Manual and Autonomous Vehicles Mixture using DL-based Traffic Safety Solution in 5G-Transportation

It is the goal of Vehicular Ad-hoc Networks (VANETs) to provide Ultra-high data transfer rates with minimal end-to-end latency. However, high transmit power in VANET is hampered by its unpredictable nature and rising bandwidth requirements. Another major issue brought on by the broadcast storm that VANETs generate is the dispersal of safety messages. For better Quality of Service (QoS), this study will develop a brand-new cellular-5G VANET infrastructure, a challenge that has plagued the field from the beginning. At first, the Adaptive Mobility Aware Path Similarity (A-MAPS) system divides up all the cars into different groups based on their shared characteristics. Clusters were constructed, and a Cluster Head (CH) is chosen, taking into account upcoming route resemblance, which is especially important in an urban setting. In the end, OMNeT++ was used to conduct further tests and analyses. The simulated results validate the promised system throughput, delivery latency, transport expense, and bit rate of our suggested work.