Collaborative optimization of signals and ecological driving speed guidance for buses without dedicated bus lanes in the connected environment

The transit signal priority, as an effective method to address public transport operation issues, has been widely applied. With the continuous advancement of connected technology, research on developing transit signal priority strategies using vehicle-to-everything technology is gaining increasing attention. However, current traffic signal priority studies primarily focus on optimizing bus speeds on dedicated bus lanes, neglecting the adverse impacts of private vehicle queuing on priority strategies, as well as the carbon emissions resulting from speed fluctuations. To more effectively evaluate the optimization effect of bus priority in the absence of dedicated bus lanes, this paper proposes a cooperative control method combining signal control and eco-driving speed guidance in a connected environment. The objective is to maximize the reduction in delays for both buses and private vehicles at intersections and optimize carbon emission reduction. Initially, an Extended Kalman Filter is employed to predict the arrival time of buses at intersections and the signal status. Building upon this, optimal timings for phase adjustments and the optimization bus trajectories are calculated using signal control and eco-driving speed guidance models. Then a Genetic Algorithm is used to solve the model. Finally, the effectiveness of the proposed model is verified using Zhengzhou city as a case study and compared against scenarios involving NTSP, TSP, and speed guidance. The results demonstrate that, in the absence of dedicated bus lanes, the proposed method not only ensures the stability of bus operations but also achieves significant bus priority and carbon emission benefits while mitigating the adverse impact of bus priority on private vehicles to a certain extent.