Multi-rhythm control for heterogeneous traffic and road networks in CAV environments

Abstract

Heterogeneity is widely observed in various aspects of urban transport, such as road types, vehicle dynamics, and demand patterns, which greatly complexifies transport systems and hinders the successful control and management of traffic. On one hand, intelligent strategies are required to relieve the loss of efficiency caused by the mixed traffic flow composed of vehicles with different speeds; on the other hand, the spatial heterogeneity of travel demand distribution requires pertinent control schemes to improve the network-level mobility and the phenomenon of oversaturation under heavy traffic also demands an appropriate way to resolve. Leveraging the advantages of connected and automated vehicle (CAV) technology, this study proposes a multi-rhythm control (MRC) scheme to accommodate heterogeneous network traffic in a CAV environment with 100% penetration rate. While the rhythmic control (RC) proposed by (Lin et al., 2021) could organize traffic efficiently and in an orderly manner, the multi-rhythm strategy has greater potential to not only improve the efficiency of heterogeneous traffic by the design of different virtual platoons (VPs) catering to different vehicle types, but also address the spatial heterogeneity of network traffic by implementing differentiated cycle lengths among the road network. For the optimal design of the MRC scheme, a two-step model is developed to minimize the total travel cost, where the first step focuses on the mesoscopic level to jointly optimize the multi-rhythm scheme, VP design and lane configuration for both undersaturated and oversaturated cases, while the second step focuses on the microscopic design to optimize the space–time trajectories of VPs under the premise of collision free. Numerical examples and simulation experiments are conducted to test the performances of the MRC scheme compared to a naive version of RC with a homogeneous rhythm and a traffic signal control (TSC) strategy. The results show that among all control strategies, the MRC scheme has the best performance under all kinds of demand patterns, which is reflected in both the lowest travel cost and the highest network throughput.