String Stability Analysis of Mixed CACC Vehicular Flow With Vehicle-to-Vehicle Communication

Abstract

This paper focuses on traffic scenarios randomly mixed with cooperative adaptive cruise control (CACC) vehicles and manual vehicles with vehicle-to-vehicle (V2V) communication. The analytical investigation of string stability of such mixed traffic flow is conducted under different CACC penetration rates. The parametric sensitivity analysis on CACC desired time-gap is also studied. Moreover, numerical simulation is conducted under both open and periodic boundary conditions. Research results indicate that increase of CACC vehicles is helpful for improving the mixed traffic flow string stability. The mixed flow will be stable for all possible velocities if CACC rate reaches to 0.64 when the CACC time-gap is considered as 0.6s. Larger CACC time-gap would have more stable regions in string stability charts with respect to equilibrium velocity and CACC penetration rate. This paper contributes to a new way for analytical investigation of string stability of the mixed CACC traffic flow.

On the Progressive Introduction of Heterogeneous CACC Capabilities

“…Finally [23] provides an approximated analysis of string stability for vehicles that mix human driven and PATH controlled vehicles as a function of the CACC penetration rate. The key approximations in this paper lies in considering only 50 vehicles, considering a small deceleration perturbation of the group of cars, and finally in the lack of definition of the vehicle string mixture, specifying only the fraction of vehicles that are controlled by CACC.…”

Proposed Empirical Approach to Measuring Traffic String Stability

“…Local stability (Sun et al 2018;Zhang and Jarrett 1997) can be defined as the disordered traffic movement between a leaderfollower pair under car-following conditions. At the same time, string stability Qin and Li 2020) is the propagation of disturbances from one following vehicle to another over the chain of vehicles. Further, with the development of numerous car-following models, researchers in the past attempted to study stability using those models, such as Bando et al (1995) with the optimum velocity model, Yang et al (2013) with the safety distance model, and Tordeux et al (2010) with the Newell carfollowing model.…”

“…Numerous researchers worked in this direction, with autonomous vehicles as a critical component (Milanés and Shladover 2014;Papadoulis et al 2019;Pereira and Rossetti 2012;Van Arem et al 2006;Ye and Yamamoto 2018). From the literature on understanding traffic string stability, researchers focused on numerous concepts, including heterogeneous driving characteristics Yao et al 2021), cooperative adaptive cruise settings , vehicle communications (Qin and Li 2020), mixed cooperative cruise control settings (Qin et al 2017), stability frameworks Zhang et al 2019), delay analysis (Zhang et al 2020), empirical analysis (Makridis et al 2020), platooning (Guo et al 2020;Ruan et al 2021;Zhao et al 2020), nonlinear platooning of vehicles (Hao et al 2020), and so on.…”

Quadratic programming-based cooperative adaptive cruise control under uncertainty via receding horizon strategy

“…However, CVs incorporate vehicular communication technologies, such as V2V communication, into the modern autonomous systems such as CACC via cooperative sensing and control. In this work, we exploit the V2V communication benefits (Darbha et al, 2018) due to its promising potential in increasing traffic stability, safety, and capacity (Chen et al, 2019;Milane´s et al, 2013;Qin and Li, 2020;Talebpour and Mahmassani, 2016;Wang et al, 2020;Zhou et al, 2017).…”