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eISSN: 2581-9615 || CODEN: WJARAI || Impact Factor 8.2 ||  CrossRef DOI

Research and review articles are invited for publication in April 2026 (Volume 30, Issue 1) Submit manuscript

Artificial Intelligence in transportation: Advanced technology stacks and real-world implementation for modern mobility systems

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  • Artificial Intelligence in transportation: Advanced technology stacks and real-world implementation for modern mobility systems

Sarath Babu Gosipathala *

ViaPlus, Plano TX, USA.
 
Review Article
World Journal of Advanced Research and Reviews, 2024, 21(01), 2993-3007
Article DOI: 10.30574/wjarr.2024.21.1.0183
DOI url: https://doi.org/10.30574/wjarr.2024.21.1.0183
 
Received on 06 December 2023; revised on 20 January 2024; accepted on 28 January 2024
 
The integration of Artificial Intelligence (AI) with advanced technology stacks has revolutionized the transportation industry, addressing critical challenges in ground transportation, autonomous vehicles, road safety, traffic management, and intelligent toll collection systems. This research examines the deployment of cutting-edge AI technologies including deep neural networks, computer vision, edge computing, IoT sensors, and cloud-native architectures in transportation infrastructure. Through comprehensive analysis of implementations by major automotive companies including Tesla, General Motors, Ford, and Waymo, this paper demonstrates how AI-powered solutions utilize technology stacks comprising TensorFlow, PyTorch, CUDA, ROS (Robot Operating System), 5G networks, and blockchain for toll management. The study presents empirical evidence of AI applications reducing traffic congestion by 30-40%, improving road safety through predictive analytics, and optimizing toll collection efficiency by 85%. Key findings reveal that machine learning algorithms integrated with real-time sensor networks enable dynamic traffic routing, predictive maintenance of infrastructure, and automated reinvestment strategies for toll revenues into smart infrastructure improvements. This analysis provides a technical framework for implementing AI solutions across transportation sectors, addressing scalability challenges, and establishing foundation for autonomous transportation ecosystems.
 
AI, Mobility Systems, PyTorch, CUDA, TensorFlow, Transportation
 
https://wjarr.com/sites/default/files/fulltext_pdf/WJARR-2024-0183.pdf

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Sarath Babu Gosipathala. Artificial Intelligence in transportation: Advanced technology stacks and real-world implementation for modern mobility systems. World Journal of Advanced Research and Reviews, 2024, 21(1), 2993-3007. Article DOI: https://doi.org/10.30574/wjarr.2024.21.1.0183

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