Agent-based Modeling for Transportation Planning: A Method for Estimating Parking Search Time Based on Demand and Supply

We estimate parking cruising time curves - the probability Pi({\tau}) of longer than {\tau} parking search for destination Ni located within an area with heterogeneous demand and supply. To do that, we estimate cruising time curves for an area of homogeneous demand and supply and then average these curves based on (1) a model of parking search behavior established in a serious parking game; and (2) a "Maximally Dense" parking pattern obtained for the case where drivers possess full knowledge of the available parking spots and are able to park at the spot closest to their destination that is vacant at the moment they start searching for parking. We verify the proposed methods by comparing their outcomes to the cruising time curves obtained in an agent-based model of parking search in a city. As a practical example, we construct a map of cruising time for the Israeli city of Bat Yam. We demonstrate that despite low (0.65) overall demand-to-supply ratio in Bat Yam, high demand-to-supply ratio in the center of the city may result in longer than 10 minutes parking search there. We discuss the application of the proposed approach for urban planning.