In 6G vehicle to everything (V2X) communications, accurate localization is the foundation of high quality intelligent services to users. However, accurate localization requires a significant amount of information and should overcome the non line of sight (NLoS). In this article, we propose the reconfigurable intelligent surface (RIS)-assisted cooperative channel state information localization (RCSIL) system to analyze and optimize the localization accuracy based on effective channel state information (CSI). RIS improves the channel quality by adjusting the phase of the reflection unit, thereby affecting the localization performance. Using RIS as an anchor saves a lot of hardware resources. However, the optimization problem of the RIS phase modulation scheme is a non-convex nonlinear integer programming which is complex and hard to solve. Thus, we propose an Adagrad gradient descent based phase optimization (AG-PO) algorithm, which computes the optimal phase of each reflecting unit in parallel. AG-PO has low complexity, effectively improves positioning accuracy, and performs fast computing. The simulation results indicate that AG-PO outperforms alternating optimization (AO) and genetic algorithm (GA) with a 44.17% and 44.02% reduction in squared position error bound (SPEB) respectively. Thus, RCSIL can be widely applied in 6G V2X communications systems.