ParkForU: A Dynamic Parking-Matching and Price-Regulator Crowdsourcing Algorithm for Mobile Applications

Abstract

Large metropolitan cities are getting busier and busier everyday. Overpopulation has caused parking related problems which in turn have severe external effects such as traffic congestion, air-pollution, social anxiety and inefficient resource distribution. To alleviate those effects infrastructure-based parking information systems have been proposed. However, they incur extreme costs due to extensive hardware installations. A promising alternative, that has shown great interest in recent years, is the use of crowdsourcing using mobile phones. In this work we propose a crowdsourcing system that aims to find the available and most suitable parking options for users in a smart city. We have developed ParkForU, a parking-matching and price-regulator algorithm. ParkForU, unlike existing approaches where a large unfiltered number of parking possibilities is given to the users, provides the best matched parking results while at the same time provides an effective way for dynamically re-adjusting the parking providers’ price. Through extensive simulations, we show how ParkForU performs and benefits both users and parking providers.