It is concerned that system-level benefits of connected automated vehicle control might only prevail in a far-future centralized control environment, whereas the benefits could be much offset in a near-future decentralized control system. To address this concern, this paper proposes a decentralized control model for connected automated vehicle trajectory optimization at an isolated signalized intersection with a single-lane road where each connected automated vehicle aims to minimize its own travel time, fuel consumption and safety risks. To improve the computational tractability, the original complex decentralized control model is reformulated into a discrete model. A benchmark centralized control model is also formulated to compare with the decentralized control model. The DIRECT algorithm is adopted to solve the above models. Numerical results show that the decentralized control model has better computational efficiency (with an average solution time of 10 s) than the centralized control model (with an average solution time of 60 s) without significant loss of the system optimality (with an average of 3.91%). Finally, analysis on connected automated vehicle market penetration shows that the extra benefit of the centralized control model is not obvious either in under-saturated traffic (less than 1%) or at a low connected automated vehicle market penetration rate in critically-saturated and over-saturated traffic (less than 3% when the market penetration rate is lower than 20%). The results suggest that, as apposed to the earlier concern, the near-future decentralized control scheme that requires less technology maturity and infrastructure investment can achieve benefits similar to the far-future centralized control scheme with much simpler operations in under-saturated traffic, or in critically-saturated traffic and over-saturated traffic with a low connected automated vehicle market penetration rate.

令人担忧的是，连接的自动车辆控制的系统级优势可能只会在未来的集中控制环境中占上风，而在不久的将来的分散控制系统中，优势可能会被抵消。为了解决这一问题，本文提出了一种分散控制模型，用于在具有单车道道路的隔​​离信号交叉口处实现联网自动汽车的轨迹优化，其中每个联网自动汽车旨在最大程度地减少自身的行驶时间，燃料消耗和安全风险。为了提高计算的可处理性，将原始的复杂分散控制模型重新构造为离散模型。还制定了基准集中控制模型，以与分散控制模型进行比较。采用DIRECT算法求解上述模型。数值结果表明，分散控制模型的计算效率（平均求解时间为10 s）比集中控制模型（平均求解时间为60 s）更好，而系统最优性的平均损失为3.91 ％）。最后，对联网自动驾驶汽车市场渗透率的分析表明，集中控制模型的额外优势在交通流量不足饱和（小于1％）或在临界饱和和超载的自动化汽车市场渗透率较低的情况下并不明显。 -饱和流量（当市场渗透率低于20％时，低于3％）。结果表明，与先前的关注相适应，