<p>Unsignaled intersections pose a significant safety challenge, particularly in the case of low-field view. To address this issue, we present a novel approach that leverages distributed vehicle-to-infrastructure (V2I) communication to enable advanced collision detection and avoidance at unsignaled intersections for connected autonomous vehicles. The proposed system utilizes roadside units (RSUs) to gather real-time data from vehicles, perform predictive analysis, and communicate potential collision risks to drivers in a timely manner. RSU used the minimal succeeding distance (MSD) among two vehicles for the identification of potential crashes. Further, the distance and speed-based threshold were utilized to send the warning alerts to the commuters. The proposed system is validated via simulation, and the efficacy of the proposed system is compared with the Central Server-based system and noted a significant improvement. Further, the model is compared with the existing state-of-the-art techniques in terms of the average number of halts, average travel time towards the destination, and average vehicle speed by varying the traffic volume.</p>