Speed guidance strategy at intersections based on platoon recognition in connected and autonomous vehicles environments

To alleviate the issues of widespread traffic congestion and low passage efficiency at urban signalised intersections, which result in increased vehicle energy consumption, this paper proposes a speed guidance strategy based on platoon recognition in connected and autonomous vehicle (CAV) environments. The study focuses on vehicle platoons, considering the impact of varying CAV penetration rates, CAV aggregation intensity and the spatio-temporal distribution of mixed traffic flows. Six distinct platoon passage scenarios through intersections are defined, based on whether platoons encounter obstructions. Three distinct guidance strategies are proposed for these scenarios: acceleration guidance, deceleration guidance and platoon splitting. Finally, a case study on secondary development based on Vissim is conducted. The results show that the platoon-based speed guidance strategy reduces vehicle fuel consumption (from 3.152 to 0.600 L/s), delay time (from 9.22 to 3.79 s), and the number of stops (from 0.18 to 0.04 times) compared to no speed guidance Furthermore, the effectiveness of platoon-based speed guidance strategies varies with CAV penetration rates. As the CAV penetration rate approaches 0.7, the benefits to traffic of the guidance strategy become more apparent. The most significant reductions were observed in fuel consumption, delay time and the number of stops: 40%, 37% and 23%.