Thesis Code: 19020
Thesis Type: M.Sc. thesis in Mathematical Engineering
Research Area: Urban Mobility & Logistic Systems
- Familiarity with differential models and partial differential equations
- Experience with main programming languages (Python, C/C++)
- Interest in Transport Planning
- Ability to critically interpret analytical results
The penetration of driver-assists/autonomous vehicles and their consequent impact on traffic is an emerging, thus still under-explored, research topic in the realm of Artificial Intelligence.
The thesis will be carried out in the UML area (Urban Mobility & Logistic Sytems) of the LINKS Foundation. There will be a strict interaction with the research group of Prof. Andrea Tosin at the Department of Mathematical Sciences “G. L. Lagrange” of Politecnico di Torino.
The thesis project is grounded on three main methodological aspects: modelling, model analysis and numerical simulation, which may be more or less developed according to the student’s taste. After deepening the state of the art on methods for traffic modelling, the student will be asked to develop a mesoscopic model for simulating the flow of vehicles and to analyse alternative penetration scenarios for driver-assist/autonomous vehicles. In particular, the model will be possibly tested on a case study of interest (such as e.g., the city of Turin) using the software MATSim and discussing critically the results. The latter may be used to outline recommendations and suggestions for the public decision maker and as an input to urban planning processes.
- Pareschi, G. Toscani. Interacting Multiagent Systems: Kinetic Equations and Monte Carlo Methods, Oxford University Press, Oxford, UK, 2013
- Tosin, M. Zanella. Control strategies for road risk mitigation in kinetic traffic modelling, IFAC-PapersOnLine, 51(9):67-72, 2018
- Tosin, M. Zanella. Kinetic-controlled hydrodynamics for traffic models with driver-assist vehicles, Multiscale Model. Simul., 17(2):716-749, 2019
- Tosin, M. Zanella. Uncertainty damping in kinetic traffic models by driver-assist controls, preprint, 2019 (available at: http://doi.org/10.13140/RG.2.2.35871.41124)
Contacts: send a resume with attached the list of exams to firstname.lastname@example.org specifying the thesis code and title.