For smooth and efficient vehicle-to-vehicle interactions in mixed traffic, comprising automated vehicles (AVs) and manually driven vehicles, AVs need to be able to anticipate future states of driving scenes and coordinate interactions with surrounding road users. Thus, the communication behavior of manual drivers needs to be investigated and could serve as a basis for AVs’ driving functions. Due to the high demand for coordinating and anticipating driving maneuvers in high-speed lane change scenarios and in low-speed shared space interaction scenarios, the behavior of human road users in these scenarios should be further analyzed. Therefore, driving cues that are applied for anticipating lane change maneuvers and manual drivers’ gap acceptance for initiating turning actions were investigated in a combined driving simulator study, in which N = 29 participants contributed. The results revealed that participants applied driving cues such as speed and position of surrounding vehicles (i.e., implicit driving cues) as a source of information to predict upcoming lane change maneuvers of other road users. Moreover, participants anticipated the development of driving scenes by considering the speed of encountering vehicles when selecting gaps for initiating turning maneuvers. This human driver behavior should therefore be considered for integration into AVs, as this enables an early anticipation of future states of driving scenes and adapting driving actions accordingly. Thus, such established interaction capabilities, based on implicit cues, can allow for intuitive encounters with surrounding road users in mixed traffic.