## 1 Introduction
They explored the effect of the WCL length on the energy consumption and traffic efficiency. However, the described model does not integrate wireless charging for CAEFVs with the upstream and downstream urban signal intersections. Therefore, this study proposes a wireless charging scenario for CAEFVs through signalised intersections and different passing strategies to satisfy the charging requirements of vehicles travelling under different circumstances. To improve the eco-driving control, [PERSON] et al. [40] used a model-predictive control approach to control the trajectory of automated vehicles and proposed a real-time cooperative eco-driving control model for hybrid automated vehicles and human-driven vehicles approaching signalised intersections. [PERSON] et al. [41] developed an eco-driving model with a deceleration strategy that considered the signal phase, timing, and vehicle status at signalised intersections. This model could guide vehicles through an intersection without stopping by analysing the red- and green-light conditions at the signalised intersection and slowing them down in advance. [PERSON] et al. [42] considered the internal functionalities of a powertrain and introduced a battery thermal effect into a powertrain-based longitudinal dynamic model of EVs using a holistic approach to design optimal driving strategies. By combining eco-driving and traditional cooperative adaptive cruise-control technology, [PERSON] et al. [43] proposed an ecological cooperative adaptive cruise-control model to enable energy optimisation and multi-vehicle speed trajectory planning. [PERSON] et al. [44] used motion wave and car-following models to design an eco-driving algorithm based on connected and automated technology. The utilised algorithm accurately estimated the time point at which each vehicle entered a signalised intersection from signal timing and the vehicle speed. It then developed a corresponding advisory speed limit approach for each automated vehicle to allow the speed-controlled vehicles enter the intersection at the allocated time, thus achieving the objective of easing traffic fluctuations and improving traffic congestions. However, wireless charging scenarios were not considered in the described eco-driving model. Table 1 summarises the aforementioned eco-driving related works available in the literature; the last row refers to the contribution provided by this study. In this study, wireless charging technology was used to enable the slow movement of CAEFVs at traffic lights for energy replenishment by placing WCLs upstream and downstream of signalised intersections. On this basis, various passing strategies were designed to ensure that CAEFVs could pass through signalised intersections without stopping and satisfy the charging requirements of different vehicles. The traffic benefits of each mode were analysed at different initial speeds, charging efficiencies, and WCL lengths to conduct charging during walking and speed planning of CAEFVs. The remainder of this paper is organised as follows: Section 2 describes a wireless charging scenario at a signalised intersection. Section 3 outlines the optimal driving model and passing strategies applicable to the above-mentioned scenario. Experiments and comparative analyses are conducted in Section 4 to verify the validity of the proposed model. Finally, concluding remarks are presented in Section 5.