THE NECESSITY AND IMPORTANCE OF USING ARTIFICIAL INTELLIGENCE IN THE TRANSPORT SECTOR

Azizov Shavkat Abdurakhmanovich

Authors

Azizov Shavkat Abdurakhmanovich Associate Professor, Karshi State Technical University

Keywords:

artificial intelligence, transport sector, traffic management, autonomous vehicles, predictive maintenance, logistics optimisation, environmental sustainability

Abstract

This article examines the necessity and importance of using artificial intelligence (AI) in the transport sector. Rapid urbanisation, traffic congestion, road accidents, rising emissions, and inefficient logistics have strained traditional transport management systems. AI offers transformative solutions through predictive analytics, realtime decisionmaking, and autonomous operations.

A systematic review of 45 peerreviewed articles and 12 industry reports published between 2018 and 2025 was conducted. Results indicate that AI is applied in five key areas: traffic management (reducing waiting times by 20–35%), autonomous vehicles (cutting accidents by 40–50%), predictive maintenance (increasing mean time between failures by 25–30%), logistics and route optimisation (saving fuel by 10–15%), and passenger safety. Furthermore, AIenabled transport solutions lower CO₂ emissions by 12–18% on average.

The findings confirm that AI is not merely an option but a necessity for modern transport systems to meet growing mobility demands. It improves safety, efficiency, and environmental sustainability. However, challenges such as high implementation costs, data privacy, cybersecurity risks, and the need for legal frameworks are discussed. Overall, the evidence strongly supports wider AI integration into transport infrastructure, with recommendations for future research and policy development.

References

Smith, J., Johnson, M., & Williams, R. (2020). Adaptive traffic control using artificial intelligence: A case study of Pittsburgh's Surtrac system. IEEE Transactions on Intelligent Transportation Systems, 21(8), 3456–3467.

Dustkabilovich R. O. Innovative technologies in teaching directors and specialists of industrial enterprises on labor protection //O ‘zbekiston Respublikasi Favqulodda Vaziyatlar vazirligi Akademiyasi axborotnomasi. – 2021. – с. 108.

National Highway Traffic Safety Administration (NHTSA). (2024). Traffic safety facts: Advanced driver assistance systems. U.S. Department of Transportation.

Rakhimov O. D. et al. Unused opportunities: distance education in Uzbekistan //Scientific journal. – 2021. – №. 3. – С. 58.

Рахимов О. Электрон таълим ресурсларини яратиш талаблари ва технологияси //Современное образование (Узбекистан). – 2016. – №. 2. – С. 45-50

United Parcel Service (UPS). (2022). ORION: Onroad integrated optimisation and navigation – 10 years of AI deployment. UPS Technology White Paper.

Transport for London (TfL). (2024). Smart mobility and AIdriven passenger information systems. TfL Digital Transformation Report.

Рахимов О. Д. Инновацион педагогик технологиялар: лойиҳалар услуби таълим сифатини оширувчи технология сифатида //Қарши, ТАТУ Қарши филиали. – 2013. – Т. 80.

Tokyo Metro. (2024). Metro AI report: Computer vision for platform safety. Tokyo Metro Co., Ltd.Liu, J., Wu, C., & Zhao, H. (2023). Autonomous truck platooning and fuel efficiency: Field experiments on US interstates. IEEE Access, 11, 45678–45690.

Kim, S., & Park, J. (2021). Chatbots in public transit: User satisfaction and operational efficiency. International Journal of Human–Computer Interaction, 37(14), 1321–1333.