Failure in change detection in the surrounding environment while driving is attributed among other things to the number of incidents and the density of them occurring along the task as this is directly related to an increase in cognitive load. Here, we investigate the role of time proximity between events on the detection performance during a naturalistic driving task in a virtual simulation. Participants performed a change detection task while driving, in which we systematically manipulated the time difference between changes and we analysed the effect on detection performance by the driver. Our research demonstrates that events occurring simultaneously deteriorate detection performance (in terms of detection rate, and detection time), while performance improves as the temporal gap increases. Moreover, the outcomes suggest that the duration of an event affects the detection of the following one, with better performance recorded for very short or very long duration events and worse for medium duration events between (5-10 sec). These outcomes are crucial for driving assistance and training, considering the detection of safety-critical events or efficient attentional disengagement on time from irrelevant targets.