  The cooperation of connected and automated vehicles (CAVs) has shown great
potential in improving traffic efficiency during intersection management.
Existing research mainly focuses on intersections where lane changing is
prohibited, which is impractical for real-life implementation. This paper
proposes a two-stage cooperation framework, which decouples the longitudinal
and lateral control of CAVs, allowing them to change to their preferred lanes.
Based on formation control, an iterative framework is initially proposed to
solve the target assignment and path planning problem for multiple CAVs on
multiple lanes. A graph-based minimum clique cover method is then applied to
obtain the optimal scheduling plan for the CAVs. Extensive numerical
simulations for different numbers of vehicles and traffic volumes validate the
effectiveness of the proposed algorithm.
