###### Abstract
Recently, mmWave communication has included a vehicle-to-everything (V2X) paradigm to facilitate connected autonomous driving, video entertainment, vehicle platooning, and dynamic map update [20]. All of these services require high-speed connections to exchange safety information (e.g., vehicle location, direction and speed) among adjacent vehicles since recent V2X standards such as cellular V2X in [21], do not have advanced QoS and cannot provide consistent high-speed data transmission. Owing to the sparsity of the mmWave channel [1], the MIMO system typically requires an LoS connection, which maintains the received power level. Indeed, the LoS channel between the transmitter and receiver may be blocked by static or moving objects, such as buildings, trees, vehicles, and humans [22]. To satisfy the service quality of V2X communication under LoS blockage, RISs have also been represented as large intelligent surfaces (LISs), which have been investigated as an emerging technology in [6; 7; 23]. An RIS controller with beamforming is typically offered with high-accuracy indoor or outdoor radio localization [24]. In mmWave MIMO communication, the RIS can easily establish robust connections subject to blockage or mobility awareness. RISs are mainly used as antenna arrays for increasing coverage area and reducing energy consumption [25]. Moreover, RISs are applied as reflective relays [26]. The functionalities of RIS controllers increase the quality of the received signal when the adjustable passive elements can individually steer an incident electromagnetic wave in any direction. Based on the RIS element arrays, beamforming and steering concepts have been investigated in [23; 24; 25; 27]. Due to the notable benefits of RIS technology, outdoor coverage was analyzed using RISs in [25] and IRS-aided beamforming concepts discussed in [27]. A channel estimation algorithm was proposed in [28; 29], an RIS-aided manifold optimization algorithm was developed in [30], and an RIS-aided real-time autonomous vehicle model was investigated in [31]. Elsewhere, researchers proposed ultra-reliable low-latency communication in a factory automation (FA) scenario to deploy an IRS to create an alternative transmission link, which can enhance transmission reliability [32]. The performance of single and multiple RIS-assisted systems has also been considered without a direct path between the transmitter and the receiver in indoor and outdoor propagation environments [33]. In addition, researchers proposed a geometry-based stochastic channel model that supports the movements of transceivers and clusters, and the evolution of clusters was considered in the space domain, where a reflecting coefficients design was based on the minimum path loss [34]. Elsewhere, researchers provided a comprehensive overview of state-of-the-art research on emerging and promising RIS/IRS-aided wireless systems, with an emphasis on signal processing techniques for solving various radio localization, transmission design, and channel estimation issues [35]. A tutorial overview of single and multi-IRS-aided wireless networks has also been provided, with an emphasis on addressing the new and more challenging issues in IRS reflection optimization and channel acquisition design, in [36]. In [37], a multi-IRS-aided system was studied in which, the IRS and base station (BS) are managed by a central processing unit to coordinate data transmission and maximize the weighted sum rate of all cell-edge users by jointly optimizing the BS's transmit beamforming and each IRS's phase shifts, subject to the BS transmit power budget. The authors solved the non-convex and unit modulus constraint optimization using an efficient iterative power allocation algorithm. The achievable secrecy performance of mmWave MIMO systems was studied using RISs in [38], where the authors assumed a smart environment in which an RIS is placed between the source and the legitimate user to enhance the main link.