Optimization Based Merging Coordination of Connected and Automated Vehicles and Platoons

Vehicle platooning is an emerging and promising technology with the benefit of fuel-saving and traffic capacity improvement, but the presence of long platoons near merging roads could act as a long barrier for merging traffic. This can lead to merging failure and traffic performance degradation without proper treatment. This paper addresses the merging coordination problem for Connected and Automated Vehicles (CAVs) and Platoons of CAVs to achieve an efficient traffic flow at the merging zone without collisions. We present a bi-level framework where we decouple traffic coordination from vehicle motion control. At the traffic coordination level, a centralized coordinator schedules a merging time and speed for each approaching CAV passing through the merging point with Mixed Integer Linear Programming (MILP). The goal of the coordinator is to optimize traffic performance while considering the presence of platoons. At the vehicle control level, each vehicle plans its motion with the assigned schedule as terminal constraints. The individual motion plan is then followed by the vehicle while keeping a minimum safety distance to its neighbor. The resulting solution is evaluated in simulation and it is shown that our coordination framework can adequately manage traffic for the on-ramp merging scenario with CAVs and platoons.