REAL-TIME PREDICTION OF ROAD FLOOD OCCURRENCE PROBABILITY USING A SINGLE FLOOD SENSOR AND RAINFALL DATA

Abstract

 Road flooding prediction can help road users select rational routes and road administrators to implement efficient traffic regulations. This research proposes a method to calculate the probability of road flood occurrence in real time. The method accumulates flood data from a single flood sensor and rainfall data, then applies logistic regression analysis to these data. Since only one flood sensor is required per location, the method can be applied to locations where road flooding occurs suddenly or where multiple flood sensors cannot be installed. The usefulness of the proposed method was confirmed through experiments using road flood and rainfall at three locations over a period of 2 years and 5 months.