A critical review of motion planning methods for cooperative lane changes of connected and automated vehicles

Abstract

Cooperative lane-change motion planning coordinates the time-dependent lateral and longitudinal motions of a lane-changing vehicle with the anticipated or commanded motions of surrounding vehicles. Although related studies are often grouped by algorithms, traffic scenarios, or communication architectures, these dimensions overlap and do not provide mutually exclusive categories. This review focuses on methods that generate a continuous two-dimensional lane-change trajectory, or an equivalent sequence of lateral and longitudinal states or controls. A targeted Web of Science search with citation tracing retained 30 primary studies meeting this criterion. The studies are classified according to their primary planning output and the vehicles whose executable motions are directly determined. Four exclusive categories are established: interaction-conditioned ego-vehicle planning, fixed-structure cooperative motion planning, maneuver-organization-based multi-vehicle planning, and fully coupled multi-vehicle trajectory planning. The comparison shows that wider cooperative authority improves motion consistency and can resolve conflicts that are infeasible for an ego-only planner, but it also increases dependence on communication, behavioral models, computation, and centralized coordination. Across all four categories, uncertainty treatment is generally weaker than nominal optimization, safety constraints rarely constitute end-to-end guarantees, computational claims are difficult to compare, and validation remains dominated by designed simulations. Mixed traffic further changes cooperation from direct control to uncertain negotiation. These findings define the application conditions of the four planning paradigms and identify priorities for robust, scalable, and verifiable cooperative lane-change planning.