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We propose an approximation method for estimating the probability [Formula: see text] of searching for on-street parking longer than time [Formula: see text] from the start of a parking search near a given destination [Formula: see text] based on high-resolution maps of parking demand and supply in a city. We verify the method by comparing its outcomes to the estimates obtained with an agent-based simulation model of on-street parking search. As a practical example, we construct maps of cruising time for the Israeli city of Bat Yam and demonstrate that, despite the low overall demand-to-supply ratio of 0.65, excessive demand in the city center results in a significant share of parking searches that last longer than 5 or even 10 minutes. We discuss the application of the proposed approach for urban planning.

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