This paper proposes a Dynamic Collision-Free Cooperative decision-making method based on the Predicted InterDistance Profile (DCFC-PIDP) for Connected Autonomous Vehicles (CAVs), aimed at solving congestion, and increasing the efficiency and safety of the transport system. Under this framework, this paper studies a typical urban driving scenario: unsignalized intersection. The method employs a greedy algorithm to explore with an appropriate metrics, the main possible scenarios, involving CAVs with a risk of collision and f ind the suboptimal feasible solution. The decision-making cost function is constructed by considering the risk of collisions and the passing efficiency of CAVs. Finally, the effectiveness and feasibility of the proposed decision-making framework are verified under statistic studies.