Cooperative Merging Control for Heavy-Duty Trucks Based on Linear Quadratic Path-Following Control

The Japanese logistics industry has been actively researching and developing autonomous trucks to address challenges such as truck driver shortages and increasing transportation demands. In particular, infrastructure-coordinated autonomous driving has gained attention, leading to the development of systems that assist merging by providing real-time information on mainline vehicles to automated trucks via sensors installed at merging points. This approach is expected to reduce traffic congestion and enhance safety during merging. In this study, we propose a merging control algorithm that integrates path-following control based on optimal control theory with infrastructure coordination to facilitate the merging of automated trucks and optimize traffic flow. Simulation results demonstrate that the proposed algorithm ensures highly accurate path following, improves the merging success rate, and reduces merging start time.