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) computing for parking slots (resources with different costs). Based on this competition, we present a game-theoretic framework to analyze parking situations. We introduce and analyzeParking 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.

The proliferation of mobile devices, location-based services and embedded wireless sensors has given rise to applications that seek to improve the efficiency of the transportation system. In particular, new applications are already available that help travelers to find parking in urban settings by conveying the parking slot availability near the desired destinations of travelers on their mobile devices.In this paper we present two notions of parking choice: the optimal and the equilibrium. The equilibrium describes the behavior of individual, selfish agents in a system. We will show how a pricing authority can use the parking availability information to set prices that entice drivers to choose parking in the optimal way, the way that minimizes total driving distance by the vehicles and is then better for the transportation system (by reducing congestion) and for the environment. We will present two pricing schemes that perform this task. Furthermore, through simulations we show the potential congestion improvements that can be obtained through the use of these schemes.

Abstract-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.

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