Learning objectives

The Inter-University Master's Degree course in Electronic Engineering for Intelligent Vehicles aims to train an electronic engineer with specific skills relating to the design, implementation, management and use of the information acquisition, transfer, data management, and intelligent processing subsystems that characterize modern vehicles.
To achieve this educational goal, the Master's Degree in Electronic Engineering for Intelligent Vehicles provides, during the first year,  the essential knowledge in the field of design and programming of embedded electronic systems, i.e. designed for the real time processing of the signals coming from the sensors, perceptions devices, and driver inputs; this is achieved through courses offered in the Electronics, Electromagnetic Fields, Electric and Electronic Measurements as well as Power electronic converters, electrical machines and drives. Simultaneously, typical contents of the related Automatics sector are provided, to make possible to put into practice actions planned by the processing system. Courses in the Telecommunication sector students can learn about the characterization and design of most commonly used sensors for automotive applications, i.e. Radar, Lidar and cameras. Future graduates can acquire skills also in the field of Machine vision and Deep Learning thanks to different Information Technologies courses. Topics like electromagnetic interference,  in-vehicle and vehicle-to-vehicle data transfer techniques, test and reliability issues both from a general point of view and from a specific point of view are also touched in different courses.
The second year complements and specializes the first, and more differences are introduced between the two curricula.
Both curricula offer courses about the  design of electronic subsystems actually built on existing vehicles.
The Electronic and Communication System curriculum mainly focuses on embedded systems, programming of embedded systems, automotive connectivity and cyber security. Nevertheless this curriculum also deepen the knowledge about artificial intelligence and platforms and algorithms for autonomous driving.
Conversely, the Autonomous Driving Engineering curriculum is much more tailored on the intelligent system transportation field. Therefore, students can learn about 3D perception, sensor fusion, Autonomous Driving and Advanced Driver Assistance Systems (ADAS) technologies, virtual systems and Human-Machine Interfaces for intelligent vehicles.  
During the second year, the study plan also allows to interact with MUNER companies that work in the automotive fields thanks to optional internships that can be carried out in real working environments.  


 

Contacts

Toll-free number

800 904 084

Student registry office

E. segreteria.ingarc@unipr.it

Quality assurance office

Education manager:
Dott.ssa Jasmine Salame Younis
T. +39 0521 906045
Office E. dia.didattica@unipr.it
Manager E. jasmine.salameyounis@unipr.it

 

President of the degree course

Prof. Massimo Bertozzi
E. massimo.bertozzi@unipr.it

Faculty advisor

Prof. Letizia Marchegiani
E. letizia.marchegiani@unipr.it

Career guidance delegate

Prof. Letizia Marchegiani
E. letizia.marchegiani@unipr.it

Tutor professor

Prof. Nicola Mimmo (UNIBO)
E. nicola.mimmo2@unibo.it
Prof. Riccardo Rovatti (UNIBO)
E. riccardo.rovatti@unibo.it

Erasmus delegates

to be determined

Quality assurance manager

Prof. Nicola Mimmo (UNIBO)
E. nicola.mimmo2@unibo.it
 

Internships

Prof. Alessandro Chini (UNIMORE)
E. alessandro.chini@unimore.it
Prof. Gaetano Bellanca (UNIFE)
E. gaetano.bellanca@unife.it
Prof.ssa Annamaria Cucinotta (UNIPR)
E. annamaria.cucinotta@unipr.it
Prof. Nicola Mimmo (UNIBO)
E. nicola.mimmo2@unibo.it
Prof. Paolo Pavan (UNIMORE)
E. paolo.pavan@unimore.it
Prof. Riccardo Rovatti (UNIBO)
E. riccardo.rovatti@unibo.it

Tutor students

to be determined