Automated driving, which is considered to be able to reduce driving workload, enhance driving safety and improve traffic efficiency, has become a research hotspot in recent years. It is believed that traffic flow will consist of manual vehicles and automated vehicles at different automation levels in the near future. Researchers have carried out many studies on mixed traffic; most of them focus on the highway scenario. However, the majority of traffic occurs in urban/suburban road networks, which contains many different scenarios, such as expressways, merging/diverging areas, signalised intersections, trunk roads, branch roads, etc. To evaluate the effect of automated driving in a more realistic way, the authors first take adaptive cruise control (ACC) and cooperative ACC as representatives of automated driving. Then, the authors make simulations at the road network level and investigate macroscopic fundamental diagram in different scenarios. Results show that compared to a highway, the improvement of traffic flow is significantly limited in the road network.

中文翻译：

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道路网络环境下自动驾驶效果的仿真研究

自动驾驶被认为能够减少驾驶工作量，提高驾驶安全性并提高交通效率，这已成为近年来的研究热点。人们认为，在不久的将来，交通流量将由手动和自动程度不同的自动车辆组成。研究人员对混合流量进行了许多研究。他们中的大多数关注高速公路情况。但是，大部分交通流量发生在城市/郊区的道路网络中，其中包含许多不同的场景，例如高速公路，合并/分叉区域，信号交叉口，主干道路，支路等。在更多情况下评估自动驾驶的效果现实的方法是，作者首先采用自适应巡航控制（ACC）和协作式ACC作为自动驾驶的代表。然后，作者在道路网络级别进行仿真，并研究不同情况下的宏观基础图。结果表明，与高速公路相比，路网中交通流量的改善受到明显限制。