I think it's essentially begging the question. Van Gelder is questioning whether there is computation going on at all, so to say that dynamical systems abstract away from the details of the information-processing mechanisms is obviously to assume that computation is going on. That might be a way somebody already committed to computationalism could look to incorporate dynamical systems theory but it's not a response to Van Gelder. This is obvious from the traffic analogy. The dynamical account of traffic is obviously an abstraction from what actually happens (internal combustion engines, gasoline, etc). But the analogy only holds with cognitive science if you assume what actually happens in cognitive systems to be computation. What Van Gelder is doing is criticising computationalism for not be able to properly account for things that are critical to cognition (such as evolution in time). It's not clear to me what it could mean to abstract away from computational models in order to study how systems evolve over time if those models do not themselves say anything about how they evolve over time. I think Van Gelder addresses this. It's difficult to get an algorithmic model to be time-sensitive.

That said, whether the dynamical approach alone is adequate to capture everything about cognition is another matter. There are alternative approaches that provide an adequate description of mechanisms but that are more sensitive to the issue of time. For example, see Anthony Chemero's Radical Embodied Cognitive Science where he argues that we need ecological psychology to make sense of the mechanisms behind the dynamics. Typically dynamicists operate on a embodied/ecological perspective and don't simply claim that the equations are the whole explanation (they are concerned with, say, neurons, bodies, the environment, etc). I think Bermudez is also confused about levels here. Presumably the mechanism level for cognition is the brain and its neurons, and perhaps the body and parts of the environment, and a computational account is an abstraction from those mechanisms just as much as a dynamical equation is. It's common in computationalism to confuse and conflate identifying the brain as a computer with merely claiming that a computational approach gives an adequate descriptive account of some process is the brain. So, for example, I could argue that an algorithm gives an adequate description of a given brain process because it is not time sensitive and can therefore be described as a sequence of successive states without reference to its evolution in time. But that would not imply that the underlying mechanisms are computational, only that a computational description gives an adequate account.