An Extended Car-Following Model considering the Driver’s Desire for Smooth Driving and Self-Stabilizing Control with Velocity Uncertainty

Abstract

In this paper, an extended car-following model with consideration of the driver’s desire for smooth driving and the self-stabilizing control in historical velocity data is constructed. Moreover, for better reflecting the reality, we also integrate the velocity uncertainty into the new model to analyze the internal characteristics of traffic flow in situation where the historical velocity data are uncertain. Then, the model’s linear stability condition is inferred by utilizing linear stability analysis, and the modified Korteweg-de Vries (mKdV) equation is also obtained to depict the evolution properties of traffic congestion. According to the theoretical analysis, we observe that the degree of traffic congestion is alleviated when the control signal is considered, and the historical time gap and the velocity uncertainty also play a role in affecting the stability of traffic flow. Finally, some numerical simulation experiments are implemented and the experiments’ results demonstrate that the control signals including the self-stabilizing control, the driver’s desire for smooth driving, the historical time gap, and the velocity uncertainty are of avail to improve the traffic jam, which are consistent with the theoretical analytical results.

Modeling and Analyzing for a Novel Continuum Model Considering Self-Stabilizing Control on Curved Road with Slope

“…Based on the FVD model, Li et al [38] proposed a new car-following model. They considered the impact of the driver's desire and the self-stabilizing control on traffic flow stability, and the extended model can be expressed as…”

Stabilization Strategy of a Novel Car-Following Model with Time Delay and Memory Effect of the Driver

“…(2) This study comprehensively designs control term parameters to mitigate delayinduced unstable traffic flow. (3) The control strategy of this study considers the influence of multiple time delays on the traffic flow, which is closer to the actual traffic situation. (4) The IDISM and Hopf bifurcation analysis methods are used to determine the stability interval of the system.…”

“…For many years, a large number of researchers have participated in the study of traffic flow dynamic characteristics. In today's traffic field, traffic flow models can be divided into microscopic models [1][2][3], mesoscopic models [4,5], and macroscopic models [6][7][8].…”