## 1 Introduction
The VANET paradigm plays a crucial role in facilitating communication among vehicles, especially during emergencies. Electric vehicles navigate the roadways, following a prioritized process, where the dissemination of emergency messages and efficient traffic organization is paramount, especially in a dynamic mobile environment. Traffic management relies on the effective calculation of communication performance involving not only moving vehicles but also roadside units and traffic lights. To ensure the smooth flow of emergency vehicles through traffic, an approach was devised [14; 15]. To improve emergency message dissemination in VANET, many existing works perform clustering and forwarder selection by performing optimal routing. However, this leads to energy consumption, lack of reliability, and packet loss. Existing research works focus on these problems but do not provide a proper solution for emergency message dissemination. Some of the unsolved gaps in the existing works--considered as the motivation of the proposed work--are listed below:  
* Communication overhead: Due to its limited bandwidth and mobility, the current combination of insufficient communication technologies results in a large communication overhead. Additionally, incorrect base station, RSU deployment, and network structure limit the network's capacity to scale, increasing communication overhead. * High packet loss: Some of the pre-existing works included direct routing. However, the lack of vehicle clustering leads to packet loss. Contrarily, clustering is based on parameters such as direction, velocity, and distance of movement. As a result, stability, reliability, energy efficiency, and packet loss are reduced when choosing the CH. However, these criteria alone are insufficient. * Transmission delay: The choice of a cluster head or a vehicle performing routing independently by just looking at its information leads to inefficient routing that interferes with packet transport. On the other hand, cluster heads are chosen for emergency message transmission depending on the direction angle. However, while sending messages, additional factors (such as distance, node location, and energy) are not taken into account, causing transmission delays. Additionally, the choice of the forwarder is made based on beacon messages and neighbor locations. However, other factors (such as speed, lane condition, and distance) are not taken into account, causing transmission delays. * Inefficient emergency message dissemination: The next hop selects the best forwarder based on a single moving direction. However, it results in the distribution of emergency messages being ineffective. Estimates of decision areas are often based only on transmission ranges in existing installations. However, since these factors are ineffective at determining decision areas, message transmission becomes difficult. Dissemination of emergency messages in this situation is limited to atypical cars and accidents. However, another emergency message (such as an ambulance alert or a list of local pharmacies) was not considered, resulting in the ineffective distribution of emergency messages. Additionally, it narrows the selection of practical and reasonably priced transportation choices and worsens traffic congestion on the roadways. The primary objective of this research is to enhance the dissemination of emergency messages within VANET by optimizing the selection of the most suitable forwarder nodes. Additionally, this study tackles several critical issues such as excessive communication overhead, elevated packet loss rates, and undesirable delays. The goal is to improve the overall transmission of packets and enhance the selection of optimal communication paths within VANET. The following are the objectives of this study:  
* To mitigate communication overhead, we employ a network construction approach that combines 2D and 3D elements. Furthermore, we establish robust vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-pedestrian (V2P) communication channels.