Measuring point traffic volume and point-to-point traffic volume in a road system has important applications in transportation engineering. The connected vehicle technologies integrate wireless communications and computers into transportation systems, allowing wireless data exchanges between vehicles and road-side equipment, and enabling large-scale, sophisticated traffic measurement. This paper investigates the problems of persistent point traffic measurement and persistent point-to-point traffic measurement, which were not adequately studied in the prior art, particularly in the context of intelligent vehicular networks. We propose two novel estimators for privacypreserving persistent traffic measurement: one for point traffic and the other for point-to-point traffic. The estimators are mathematically derived from the join result of traffic records, which are produced by the electronic roadside units with privacypreserving data structures. We evaluate our estimation methods using simulations based on both real transportation traffic data and synthetic data. The numerical results demonstrate the effectiveness of the proposed methods in producing high measurement accuracy and allowing accuracy-privacy tradeoff through parameter setting.