  Since the traffic administration at road intersections determines the
capacity bottleneck of modern transportation systems, intelligent cooperative
coordination for connected autonomous vehicles (CAVs) has shown to be an
effective solution. In this paper, we try to formulate a Bi-Level CAV
intersection coordination framework, where coordinators from High and Low
levels are tightly coupled. In the High-Level coordinator where vehicles from
multiple roads are involved, we take various metrics including throughput,
safety, fairness and comfort into consideration. Motivated by the time
consuming space-time resource allocation framework in [1], we try to give a low
complexity solution by transforming the complicated original problem into a
sequential linear programming one. Based on the "feasible tunnels" (FT)
generated from the High-Level coordinator, we then propose a rapid
gradient-based trajectory optimization strategy in the Low-Level planner, to
effectively avoid collisions beyond High-level considerations, such as the
pedestrian or bicycles. Simulation results and laboratory experiments show that
our proposed method outperforms existing strategies. Moreover, the most
impressive advantage is that the proposed strategy can plan vehicle trajectory
in milliseconds, which is promising in realworld deployments. A detailed
description include the coordination framework and experiment demo could be
found at the supplement materials, or online at https://youtu.be/MuhjhKfNIOg.
