The fast development of communication technique builds an era of Internet of Everything. In the automobile world, Internet-Connected Vehicle (CV), also called IntelliDrive, will accelerate the autonomous driving era’s coming. And the traffic flow theory will undergo major changes as CV platoon becomes common way for our travel. As we know that the CV has different driving decision mechanisms from human-driven vehicles, such as an CV can receive more information and make much faster decision than a human-driven vehicle. Only if we fully understand the autonomous traffic flow’s characteristics, then we can improve the level of traffic engineering study and management in the future. On the thought of building autonomous traffic flow theory, we present CV platoon car-following model as the theoretical microscopic traffic flow model. The model is described by a mathematical differential-difference equation, which has a synthesized optimal velocity differential function and a full platoon with weighted relative velocity difference function. There are three main factors in the model, which are the optimal velocity difference impact factor $p$ and action related vehicle number $l$, and weighted velocity difference sum coefficient $\lambda$. The model reflects the effects of front interactions between every two adjacent CV instead of the weighted average headway in the platoon. We deduce the model’s stability conditions with linear system stability theory and do some computer numerical simulations to verify our suppositions. Simulation results show that the more information broadcasting among CV, the more stable of the traffic flow system is. At last, we discuss our study’s contributions from the viewpoint of theoretical and practical value, and point out future research directions. In a word, the highlight of the paper is that we find the CV platoon system’s running mechanism by building an CV platoon car-following model under connected environment and give its linear stability condition, which is great value for advanced traffic management in autonomous driving era.

通信技术的飞速发展建立了万物互联的时代。在汽车世界中，也称为IntelliDrive的互联网连接的汽车（CV）将加速自动驾驶时代的到来。随着CV排成为我们旅行的常见方式，交通流理论将发生重大变化。众所周知，CV与人类驱动的车辆具有不同的驾驶决策机制，例如CV可以比人类驱动的车辆接收更多信息并做出更快的决策。只有充分了解自主交通流的特征，才能在未来提高交通工程的研究和管理水平。在建立自主交通流理论的思想上，我们提出了CV排车跟随模型作为理论微观交通流模型。该模型由数学差分方程描述，该方程具有综合的最佳速度差分函数和具有加权相对速度差分函数的全排。模型中存在三个主要因素，即最佳速度差影响因素$p$ 与动作有关的车号 $升$和加权速度差和系数 $\lambda$。该模型反映了每两个相邻CV之间的前部交互作用的影响，而不是排中的加权平均前进距离。我们用线性系统稳定性理论推导了模型的稳定性条件，并进行了一些计算机数值模拟以验证我们的假设。仿真结果表明，简历之间的信息广播越多，交通流系统越稳定。最后，从理论和实践价值的角度讨论了本研究的贡献，并指出了今后的研究方向。简而言之，本文的重点是通过建立互联环境下的CV排车跟随模型并给出其线性稳定性条件，来找到CV排系统的运行机制，这对于自动驾驶时代的先进交通管理具有重要的价值。 。