An unstructured single‐layer optimization approach for flexible right‐of‐way allocation and cooperative trajectory planning at signalized intersections

Existing methods for signal timing and vehicle trajectory coordination often rely on fixed-phase designs or leading vehicle guidance, limiting efficiency in dynamic traffic and multi-vehicle coordination. This study models signal timing as right-of-way allocation for each inbound lane at discrete time intervals and integrates trajectory planning into a mixed integer linear programming framework for joint optimization. By ensuring the isolation of conflicting flows and optimizing the coordinated release of non-conflicting traffic, the proposed method enhances intersection throughput while maintaining safety. To ensure the real-time applicability of the cooperative optimization strategy, this study employs an iterative Benders decomposition algorithm to reduce computational costs and mitigate the impact of prolonged solution times on optimization accuracy. Compared to leading vehicle guidance and fixed-phase cooperative optimization methods, the proposed framework reduces average delay by 13.37% and 23.4%. These results demonstrate that the proposed method effectively balances computational efficiency and traffic performance, making it a promising solution for real-world intersection management.