Predicting the use of car parks in the province of Barcelona

Treball fi de màster de: Master in Intelligent Interactive Systems Tutor: Vicenç Gómez Designing and generating wiser policies for urban systems and infrastructures is a challenge of paramount importance. Today, the cities that present the most successful transport strategies are prioritising the movement of people, giving residents and visitors a wider variety of attractive transport options while creating effective ways to switch from private to public transport means. Understanding the use and the impact of public infrastructures that facilitate mobility is crucial. We consider a dataset of one year of activity in the form of car park occupancy in the province of Barcelona. The data comprises ten different parking facilities located close to train stations. We propose and analyze different and intuitive prediction models based on statistical and mathematical approximations. First, we analyze the occupancy recordings in different parking locations and show that the activity is strongly coupled with the circadian rhythm, following a 24-hours cyclic pattern. Second, we implement a predictive model to provide the occupancy of a particular parking for an entire future day. We show that for both, statistical and mathematical approximations it performs quite accurately. Third, we implement a predictive model to guess the occupancy of the remaining hours of the day given the occupancy of the previous hours. Finally, a qualitative and quantitative analysis of the parking occupancy during the Covid-19 pandemic has been performed in order to understand how the global situation has influenced the parking usage. Our results show that, despite the apparent complexity associated to public mobility and use of car parks, very simple models motivated in intuitive principles are sufficient to understand and predict this dynamics. Overall, our results can facilitate the design of public policies to facilitate the mobility within Barcelona and its surroundings, by providing a better understanding of how the citizens switch between private cars and public trains.