Research on Ramp Merging Strategies Based on Different Traffic Conditions in a Fully Connected Environment

The development of autonomous driving technology faces a significant challenge in effectively addressing the ramp merging task. Current research encounters difficulties in handling the dynamic coupling between the longitudinal speed adjustment of ego vehicles and merging gap selection, as well as ensuring intelligent interaction with mainline vehicles. To tackle this issue, this paper proposes a baseline merging strategy using a virtual fleet in an interconnected environment. Subsequently, dynamic arrival time-based merging strategies are introduced for three cooperative merging scenarios. These strategies aim to synchronize the speed of ego vehicles on the ramp with the fleet on the right side of the mainline while ensuring minimal disruption to the efficiency of upstream vehicles. Simulation results demonstrate that the three cooperative merging strategies outperform the baseline strategy in terms of efficiency and comfort, significantly reducing merging completion time. Notably, Scenario 1 exhibits the shortest merging time, achieving an approximate 8% reduction in overall merging time for the three on-ramp vehicles compared to the baseline strategy. These findings provide valuable insights for researchers to develop ramp merging technologies in a fully connected environment.