Modern technology allows for the detection and identification of a vehicle passing through specific locations on a road network. The most prominent technology in use leverages cameras capable of high speed image capture, back-end extraction of plate numbers, and real time membership queries in multiple databases. Various parties have a vested interest in making use of the kind of data produced by such systems, in particular to deter risky driving, analyze traffic patterns, enable unmanned toll collection, and aid law enforcement agencies. In this paper, we proceed to assess the mass surveillance potential arising from the type and frequency of data collected in these systems. We show that even when restricted to information only about the structure of a road network, one can begin to set up an effective network of traffic monitoring devices to infer the travel destinations of individuals up to a concerning level of precision. We develop a tracker placement algorithm to corroborate this claim, and provide a quantitative evaluation of the privacy risks generated by the network of trackers determined by this algorithm.