Game theory-based and heuristic algorithms for parking-lot search

Increasing the population of cites has led to several problems in using the spatial sources of cities. One of these sources which imposes high expenses on city mates are car parks. To solve such problems many parking guidance systems have been developed, but unfortunately in most of them the efficiency has not been evaluated. In order to analyze efficiency of parking guidance systems, in this paper two models of parking selection systems are provided, using two concepts: game theory and priority heuristic. In the games theory model, drivers are considered as being rational entity that are seeking to maximize their payoffs. On the other hand, in the priority heuristic model, characteristics of drivers are taken into account for choosing a car park. We compared our model to the similar existing models based on three factors: the total number of drivers, the number of on-street car parks space, costs difference between private and on-street car parks and the influences of each factor on the efficiency of the parking guidance system. The results of comparison represent far higher efficiency compared to previous models.