###### Abstract  
A reconfigurable intelligent surface (RIS) is a type of metasurface that can dynamically control the reflection and transmission of electromagnetic waves, such as radio waves, by changing its physical properties. Recently, RISs have played an important role in intelligently reshaping wireless propagation environments to improve the received signal gain as well as spectral efficiency performance. In this paper, we consider a millimeter wave (mmWave) vehicle-to-vehicle (V2V) multiple-input multiple-output (MIMO) system in which, an RIS is deployed to aid downlink V2V data transmission. In particular, the line-of-sight path of the mmWave system is affected by blockages, resulting in higher signaling overhead. Thus, the system performance may suffer due to interruptions caused by static or mobile blockers, such as buildings, trees, vehicles, and pedestrians. In this paper, we propose an RIS-assisted hybrid beamforming scheme for blockage-aware mmWave V2V MIMO systems to increase communication service coverage. First, we propose a conjugate gradient and location-based hybrid beamforming (CG-LHB) algorithm to solve the user sub-rate maximization problem. We then propose a double-step iterative algorithm that utilizes an error covariance matrix splitting method to minimize the effect of location error on the passive beamforming. The proposed algorithms perform quite well when the channel uncertainty is smaller than 10%. Finally, the simulation results validate the proposed CG-LHB algorithm in terms of the RIS-assisted equivalent channel for mmWave V2V MIMO communications. the single and multi-path channels to validate the adaptive channel estimation algorithm. A generalized hybrid architecture was proposed with a small number of RF chains and a finite number of ADC bits and the authors derived achievable rates with channel inversion and singular value decomposition-based transmission methods. A content-centric communications scenario was studied and a beamforming-based rate-splitting method applied to maximize the sum rates of all users in [11]. In addition, joint beamforming and power allocation was demonstrated for a non-orthogonal multiple access (NOMA)-based satellite-terrestrial integrated network in [12]. In [13], a receiver prototype was presented that enables reconfiguration between analog and digital beamforming modes to better deal with different operating scenarios. The authors designed a true-time-delay analog and digital beamformer in [13]. Elsewhere, a network was proposed featuring a multi-antenna array base station (BS) and a reconfigurable intelligent surface (RIS) to deliver information to information users and power to energy users [14]. Conjugate and zero-forcing beamforming was proposed to develop a path-following algorithm to solve the user throughput maximization problem subject to a realistic constraint on the quality-of-energy-service in terms of the harvested energy thresholds in [14]. In [15], the authors investigated a secure transmission design for an intelligent reflecting surface (IRS)-assisted unmanned aerial vehicles network and solved active and passive beamforming and trajectory optimizations. In addition, a neural networks-based beam codebook was designed in [16]. There are three hybrid beamforming architectures investigated in the literature: fully connected, fixed subarray and dynamic subarray. In [17], an iterative hybrid beamforming design algorithm was proposed with a fully connected architecture to maximize the weighted sum-rate performance of mmWave MIMO systems. The authors considered an RIS-aided mmWave-NOMA downlink system with a hybrid beamforming structure in [18]. They developed an alternating optimization algorithm to solve the non-convex optimization issue. Finally, geometric mean decomposition-based beamforming for RIS-assisted mmWave hybrid MIMO systems was proposed in [19]. The authors designed phase shifters for RIS by maximizing the array gain for the line-of-sight (LoS) channel.