A Ramp Merging Strategy for Automated Vehicles Considering Vehicle Longitudinal and Latitudinal Dynamics

Abstract

Recently, automated vehicles have shown great potential in many driving scenarios, such as merging from on-ramp lanes to the highway. This paper proposed a ramp merging strategy for automated vehicles to merge from on-ramp lanes to the highway. According to the collected spatial and temporal data for vehicles, we first generate possible merging gap options. Then for different merging gap options, we use trajectory planning to determine the merging path and velocity profiles to help the vehicle merge with time-dependent longitude and latitude position references. Note that the optimized trajectory planning can be computed with high computational efficiency using QP (Quadratic Programming) model and can guarantee safety using the discretized space technique and linear collision-free constraints' construction. Finally, we select the best merging gap and corresponding planned trajectory with the minimum fuel consumption. The numerical experimental results show that the proposed model can select an environmentally friendly merging gap and plan a safe and comfort trajectory for the vehicle. Also, the results show that the controlled vehicle can enter the main lane with little speed difference, which suggests that the proposed model can avoid speed oscillation caused by merging behavior and increase traffic efficiency. It is hoped that this study can facilitate real-time computation and guarantee the safety and efficiency of the trajectory planning process for merging automated vehicles.