  Reliable wireless communication between the autonomously driving cars is one
of the fundamental needs for guaranteeing passenger safety and comfort.
However, when the number of communicating cars increases, the transmission
quality may be significantly degraded due to too high occupancy radio of the
used frequency band. In this paper, we concentrate on the autonomous
vehicle-platooning use-case, where intra-platoon communication is done in the
dynamically selected frequency band, other than nominally devoted for such
purposes. The carrier selection is done in a flexible manner with the support
of the context database located at the roadside unit (edge of wireless
communication infrastructure). However, as the database delivers only context
information to the platoons' leaders, the final decision is made separately by
the individual platoons, following the suggestions made by the artificial
intelligence algorithms. In this work, we concentrate on a lightweight
Q-learning solution, that could be successfully implemented in each car for
dynamic channel selection.
