Previous studies used an adaptive time gap strategy to stabilise the head-to-tail string stability by connected and automated vehicles (CAVs). However, this strategy can bring an adverse effect on traffic throughput. Moreover, at a lower market penetration rate of CAVs, it is also difficult to implement a larger adaptive time gap to dampen the unstable traffic conditions. To this end, this study proposes cooperative control strategies to improve the mixed traffic throughput and stabilise the head-to-tail string stability in an intelligent road system (IRS) environment. The mixed traffic was composed of autonomous vehicles (AVs) with string instability/stability, and CAVs with low penetration. The feasible stable control parameters of AVs and CAVs are computed and implemented into the cooperative control strategies. The results show that the cooperative control strategies have better performances in improving traffic throughput and stabilising the overall head-to-tail string stability. Moreover, analytical solutions and simulation experiments are conducted to verify the effectiveness of the proposed control strategies subject to exogenous disturbances. The cooperative control strategies can be potentially applied to alleviate the mixed traffic problems, with the advanced connection and automation technologies in an IRS environment.

中文翻译：

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在智能路边系统环境中，协调控制策略可稳定高速公路的混合交通稳定性并提高交通吞吐量

先前的研究使用自适应时间间隙策略来通过连接的和自动的车辆（CAV）来稳定头对尾的弦稳定性。但是，此策略可能会对流量吞吐量产生不利影响。此外，在CAV的市场渗透率较低的情况下，也难以实施较大的自适应时间间隔以缓解不稳定的交通状况。为此，本研究提出了一种协作控制策略，以提高混合交通流量并在智能道路系统（IRS）环境中稳定首尾字符串的稳定性。混合交通由具有不稳定性/稳定性的自动驾驶汽车（AV）和低穿透性的CAV组成。计算AV和CAV的可行的稳定控制参数，并将其实现为协调控制策略。结果表明，协同控制策略在提高通信量吞吐量和稳定整体头对尾字符串稳定性方面具有更好的性能。此外，进行了分析解决方案和模拟实验，以验证所提出的受到外来干扰的控制策略的有效性。借助IRS环境中的高级连接和自动化技术，可以将协作控制策略潜在地应用于缓解混合交通问题。