Smart City Transformation: Leveraging AI-Enhanced Vanets for Next-Generation Traffic Management

The rapid urbanization of cities worldwide has led to unprecedented traffic congestion, inefficient transportation systems, and increased environmental concerns.Smart city initiatives aim to address these challenges by integrating cutting-edge technologies to create more sustainable and intelligent urban environments.Among these advancements, Artificial Intelligence (AI)-enhanced Vehicular Ad Hoc Networks (VANETs) have emerged as a transformative solution for next-generation traffic management.VANETs facilitate seamless communication between vehicles, roadside infrastructure, and central traffic management systems, enabling real-time data exchange and decision-making.By incorporating AI, these networks can analyze vast amounts of traffic data, predict congestion patterns, optimize traffic flow, and enhance road safety.AI-driven VANETs employ machine learning algorithms, deep learning models, and edge computing to process data efficiently, making traffic management more adaptive and responsive to dynamic conditions.One of the key benefits of AI-enhanced VANETs is their ability to support autonomous and connected vehicles, reducing human errors and improving traffic efficiency.These systems can detect accidents, reroute vehicles, and provide predictive analytics for better urban mobility planning.Furthermore, AIdriven VANETs play a crucial role in reducing carbon emissions by minimizing idling time and optimizing fuel consumption.

Authors

Publication Details

Journal
International Journal of Managerial Studies and Research
Published
2025-01-01
DOI
https://doi.org/10.20431/2349-0349.1304001
Primary Topic
Traffic Prediction and Management Techniques
Type
article
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article

Smart City Transformation: Leveraging AI-Enhanced Vanets for Next-Generation Traffic Management

Nishanth Sastry, C N Pruthvi
International Journal of Managerial Studies and Research
Traffic Prediction and Management Techniques
article

Smart City Transformation: Leveraging AI-Enhanced Vanets for Next-Generation Traffic Management

Nishanth Sastry, C N Pruthvi
article en

Abstract

The rapid urbanization of cities worldwide has led to unprecedented traffic congestion, inefficient transportation systems, and increased environmental concerns.Smart city initiatives aim to address these challenges by integrating cutting-edge technologies to create more sustainable and intelligent urban environments.Among these advancements, Artificial Intelligence (AI)-enhanced Vehicular Ad Hoc Networks (VANETs) have emerged as a transformative solution for next-generation traffic management.VANETs facilitate seamless communication between vehicles, roadside infrastructure, and central traffic management systems, enabling real-time data exchange and decision-making.By incorporating AI, these networks can analyze vast amounts of traffic data, predict congestion patterns, optimize traffic flow, and enhance road safety.AI-driven VANETs employ machine learning algorithms, deep learning models, and edge computing to process data efficiently, making traffic management more adaptive and responsive to dynamic conditions.One of the key benefits of AI-enhanced VANETs is their ability to support autonomous and connected vehicles, reducing human errors and improving traffic efficiency.These systems can detect accidents, reroute vehicles, and provide predictive analytics for better urban mobility planning.Furthermore, AIdriven VANETs play a crucial role in reducing carbon emissions by minimizing idling time and optimizing fuel consumption.

International Journal of Managerial Studies and ResearchVol. 13(4)
Sustainable cities and communities
Openalex Percentile: Top 93%
Traffic Prediction and Management Techniques
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Smart City Transformation: Leveraging AI-Enhanced Vanets for Next-Generation Traffic Management — Nishanth Sastry, C N Pruthvi · International Journal of Managerial Studies and Research (2025) | TGRS Research Map | TGRS