Given the escalating population across the globe, it has become paramount to construct smart cities, aiming for improving the management of urban flows relying on efficient information and communication technologies (ICT). Vehicular sensing networks (VSNs) play a critical role in maintaining the efficient operation of smart cities. Naturally, there are numerous challenges to be solved before the wide-spread introduction of VSNs, including the conception of an accurate topological analysis method and a beneficial cooperation mechanism during the process of city-wide information sharing. Hence, in this article, we construct a VSN-aided smart city model and appraise a range of intelligent applications in terms of both public services and urban flow management. Then, the information source selection algorithm of a complex network and a reinforcement learning based city information sharing mechanism are considered, complemented by a range of open challenges.