Simulating Scenarios for the Evaluation of Data Management Approaches for Searching Parking Spaces

Finding a parking space is a costly and tedious task for drivers, which leads to high fuel consumption and air pollution. Moreover, in a context of a health crisis such as the pandemic of the COVID-19, the use of private vehicles may be favored over public transport, which could increase the difficulty of finding an available parking spot. Therefore, the use of data management strategies that facilitate the search for available parking is important to alleviate this problem. Due to the complexity of evaluating these data management techniques in the real world, evaluations are usually based on simulations.In this demo paper, we describe MAVSIM+, a novel simulation tool that we have developed to evaluate data management techniques for parking search. It integrates a tool focused on the definition and simulation of parking lots (SimulParking) and incorporates functionalities that support the definition of parking areas and individual parking spaces in the streets of a city.