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The deployment of automated vehicles (AVs) has generated high societal expectations. However, due to the absence of the driver role, the communication issues between pedestrians and AVs have not yet been solved. Previous research has shown the crucial role of implicit signals in this context. However, it is still unclear how pedestrians subjectively estimate vehicle behaviour and if pedestrians incorporate these estimations as part of their crossing decisions. For the first time, this study explored the impact of implicit signals both on pedestrians' subjective estimations of approaching vehicle behaviour across a wide range of experimental traffic scenarios and on their crossing behaviour in the same scenarios through a comprehensive analysis. Two simulator tasks, ie, a natural road crossing task and a vehicle behaviour estimation task, were designed with time to collision, vehicle speed, and braking behaviour controlled. A novel finding is that the correlation between crossing decisions and vehicle behaviour estimations depends on the traffic scenario. That is, pedestrians could recognise the vehicle's different braking behaviours and that their crossing decisions aligned well with their subjective estimates, supporting the idea that pedestrians actively estimate vehicle behaviour as part of their decision-making process. However, if the traffic gap is big enough, there is a separation between crossing decisions and estimations about vehicle behaviour. We further showed that pedestrians crossed the street earlier and estimated yielding behaviour more accurately in early-onset braking scenarios than in late-onset braking scenarios. Interestingly …