predictive Analytics for Road Safety and Accident Prevention,” in 2026 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE, Mar. 2026, pp. 1–6. doi: 10.1109/IATMSI68868.2026.11465965.
O. F. Hamim and S. V. Ukkusuri, “Towards safer streets: A framework for unveiling pedestrians’ perceived road safety using street view imagery,” Accid. Anal. Prev., 2024, doi: 10.1016/j.aap.2023.107400.
M. Čabarkapa and Z. Avramović, “The applicability of Smeed’s Law in an evaluation of national road safety management systems: Montenegro versus Great Britain,” Int. J. Inj. Contr. Saf. Promot., 2022, doi: 10.1080/17457300.2022.2067183.
V. Kumar, S. K. Madishetty, and G. N. Maddipatla, “Intelligent Surgical Tables: Real-Time Patient Monitoring and Autonomous Adjustment Using IoT, Cloud Computing, and Cybersecurity,” J. Comput. Anal. Appl., vol. 31, no. 02, Feb. 2023, doi: 10.48047/jocaaa.2023.31.02.50.
R. F. Soames Job, J. Truong, and C. Sakashita, “The Ultimate Safe System: Redefining the Safe System Approach for Road Safety,” Sustain., 2022, doi: 10.3390/su14052978.
H. Mowafi et al., “Household economic impact of road traffic injury versus routine emergencies in a low-income country,” Injury, vol. 52, no. 9, pp. 2657–2664, Sep. 2021, doi: 10.1016/j.injury.2021.06.007.
S. Singh, “Advancing Network Security in 5G: Leveraging the 5G-NIDD Dataset for Intrusion Detection and Mitigation,” in 2025 IEEE 12th International Conference on Cyber Security and Cloud Computing (CSCloud), IEEE, Nov. 2025, pp. 1–6. doi: 10.1109/CSCloud66326.2025.00055.
J. B. Mehta, “Autonomous Patch Validation for Zero-Day Exploits in Enterprise Clouds,” Int. J. Appl. Math., vol. 38, no. 4s, pp. 1270–1285, Oct. 2025, doi: 10.12732/ijam.v38i4s.685.
A. Sohail, M. A. Cheema, M. E. Ali, A. N. Toosi, and H. A. Rakha, “Data-driven approaches for road safety: A comprehensive systematic literature review,” Safety Science. 2023. doi: 10.1016/j.ssci.2022.105949.
J. Joseph and S. Roy, “Multi-Modal Driver Safety System Using Deep Learning and Machine Learning,” in 2026 International Conference on Emerging Trends and Innovations in ICT (ICEI), IEEE, Jan. 2026, pp. 1–5. doi: 10.1109/ICEI65890.2026.11448018.
M. A. Mou, M. I. Jahan, S. Labonna, N. Najnin, S. M. Jahan, and M. M. Hossain, “Enhancing Road Safety in Bangladesh: A Comparative Deep Learning Framework for Automated Road Surface Classification,” in 2026 5th International Conference on Electrical, Computer & Telecommunication Engineering (ICECTE), IEEE, Jan. 2026, pp. 1–6. doi: 10.1109/ICECTE69292.2026.11429238.
D. Marichamy, H. Hemanth, G. L. Prasanna Kumar, K. Venkata Sunil, R. M. D. Charaan, and P. Sivaprakash, “Advanced Road Safety System with Real – Time Helmet and Triple Riding Detection, Intelligent Notifications, and Adaptive Speed Control,” in 2025 7th International Conference on Inventive Material Science and Applications (ICIMA), IEEE, May 2025, pp. 1453–1457. doi: 10.1109/ICIMA64861.2025.11074021.
F. J. Zárate Ramírez, A. Tonatiuh Vasconcelos Carrillo, C. D. Ayala Martinez, D. Eduardo Nicolas Aguiar, J. C. Catuche, and A. Viviana Vargas Durán, “Analysis of Driving Patterns on the Manzanillo–Colima Route Using Telematic Monitoring and Unsupervised Learning,” in 2025 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT), IEEE, Dec. 2025, pp. 1–6. doi: 10.1109/ICMLANT68509.2025.11394740.
L. Pipanmekaporn, S. Kamonsantiroj, R. Sutthaweekul, W. Lee, and K. Srisomboon, “Smartphone-based Road Condition Sensing using Machine Learning techniques,” in 2024 21st International SoC Design Conference (ISOCC), IEEE, Aug. 2024, pp. 246–247. doi: 10.1109/ISOCC62682.2024.10762144.
N. Parashuram and K. Vijayalakshmi, “A Comprehensive Analysis of Road Traffic Prediction Using Machine Learning Algorithms,” in 2024 First International Conference on Software, Systems and Information Technology (SSITCON), IEEE, Oct. 2024, pp. 1–5. doi: 10.1109/SSITCON62437.2024.10797035.
E. Kasatkina and D. Vavilova, “Identification and Mitigation of Road Traffic Accident Concentration Areas by Using Cluster Analysis,” in 2023 5th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA), IEEE, Nov. 2023, pp. 247–251. doi: 10.1109/SUMMA60232.2023.10349636.
G. Christou, A. Georgiou, C. Laoudias, A. Savva, and C. G. Panayiotou, “FixCyprus: Crowdsourcing Smartphone Imagery Data For Managing Road Safety Hazards,” in 2023 24th IEEE International Conference on Mobile Data Management (MDM), IEEE, Jul. 2023, pp. 188–191. doi: 10.1109/MDM58254.2023.00039.
R. Jain and A. Bhat, “Determining Statistically Significant Road Accident Spatial Hotspots using Machine Learning Approaches,” in 2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N), IEEE, Dec. 2022, pp. 214–221. doi: 10.1109/ICAC3N56670.2022.10074260.

Most read articles by the same author(s)

Similar Articles

11-20 of 40

You may also start an advanced similarity search for this article.