In this talk, I will present the derivation of microscopically controlled Generic Second Order Models (GSOMs) of vehicular traffic out of a Follow-the-Leader particle description via a collisional kinetic approach. In certain randomly selected pairs of interacting vehicles, we introduce a binary control modeling the automatic feedback of a driver-assist vehicle participating in the interaction. Next, we upscale such controlled particle dynamics by means of an Enskog-based hydrodynamic limit, whence we recover a class of GSOMs that contain a control term inherited from the microscopic vehicle interactions. We show that this control may be chosen so as to optimize global traffic trends, such as e.g., the vehicle flux or the road congestion, constrained by the GSOM dynamics, thereby realizing a multiscale path from the vehicle-wise implementation of a driver-assist control to its optimal hydrodynamic design. This is joint work with F. A. Chiarello (Politecnico di Torino) and B. Piccoli (Rutgers University - Camden). The content of the talk is based on the paper: F. A. Chiarello, B. Piccoli, A. Tosin. Multiscale control of generic second order traffic models by driver-assist vehicles, Multiscale Model. Simul., 19(2):589-611, 2021