  Cooperative intelligent transportation systems (ITS) are used by autonomous
vehicles to communicate with surrounding autonomous vehicles and roadside units
(RSU). Current C-ITS applications focus primarily on real-time information
sharing, such as cooperative perception. In addition to real-time information
sharing, self-driving cars need to coordinate their action plans to achieve
higher safety and efficiency. For this reason, this study defines a vehicle's
future action plan/path and designs a cooperative path-planning model at
intersections using future path sharing based on the future path information of
multiple vehicles. The notion is that when the RSU detects a potential conflict
of vehicle paths or an acceleration opportunity according to the shared future
paths, it will generate a coordinated path update that adjusts the speeds of
the vehicles. We implemented the proposed method using the open-source Autoware
autonomous driving software and evaluated it with the LGSVL autonomous vehicle
simulator. We conducted simulation experiments with two vehicles at a blind
intersection scenario, finding that each car can travel safely and more
efficiently by planning a path that reflects the action plans of all vehicles
involved. The time consumed by introducing the RSU is 23.0 % and 28.1 % shorter
than that of the stand-alone autonomous driving case at the intersection.
