ently predicting the QoS along planned vehicle trajectories, as an example of the type of problems that need to be solved for a successful ITS deployment. While it is generally beneficial to have both accurate and timely predictions of the radio environment at locations along the route of a vehicle, it is of particular importance in the context of MEC as these conditions can trigger: Initiation of certain V2X functionalities; Download of content delivery/software packages. As explained above, MEC is a technology allowing applications to be instantiated at the edge of the access network, providing low latency applications in close proximity to user terminals. However, in V2X system scenarios characterized by high mobility, the infor- mation related to radio network conditions centrally collected by a MEC host may not be always up to date. The accuracy and the timeliness of the information collected are ham- pered by the environmental situation, for example, the occurrence of network congestion events when, for example, many vehicles attempt to provide radio measurements to the connected eNB/gNB, which is collocated with a MEC host. It is also affected by the deploy- ment density of the cellular network, together with the capabilities of the deployed MEC infrastructure. To illustrate the impact of the above-mentioned limitations on system performance we use an example of a vehicle en route from location A to location B and a related MEC application that would need to be informed of radio conditions along that route. The MEC application may need to have that information ahead of time in order to make timely deci- sions, such as: Enabling/disabling autonomous driving features; Downloading infotainment content; Scheduling software over the air/firmware over the air (SOTA/FOTA) updates, etc. According to the current specification, journey-specific environmental/situational infor- mation will only be available to vehicles together with a bulk of other data, most of which is irrelevant to the planned route. This is subop