Merging Vehicles at Junctions using Mixed-Integer Model Predictive Control

Abstract

A method is proposed for vehicle merging scenarios in junctions with relative cost prioritization. The method is based on Model Predictive Control, employing Mixed Integer Quadratic Program optimization. The scheme provides optimal control properties while maintaining safety and recursive feasibility. The latter properties are ensured through positive control invariance of simple time headway constraints. For examples with two vehicles, tunable prioritization and gap acceptance are verified and presented on a decision graph. Priorities are then demonstrated to be respected in an example with four vehicles.