This article considers the problem of traffic control in which an autonomous vehicle is used to regulate human-piloted traffic to dissipate stop-and-go traffic waves. We first investigated the controllability of well-known microscopic traffic flow models, namely, (i) the Bando model (also known as the optimal velocity model), (ii) the follow-the-leader model, and (iii) a combined optimal velocity follow-the-leader model. Based on the controllability results, we proposed three control strategies for an autonomous vehicle to stabilize the other, human-piloted traffics. We subsequently simulate the control effects on the microscopic models of human drivers in numerical experiments to quantify the potential benefits of the controllers. Based on the simulations, finally, we conduct a field experiment with 22 human drivers and a fully autonomous-capable vehicle, to assess the feasibility of autonomous vehicle-based traffic control on real human-piloted traffic. We show that both in simulation and in the field test that an autonomous vehicle is able to dampen waves generated by 22 cars, and that as a consequence, the total fuel consumption of all vehicles is reduced by up to 20%.