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Organisational Chart


Modena Municipality UNIMORE Maserati SpA

Ing. Luca Chiantore 
Ing. Guido Calvarese 
Ing. Nabil El Ahmadič 
Dott.ssa Ludovica Carla Ferrari 

Prof. Ing. Michele Colajanni 
Prof. Ing. Mauro Dell'Amico
Prof. Ing. Francesco Leali 
Prof. Gianluca Marchi 

Ing. Serino  Angellotti 
Ing. Roberto Corradi 
Ing. Edoardo Rossi
Engineering Law Economics Engineering
Real time systems for autonomous driving Law and ethics for autonomous driving Economics for autonomous driving Artificial Intelligence and Computer Vision for smart cities and automotive

Supervisor: Prof. M. Bertogna

Supervisor: Prof. S. Scagliarini

Supervisor: Prof. G. Marchi
Supervisor: Prof. R. Cucchiara

A self-driving vehicle needs to process a wide amount of data from multiple sensors (e.g., cameras, radars, lidars, GNSS, etc.) to derive a common understanding of the surrounding environment (sensor fusion), before taking a driving decision. If such a decision is not taken in time, the car “does not know what to do”. Breaking, stopping, pulling over the car, or simply not doing anything, may all be wrong solutions, considerably endangering the safety of passengers and pedestrians. The expertise of this vertical group encompasses the prompt and timely elaboration of heterogeneous sensors on state-of-the-art embedded devices, the real-time planning of driving maneuvers , and the predictable enforcement of actuation signals to ensure a safe condition. 

Examines international, comparative and national issues in relation to the circulation of autonomous cars, with a particular focus on the first legislations concerning tests on public roads and their enforcement in the italian legal system. Moreover the matters relating to liability and insurance for self-driving cars are analysed as well as some aspects regarding legal informatics (for example, smart roads) and personal data treatment (privacy) involving
driverless cars. Finally also ethical issues , concerning the choices of autonomous cars (moral algorithms) and their implementation, are investigated.

Contributes to the research project in the field of:  Cost-Benefit Analysis, referred to tangible values, intangibles, and externalities  (safety, comfort, time savings, environment) for different types of stakeholders, both at the individual and at the collective level (e.g. citizens); Socio-Economic Analysis , through multi-disciplinary surveys, simulations, and interviews; Technology Acceptance  and Attitude analysis at the individual (e.g. drivers) and societal level (e.g. public opinion); Territorial Marketing Analysis , to define the possible effect of the implementation of MASA on city’s ability to attract investments, organise events, and gain additional revenues. 

The team will discuss and contribute in applying new computer paradigms of  machine learning, deep learning and computer vision  to city-related problems, mainly concerning video-surveillance, traffic analysis, automatic recognition of scenes from static, and moving cameras, autonomous and semi-autonomous guidance. The working group will support public body in defining procedures and solutions for assessing the contextual situation in urban areas where  vehicles and persons interact . The working group will discuss problems related with automatic data extraction and recognition, comparison of commercial available solutions and prototype, assessing new standards and best-practices also in collaboration with groups working on privacy and security issues, and to support industries to tests research and commercial solutions.

Engineering Engineering
Automotive Cybersecurity Human Machine Interaction

Supervisor: Prof. M. Marchetti

Topics Representatives: Prof.ssa C. Iani, Prof. G. Mincolelli, Prof.ssa M. Peruzzini
  Topic: Psychology Topic: UX Topic: User Experience Tools
The Automotive Cybersecurity team conducts bleeding-edge research activities on cyberattacks targeting modern and future vehicles. Its main goal is to design, develop and test novel solutions able to detect cyberattacks and react by preserving the safety of drivers, passengers and pedestrians.
Research activities include security of electronic control units, in-vehicle networks and communication buses , as well as V2X (vehicle to cloud, vehicle to infrastructure, vehicle to vehicle ...) communication technologies.
The team is also responsible for the Automotive Cybersecurity university course, part of the Advanced Automotive Electronic Engineering Master's Degree.

The main topics addressed by this research group are related to the consideration, in the design phase, of  human factors , that is the set of  drivers’ capabilities, limitations and needs , with the main objective of improving both safety and the driving experience.
Relevant areas of interest are: the monitoring of the psychophysiological parameters, of cognitive load, of the driver’s level of attention and awareness in the different driving conditions, with particular reference to semi-autonomous driving, in which the driver's active intervention is still required, and totally autonomous driving.

The team will focus on the sensemaking and the design of the user experience of an autonomous vehicle in the context of a smart city. Based on a human-centred approach, behaviours and needs of direct users and stakeholders will be analysed. Team will discuss the characteristics of the relational system that could be produced by the interactions between autonomous driving vehicle and men , as well as between city , vehicle and passengers . We will discuss the ways in which these relationships, could be designed and translated into perceptible, interpretable and meaningful events and information. We will try to define some concept designs of the autonomous drive vehicle user experience and of the related interface and interaction systems between man, car and the city and we will discuss the new sense that could take on topics such as accessibility, inclusion, sustainability, fun, safety, responsibility, identity etc.

The team is focused on the human-centred design thought the adoption of advanced tools to simulate and predict the user experience . Drivers as well as passengers have a direct interaction with the car systems, both physical and cognitive. The combination of behavioral and reflective responses within the car generates the lived experience , that is directly connected with the perceived quality. The team contributes to the project by offering virtual reality and simulation tools and proper design protocols to predict the user experience on digital prototypes to support the design of the vehicle and the on-board interactive technologies. On the basis of usability and comfort analyses, as well as physical and cognitive ergonomic assessment, different design solution can be validated from the early design stages and validated with users, according to a participatory design approach . This approach is adopted to the car as well as the V2X infrastructure and related services to be created in the smart area.