Modeling and Analysis of Car-Following for Intelligent Connected Vehicles Considering Expected Speed in Helical Ramps

Abstract

In this paper, to explore the influence of expected speed on traffic flow in helical ramps, a new car-following model for intelligent connected vehicles (ICVs) was established for helical ramps, mainly considering the expected speed provided in the vehicle-to-everything (V2X) environment. On this basis, sufficient conditions to ensure the stability of the traffic stream were met and the congestion propagation mechanism was discussed by using a linear stability analysis and nonlinear stability analysis. The results showed that the ICVs can effectively increase the stability of the traffic flow by considering the expected speed of the helical ramps. When the feedback coefficients of the expected speed of the helical ramps were 0.3 and 0.5, the stability of the traffic flow changed significantly, especially in the uphill section; the feedback coefficient was 0.5 when the traffic flow was completely restored to the initial steady state even under the action of small disturbances. In a difficult field-driving test, this paper showed through a numerical simulation that broadcasting an expected speed to the ICVs in the helical ramps can effectively improve the stability of traffic flow, which provides a theoretical basis for future landing applications of ICVs in complex road scenarios.