Collaborative optimization of battery electric bus scheduling and charging considering arterial signal coordination under connected environment

As a strategic pathway to decarbonization, electrification provides an effective solution for achieving low or even net-zero carbon emissions in transportation systems. Static wireless charging (SWC) presents a promising charging strategy by utilizing the dwell time of battery electric buses (BEBs) at bus stations. This approach can effectively mitigate operational challenges such as limited range and prolonged charging times for connected-battery electric buses (C-BEBs). This study proposes a collaborative optimization model for C-BEB scheduling and charging considering arterial coordination under connected environment. The model uses mixed integer linear programming (MILP) to develop an arterial signal coordination control approach that considers the operation efficiency of regular vehicles (RVs) and the constraints that C-BEBs passing through signalized intersection without stopping. Additionally, a collaborative optimization model for bus scheduling and charging is constructed, which considers bus headway, bunching, passenger demand, non-stop constraints for C-BEBs, and speed and stop duration limits. This model can enable C-BEBs to flexibly adjust stop time for wireless static charging while maintaining good operational efficiency and planning. Simulation experiment based on real bus lines in Hangzhou shows that the proposed model can charge buses that lack power during operation with almost no impact on overall efficiency. This not only enhances the operational stability of the bus system but also reduces the need for additional backup buses prepared for situations where buses terminate mid-route due to power shortages, thereby lowering the purchasing costs for bus operators.