With the proliferation of location-based services, mobile devices, and embedded wireless sensors, more and more applications are being developed to improve the efficiency of the transportation system. In particular, new applications are arising to help vehicles locate open parking slots. Nevertheless, while engaged in driving, travelers are better suited being guided to an ideal parking slot, than looking at a map and choosing which slot to go to. Then the question of how an application should choose this ideal parking slot becomes relevant. Vehicular parking can be viewed as vehicles (players) competing for parking slots (resources with different costs). Based on this competition, we present a game-theoretic framework to analyze parking situations. We introduce and analyze parking slot assignment games and present algorithms that choose parking slots ideally in competitive parking simulations. We also present algorithms for incomplete information contexts and show how these algorithms outperform even algorithms with complete information in some cases.