## 1 Introduction  
Vehicle ad hoc networks (VANET) are often referred to as networks on wheels, which are used to provide connectivity between vehicle nodes. It is an outgrowth of mobile networks. Vehicular nodes are self-organized and connect with each other in a less environmentally sound infrastructure. The IEEE Committee has established the IEEE 802.11p standard for VANETs, recognizing that the ad hoc vehicle network is essential for the provision of safety-associated applications in the Intelligent Transportation System. For short-range transmission, the US Federal Communication Commission (FFC) has allotted 75 MHz of bandwidth at 5.9 GHz between vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I). The main objective of VANETs is to create an intelligent framework for transport. In building V2V and V2I communications, Dedicated Short Range Communication (DSRC) may play an important role. DSRC has a range of around one thousand meters. Inter-networking via VANETs has received huge attention over the past few years. Realizing its increasing importance, academia, major automotive manufacturers, and government agencies are making efforts to develop VANETs [1, 2]. VANET has mobile nodes, sensor vehicles, static networks, fixed roadside access points (RSAP), and wireless links such as V2V, V2I, and point-to-a-vehicle access (I2V). Depending on the coverage requirements, this wireless communication device consists of a combination of GPS and a cellular communication system using either one- or multi-hop mode. One of this technology's main services is to support drivers with protection so that road injuries can be reduced. Providing protection for onboard passengers is the main service offered by this form of network. A VANET's key requirements are high processing power, large storage space, adequate energy, and node movement estimation [3,4]. This technology facilitates a variety of applications that affect daily human life, such as infotainment, traffic management services, and security, as displayed in Figure 1. Due to their unique characteristics, several clustering schemes have been proposed for VANETs in previous years. Due to technological advancement in vehicle mobility, protocols that utilize multiple network parameters have been revealed to be highly appropriate for VANETs. The authors selected parameters such as distance, density, connection stability, velocity, and location in soft computing techniques for their review work. In addition, VANETs have received a lot of consideration in industry a0 nd are predicted to be introduced in the near future, thus attaining data sharing between vehicles and organizations that enable different mobile vehicle services such as safety, traffic performance, urban detection, driver support, and vehicle user entertainment [5]. Vehicles can create intra-vehicle, V2V, V2I, and still vehicle-to-everything (V2X) transmission, in particular, in such a VANET to partially reduce the load of data traffic while meeting the maintenance requests of vehicle users nearby [6]. The traffic flowing through a vehicular network increases with the vehicular nodes, resulting in network congestion. Routing in the network then becomes a challenging task which affects throughput, delay, and packet loss and hence reduces the overall efficiency of the network. In past years, Particle Swarm Optimization (PSO), K-means, Neural Networks (NN), Artificial Bee Colony (ABC), Genetic Algorithm (GA), Firefly Algorithm (FA), and Fuzzy Logic (FL) have been proposed to upgrade the efficiency in wireless sensor networks with the rapid expansion of soft computing techniques [7]. To provide versatility and strength to network failure, complex network topology, and flexible channel requirements in VANETs, soft computing techniques are found to be the best optimal solution in a vehicular environment. This survey, therefore, discusses the recently proposed clustering protocols based on soft computing techniques in the literature  
Figure 1: VANET Applications with Examples.