Contraflow lane reversal - the reversal of lanes in order to temporarily increase the capacity of congested roads - can effectively mitigate traffic congestion during rush hour and emergency evacuation. However, contraflow lane reversal deployed in several cities are designed for specific traffic patterns at specific hours, and do not adapt to fluctuations in actual traffic. Motivated by recent advances in autonomous vehicle technology, we propose a framework for dynamic lane reversal in which the lane directionality is updated quickly and automatically in response to instantaneous traffic conditions recorded by traffic sensors. We analyze the conditions under which dynamic lane reversal is effective and propose an integer linear programming formulation and a bi-level programming formulation to compute the optimal lane reversal configuration that maximizes the traffic flow. In our experiments, active contraflow increases network efficiency by 72%.