Research on the Comparison of Vehicle Speed Control Models in the Connected and Autonomous Vehicle Environment

To exaggerate traffic congestion, relaying on speed control strategy in the signalized intersection, using traffic efficiency and fuel consumption as the optimization goal, three speed guidance control models at isolated intersections was proposed, which were real-time based model, arrival-based model and considering queue model. PTV Vissim was used to simulate the situations with or without speed control model, different speed control model and different permeability respectively, and compared the average delay, average stop times, fuel consumption and vehicle trajectory at intersections under different conditions. By comparing the vehicle trajectory under different permeability, the variation and causes of vehicle trajectory and traffic flow under different vehicle composition were analyzed. Several evaluation indices for the three speed control models were compared, which shows that among the three speed guidance control models, the real-time based model has better performance in reducing average delay and fuel consumption than arrival-based model, by reducing 46.3% and 10.9% respectively, and There is no significant difference with the considering queue model. Real-time based model can significantly improve traffic efficiency and fuel economy.