High speed vehicular communication using localization technology with millimeter wave (mmWave) wireless communication is one of the promising technology. The low level Vehicle to Vehicle (V2V) communication standards are all incompatible with handling data rates at Gbps level. mmWave communication handles multi-Gbps data rates but it is sensitive to blockage. To overcome this blockage problem, directional antenna is used but it leads to beam misalignment because of doppler effect. When there is a high mobility, the conventional method of beam sweeping is ineffective because of searching and recovering actions that frequently result in beam alignment issues. In this thesis, considering beam misalignment in localization technology errors. We design and analyze by the proposed Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO) and Hybrid Particle Swarm Optimization Grey Wolf Optimizer (HPSOGWO) optimization algorithms. The proposed algorithm are a fine beam alignment without searching steps taken before steering the beam to the estimated vehicular position caused by localization errors. The simulation results show that HPSOGWO has better average maximum throughput performance than GWO by 1.96% and PSO by 12.82%. GWO has better throughput performance than PSO by 11.07%. The result also show that HPSOGWO significant throughput improvements and fastly converge to the optimal value. Keywords: Beam alignment, GWO, HPSOGWO, mmWave, PSO, V2V