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 spaces. Nevertheless, while engaged in driving, travelers are better suited being guided to a particular and ideal parking slot, than looking at a map and choosing which spot to go to. Then the question of how an application should choose this ideal parking spot 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 (Psag) in complete and incomplete information contexts. For both models we present algorithms for individual players to choose parking spaces ideally. To evaluate the more realistic incomplete information Psag, simulations were performed to test the performance of various proposed algorithms.
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