The intersection cooperative driving system(ICDS) envisions that vehicles and an intersection controller could cooperatively work together to improve traffic operations and managements so that vehicles can safely and efficiently cross the intersection. Thus, the cooperation and optimization of the ICDS, which is solved simultaneously on incommensurable and conflicting objectives, is a typical multiobjective optimization problem(MOOP) with constrained conditions. For solving the ICDS’s MOOP, an improved membrane computing-based multi-vehicles optimization method (IMC-MOOM) is proposed from vehicle-to-everything (V2X) perspective. In detail, the ICDS’s MOOP is described using population P system, and then the IMC-MOOM is proposed to solve the ICDS’s MOOP. Finally, experimental results and analysis demonstrate that our proposed method is superior or competitive to four optimization evolution algorithms recently reported in the literature.