For the uncompromising driver, urban traffic equals the constant stop-and-go inconvenience of traffic jams. It is precisely the acceleration and braking process, however, that concentrates around 40% of carbon dioxide emissions generated by transport, which are the main causes of the greenhouse effect. The impact of trivial maneuvers, such as the search for a parking space, becomes a considerable factor in the definition of public policies on sustainability and mobility.

 

Under the advisory of Professor Paulina Achurra, Mechatronics Engineering students Bruno Vieira Sanches, Davi Dom Bosco Silva and Lucas Nicascio dos Santos, along with Mechanical Engineering student Marcelo Lisboa de Castro Reis, worked on a model that would facilitate the search for city parking spaces. The proposal was shared in the Engineering Capstone Project entitled Public Parking Predictive Model and the Impact on CO2 Emissions, developed in partnership with ‘IMREDD’ (acronym in French for the Mediterranean Institute of Risk, Environment and Sustainable Development), from Côte d’Azur University, in France.

 

Distinguished with the Falconi-Insper certification, issued by the consulting firm ‘Falconi Consultores de Resultado’, the project was showcased to the City Hall of Mandelieu-La Napoule, a Southern French city that provided the real information. “The daily conversations with the representative from an international institution were quite enriching, especially to understand the work dynamics overseas”, Davi Silva says. “Presenting it in English to the City Hall of the French city was very interesting, so that we could see the relevance of what the group was doing. The possibility of implementing the project in public and private spheres brings us great satisfaction.”

 

According to Bruno Sanches, the project aims to optimize the search for public parking spaces, while based on a predictive model that takes into account the flow of vehicles given by the attractiveness of the zones assessed. “By using the model, we can point out beforehand the best place for drivers to park, meaning where there is greater probability of finding a parking space within a viable distance from their destination”, Sanches adds. “This reduces the time spent searching and, consequently, the carbon dioxide emissions from the car.”

 

“One of the main difficulties was to create the solution for this far-away reality from where the group was”, Marcelo Reis explains. Even though the project was developed with a view to its replicability in different cities, the pilot was implemented for Mandelieu-La Napoule, with real data provided by the city government. “So, the challenge was to apply and convert the hypotheses raised in a test neighborhood of São Paulo to the reality of Mandelieu-La Napoule”, Reis clarifies.

 

His colleague, Davi Silva, continues: “Also, the exploratory analysis and processing of the real data, as well as the development and application of mathematical and statistical models to anticipate how parking spaces work throughout the day, were quite challenging.”

 

According to Professor Paulina Achurra, this project illustrates how the vast amount of data currently generated in cities can be used to improve the quality of life of its citizens, assist in public policy decisions and deal with the great challenge of our time: reducing greenhouse gas emissions. “We hope that São Paulo will move towards the same direction to make the data generated in the city increasingly available”, Achurra points out.

 

Possibilities to explore

 

The deliverables of the Engineering Capstone Project are not only interesting for municipal administrations, but also for drivers. “The developed model explains quite well the reality in the qualitative realm, while varying its outputs throughout the hours of the day”, Marcelo Reis reveals. “Quantitatively speaking, there is room for future iterations by further exploring the specific character of the assessed location, so that the calculated attractiveness expresses the reality of the flow of vehicles with increasing assertiveness.”

 

Lucas Santos explains that with the prototype developed, the predictive model would not only act as a support for the driver, by pointing out the optimal place to park, but also as a tool for public policy intervention in the sphere of urban logistics. “The model enables the city to simulate the manipulation of urban parameters, such as the speed limit of roads and the commercial network layout, while envisioning the direct impact on the flow of vehicles and on greenhouse gas emissions”, Santos adds.

 

The four students can build on the solution over the course of their professional careers. “The scope of the project involves topics that strongly resonate with the group, such as mobility, sustainability and data science”, Bruno Sanches says. “Over the semester, we realized that the project has great potential to generate positive impacts on urban logistics and on carbon dioxide reduction, both with a focus on users and for cities and decision-making bodies.”

 

They remark that they are open to discussing proposals for implementing the model, in a spirit that is in line with Insper’s principles. “Insper’s teaching methodology, centered on learning by doing from the first semester of college, makes students solve real problems, while creating viable solutions for a given target audience”, Lucas Santos says.

 

The future engineers credit the successful development of the Engineering Capstone Project to that mindset, added to the technical knowledge gained. “We are grateful to the highly qualified faculty of the institution over the past few years, who assisted us whenever needed, especially Professor Paulina Achurra, who has advised us throughout the project,” Santos concludes.