PORTALE DELLA DIDATTICA

Ricerca CERCA
  KEYWORD

Design of innovative transport solutions: from ITS to support transport systems to MaaS (Mobility as a Service)

keywords DATA MINING, NONLINEAR ANALYSIS, COMPLEX NETWORK, INTELLIGENT TRANSPORT SYSTEMS, MODELLING AND EXPERIMENTAL TESTS, STATISTICAL DATA ANALYSIS

Reference persons CRISTINA PRONELLO

Research Groups Transport Research for Innovation and Sustainability (TRIS)

Thesis type DATA ANALYSIS AND MODELING, DATA MINING, EXPERIMENTAL AND MODELING, PUBLIC TRANSPORT, SUSTAINABLE MOBILITY, TRANSPORT SYSTEM

Description The activity aims at defining innovative transport solutions using ITS (Intelligent Transport Systems) to face the problem of increasing budget cut in public transport.
To this end, for example, finding out new methods for collecting mobility data from different sources could help in understanding the mobility patterns and propose tailored solutions at different geographical scales. Another example regards the design of "mobility as a service" where packages of services can be offered focusing also on the integrated ticketing.
The student will have to carry out a diagnostic of transport data related to:
- supply (network for all transport modes) getting information from existing sources (geoportal, multimodal map, etc.):
- demand (mobility), finding out all the available data: from social media (e.g. Twitter), existing surveys, validations from public transport (given from the Transport Authority), etc.
According to the diagnostics made so far, they will individuate the gaps between what existing and a good knowledge of mobility patterns on existing networks and propose possible new methods of data collection of mobility: sensors on vehicles, improvement of existing apps.
In parallel (s)he could use in Torino or other cities an app to collect data of mobility patterns, together with the data already collected above (see demand), they will:
- design a data storage: a repository of data using data fusion techniques;
- visualise the mobility patterns and compare them with the transport supply;
- propose interventions focused to improve the people mobility using more sustainable transport modes.

Required skills Preferably, the needed skills are software programming, data mining, algorithm development and, additionally app development (not mandatory). A knowledge of transport systems is also fundamental to better exploit the potentiality of the ICT.


Deadline 05/11/2024      PROPONI LA TUA CANDIDATURA




© Politecnico di Torino
Corso Duca degli Abruzzi, 24 - 10129 Torino, ITALY
Contatti