Artificial Intelligence in Traffic Management: A Review of Smart Solutions and Urban Impact
Abstract
Artificial Intelligence (AI) has emerged as a transformative force in the realm of traffic management, revolutionizing urban mobility and addressing the challenges posed by increasing population density. This paper presents a comprehensive review of smart solutions powered by AI in the context of traffic management and evaluates their impact on urban environments. The integration of AI into traffic management systems has paved the way for dynamic and adaptive solutions that optimize traffic flow, reduce congestion, and enhance overall transportation efficiency. Machine learning algorithms enable the prediction and analysis of traffic patterns, allowing for real-time adjustments and responsive control mechanisms. Smart traffic signal systems, for instance, utilize AI to adapt signal timings based on live traffic conditions, minimizing delays and improving the overall flow of vehicles. Moreover, AI-driven technologies play a crucial role in enhancing safety on roadways. Advanced driver assistance systems (ADAS) leverage AI algorithms to detect potential hazards, monitor driver behavior, and mitigate risks through features like collision avoidance and automatic emergency braking. This not only contributes to reducing accidents but also enhances the overall safety of urban transportation. The impact of AI in traffic management extends beyond mere efficiency gains. Sustainable urban development is facilitated by intelligent transportation systems that encourage the use of public transport, cycling, and walking. Additionally, the integration of AI supports environmental goals by optimizing traffic patterns, reducing emissions, and promoting eco-friendly modes of transportation. However, challenges such as data privacy, ethical considerations, and the need for robust infrastructure persist. This review highlights the potential of AI in reshaping urban mobility while emphasizing the importance of addressing associated challenges. As cities continue to grow and face escalating transportation demands, the adoption of AI in traffic management emerges as a pivotal strategy for creating smart, efficient, and sustainable urban environments.
Keywords
AI; Traffic Management; Urban Impact; Smart Solution; Review
Citations
IRE Journals:
Afees Olanrewaju Akinade , Peter Adeyemo Adepoju , Adebimpe Bolatito Ige , Adeoye Idowu Afolabi
"Artificial Intelligence in Traffic Management: A Review of Smart Solutions and Urban Impact" Iconic Research And Engineering Journals Volume 7 Issue 12 2024 Page 511-522
IEEE:
Afees Olanrewaju Akinade , Peter Adeyemo Adepoju , Adebimpe Bolatito Ige , Adeoye Idowu Afolabi
"Artificial Intelligence in Traffic Management: A Review of Smart Solutions and Urban Impact" Iconic Research And Engineering Journals, 7(12)
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