## 2 Literature Review
They simulated SUMO for different vehicle counts. [PERSON] et al. [61] explored VANET routing protocols using cluster-based routing protocols. [PERSON], [PERSON], and [PERSON] [62] addressed VANET location-based routing protocol problems. They also addressed cluster-based routing protocol concerns and challenges. [PERSON] et al. discussed how machine learning may address VANET safety, communication, and traffic difficulties. It contains a VANET-based case study [44] and explored future approaches and challenges. [PERSON] et al. proposed an Efficient Key Management Scheme (KMSUNET) to optimize global criteria while increasing class lifespan and information transmission and decreasing inter-class overload [45]. [PERSON] et al. presented a trust-based authentication mechanism for clustered vehicular AdHoc networks to build reliable and stable clusters. Cluster Heads are chosen according to the predicted trust degree of each vehicle, and messages are encrypted using a public/private key pair provided by a Trusted Authority [46]. [PERSON] et al. suggested that Intelligent Transportation Systems, such as vehicular AdHoc networks, are essential for road safety and management, a novel method for  
Figure 2: V2V and V2I Communication on our proposed VANET. identifying malicious nodes using a fuzzy logic model [47]. [PERSON] et al. presented a SAACS, a self-adaptable Angular-based k-medoid Clustering Scheme (SAACS) that reduces network latency by making educated assumptions about route lengths and signal ranges. It is 50% more effective than RTVC plus ECHS and reduces the ratio of lost packets to total packets by 45% [48]. [PERSON] et al. analyzed current traffic congestion solutions. It analyzes the three primary subsystems of a Traffic Management System and suggests future research and themes that need more study for a realistic and successful system [49]. [PERSON] et al. analyzed the SUMO that simulates road traffic to assess the effectiveness of a one-way hash chain model to strengthen privacy and data integrity safeguards in VANET-based healthcare networks [50]. The author proposed a methodology to determine which bicycle and pedestrian paths would impact health outcomes most. Walking is the most accessible and social means of transportation, but transportation innovations have reduced the quality of life for pedestrians. This study combines a survey questionnaire and walkability assessment to assess how people feel about walking [63]. This study showed that a pleasant walking environment can positively impact the walking experience. It was found that urban areas with lively public squares and pedestrian walkways provide much visual stimulation, while underpasses lead to 64% fewer head motions and a 164% increase in time glanced down. Two multiple linear regression statistics show the elements of the surroundings that draw the gaze of pedestrians. Humans have a finite range of detection for their sensory organs, so human-scaled walking settings are more engaging [64]. [PERSON] et al. proposed a new framework for an intelligent data-driven transportation system in metropolitan settings that can display CV data in real-time utilizing a big data analytic engine [51]. [PERSON] et al. 's proposed algorithm achieves a maximum cluster efficiency of 96.84, superior to both the Weighted Cluster Protocol and the AWCP Whale algorithmic program protocol regarding encapsulation potency and portability [52]. Our research contributes to vehicular communication by proposing secure cluster-based authentication and communication protocols for Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications. The protocols we developed address the critical phases of V2I and V2V communications and resource sharing within a VANET. Our contribution includes the following aspects:  
* We introduce a secure authentication mechanism that relies on a trusted third-party certification authority. It ensures the integrity and authenticity of vehicles and infrastructure units participating in the communication network.