Smart City Transformation: Leveraging AI-Enhanced Vanets for Next-Generation Traffic Management
Year: 2025
Type: article
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.
Authors: N Subbu Krishna Sastry, Purushotham Bhat N
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409508028