Analysis of the impact of large vehicles in merging areas based on driver characteristics under vehicle-road coordination

Abstract

The lane-changing behavior of vehicles in highway merging areas is a crucial factor affecting road flow and safety. Due to the size and power performance limitations of large vehicles, they cause more significant interference to the surrounding vehicles, thereby reducing the traffic capacity of the main road and ramp in the merging area. To study the impact of large vehicles on the driving behavior of different types of drivers in highway ramp merging sections, this paper analyzes the driving behavior differences of different driver types based on the vehicle driving state data from the Mirror-Traffic database. It constructs a vehicle gap acceptance model for highway ramp merging sections under the influence of large vehicles and verifies the rationality of the model. On this basis, taking the unidirectional three-lane highway ramp merging area under the condition of vehicle-road coordination as the research object, the game benefit function of merging vehicles in the merging area is redefined. To achieve optimal traffic efficiency in the merging area and minimize vehicle travel time and delay, an induction optimization method and a cooperative control strategy are proposed, and a group vehicle induction distribution optimization model is established. The multi-vehicle cooperative induction distribution method can adjust the merging speed and position of vehicles, optimizing vehicle merging trajectories. Simulation results show that under the condition of vehicle-road coordination, the average speed of the group of vehicles increased by 5–15 %, the average flow increased by 8–16 %, vehicle collision safety was improved, vehicle delay time was significantly reduced, and with the increase in traffic flow in the merging area, the optimization effect became more significant.