| Abstract |
Due to rapid population growth and industrialization, residents of large cities often face severe traffic congestion during their commutes. This leads to unexpected delays, increased accident risks, fuel wastage, and a decline in public health, particularly in urban areas where pollution exacerbates unsanitary conditions. In response, many smart cities are implementing traffic control systems based on traffic automation principles to mitigate these issues. A key challenge lies in using real-time analytics and online traffic data to efficiently manage traffic flow. To address this, the current research proposes an advanced monitoring system leveraging highly flexible mobile agent technology for intelligent data analytics. In the context of a Vehicular Ad-hoc Network (VANET), the mobile agent incorporates additional features such as crime reduction, accident prevention, enhanced driver flexibility, and improved security. These features are combined with a congestion control algorithm to optimize traffic flow and prevent congestion at the entry points of smart traffic zones. Simulation results using the Ns2 simulator demonstrate significant improvements in reducing delays and preventing accidents caused by heavy traffic. © 2025 IGI Global. All rights reserved. |
