  This paper studies the cooperative driving of connected and automated
vehicles (CAVs) at conflict areas (e.g., non-signalized intersections and
ramping regions). Due to safety concerns, most existing studies prohibit lane
change since this may cause lateral collisions when coordination is not
appropriately performed. However, in many traffic scenarios (e.g., work zones),
vehicles must change lanes. To solve this problem, we categorize the potential
collision into two kinds and thus establish a bi-level planning problem. The
right-of-way of vehicles for the critical conflict zone is considered in the
upper-level, and the right-of-way of vehicles during lane changes is then
resolved in the lower-level. The solutions of the upper-level problem are
represented in tree space, and a near-optimal solution is searched for by
combining Monte Carlo Tree Search (MCTS) with some heuristic rules within a
very short planning time. The proposed strategy is suitable for not only the
shortest delay objective but also other objectives (e.g., energy-saving and
passenger comfort). Numerical examples show that the proposed strategy leads to
good traffic performance in real-time.
