Intelligent Re-Routing Process using PSO Approach in Vehicular Ad-Hoc Network in Urban Environment

VANETs are pivotal components of ITS, offering enhanced safety and efficiency through V2V and V2I communications. This paper presents an Intelligent Re-Routing Particle Swarm Optimization (IRPSO) model for VANETs, addressing the challenges of efficient data transmission, reduced delay, and minimized routing overhead. The proposed model integrates a geometric particle swarm-based routing scheme, leveraging GPS coordinates and vehicle mobility patterns. Through simulation and analysis, the IRPSO model is compared with existing routing algorithms, highlighting its superior performance in terms of data success rate, data loss rate, average delay, network throughput, and routing overhead. Results demonstrate that the IRPSO model achieves a data success rate of 92.41%, a significantly lower data loss rate of 9.06%, a reduced average delay of 120.74 ms, a higher network throughput of 402 kbps, and a minimized routing overhead of 296.36 packets. This study aids in the progress of effective and dependable routing protocols in VANETs, essential for the creation of secure and smart transportation systems. The IRPSO model offers a promising solution to optimize data delivery, mitigate packet loss, and improve overall network performance, paving the way for enhanced V2V and V2I communications in future smart transportation networks.