One of the important goals of a smart city is to increase the quality of urban mobility. This paper will explore the use of dynamic tariffs for this purpose. Transactive control, the concept of feedback through economic transactions, is a promising concept for accomplishing such dynamic tariffs, and is the focus of this paper. Two specific examples of transactive control are considered in this paper, the first of which is the synthesis of dynamic toll prices with the goal of reducing traffic congestion in highways. We examine how a model-based approach can result in optimal toll pricing schemes. Sociotechnical models that combine behavioral models of drivers and traffic flow models, together with real-time traffic information obtained from on-road sensors are used to determine the transactive control strategies. The overall pricing strategy is evaluated using real traffic data from an existing dynamic toll-pricing framework. The second example of transactive control is in the context of Mobility on Demand (MoD), where new modes of transportation other than private and public are being proposed, providing a smorgasbord of options for passengers. We investigate a dynamic routing concept for multipassenger transport, and propose a transactive control strategy to regulate the achievable performance around desired values. Numerical simulations using actual passenger data are carried out to demonstrate the advantages of the proposed concept.