Estimation of mixed traffic flow including the impact of bus bay in the connected environment
Document Type
Journal Article
Publication Date
2025
Subject Area
place - urban, mode - bus, infrastructure - stop, operations - traffic, technology - intelligent transport systems, land use - impacts, planning - methods
Keywords
connected and automated bus, fundamental diagram, lane changing control, mixed traffic flow, public transportation
Abstract
The incorporation of connectivity and automation is crucial to the development of urban transportation, with connected and automated buses (CABs) anticipated to enhance network efficiency, however, bus stops, particularly bus bays, will substantially impact surrounding traffic, resulting in lane changes and additional delays. A novel analytical model is derived to capture the dynamics of the mixed traffic flow, which includes CABs, CAVs (connected and automated vehicles), and HVs (human-driven vehicles), according to the fundamental relationship between speed and density. This model separately accounts for the average headway considering platooning intensity, the increase in density due to lane changes, and the additional delay incurred by CABs entering and exiting the bus bay. Furthermore, a simulation model is constructed, wherein control rules for longitude movements and lane-changing maneuvers are defined according to different driving mechanisms. The simulation results are used to propose mutual verification for the accuracy of the proposed analytical model. Furthermore, sensitivity analyses are conducted to assess the influence of various parameters, including the proportion of left-turning buses, the number of arriving CABs, the proportion of stopping buses, and the location of bus bay.
Rights
Permission to publish the abstract has been given by Taylor&Francis, copyright remains with them.
Recommended Citation
Wang, T., Li, X., Qin, B., Xu, W., & Yuan, Y. (2026). Estimation of mixed traffic flow including the impact of bus bay in the connected environment. Journal of Intelligent Transportation Systems, 30(2), 250-267.
