OPTIMIZATION PROBLEMS IN SOFT AND ACTIVE MOBILITY
In recent years, the theme of sustainable and active mobility in urban and extra-urban areas has grown enormously. Groups and movements have made their main value the right to move more sustainably. Numerous public administrations have accompanied the debate, experimenting and subsequently implementing new winning strategies to change the current state, very often involving citizens sensitive to the issue. As a result, the theme of pedestrian and cycling mobility on the streets of our cities has become increasingly topical.
The great challenge of climate change and the COVID-19 pandemic have accelerated this process, setting in motion a whole social ecosystem that, starting from universities and research centers, up to companies and local and global government, have begun to produce analysis and projects to rethink urban and extra-urban mobility in crucial places, both at a macroscopic and microscopic level. These places are revalued or rethought by putting people at the center. The benefits of active mobility go far beyond the functional purpose of transport. Cycling and walking are free activities that are potentially accessible to any individual of any class, age, ethnic, or cultural group. Their greatest benefits are, however, only enjoyed by a limited group of people, namely those who practice this activity regularly.
There are also economic benefits: from a tourism point of view, cities with many pedestrian spaces and cycle infrastructures are much more attractive than those with large spaces dedicated to cars: there are many examples throughout Europe that testify to this. It also has a positive effect on businesses, as it has been shown that people tend on average to spend more if they are walking or cycling. Planning a bicycle and pedestrian network for any purpose, however, is quite complex, as these activities are not only functional for travel but also involve perceptions of the user's surroundings. To this purpose, it is important to support the decisional process with data and tools that can inform the choices made by public administrations and planners.
This project aims to develop modern and accessible tools that optimize the cycling network, considering not only the utilitarian criteria that guide the transport planning area but also the criteria that influence cycling users. The development will be made by mathematical models, implemented in Python - MIP or other libraries and include them in a Geographical Information System (GIS) tool, such as QGIS. It will therefore be important to be able to couple the knowledge of the urban planning group, which will provide support in identifying sustainable factors to generate inland, and the operational research group, which will convert these qualitative inputs into quantitative and measurable ones for solving graph optimization.
It will therefore first be necessary to separate the types of routes: cycling tourist routes and urban routes will be treated differently, then planning constraints will be defined. Different approaches will be used, such as decomposition of path models. On urban networks it will be interesting to focus on yet underdeveloped parts of the market such as delivery infrastructures that determine a specific type of users and travel purpose. From the perspective of cycling tourism, this approach should differentiate, concerning the territories that are crossed by the infrastructure considering less experienced users. It will also be strategic to consider the intermodality of travel, integrating cycling solutions with other means of transport such as boats, trains, or buses. We will apply these criteria to implement networks within inland territories such as valleys or the countryside to develop a different type of tourism. This will encourage virtuous practices in the progress of all productive sectors of society and consequently build a more sustainable economy with less environmental impact. Furthermore, to provide a tool that can be easily used by all stakeholders, a model will be developed that uses open data that is readily available from public administration databases. The model can also be adopted to use more structured and specific data from alternative sources.
In conclusion, this study will have very positive consequences for society. First of all, the developed tool will be very useful for public administrations and planners to manage their resources. They will also be used in multiple realistic scenarios that help in the choice of alternative urban configurations. More generally, improving infrastructures dedicated to active and sustainable mobility leads to a healthier society and fewer social costs, hence less public expenditure to be incurred.
Back to Current Students