A new concept for a Sport-Coupè car developed with the Industrial Design Structure method (IDeS)

The aim of this study, conducted in collaboration with Lawrence Technological University in Detroit, is to create, through the method of the Industrial Design Structure (IDeS), a new concept for a sport-coupe car, based on a restyling of a retro model (Ford Mustang 1967). To date, vintage models of cars always arouse great interest both for the history behind them and for the classic and elegant style. Designing a model of a vehicle that can combine the charm of retro style with the innovation and comfort of modern cars would allow to meet the needs and desires of a large segment of the market that today is forced to choose between past and future. Thanks to a well-conceived concept car an automaker company is able to express its future policy, to make a statement of intent as, such a prototype, ticks all the boxes, from glamour and visual wow-factor to technical intrigue and design fascination. IDeS is an approach that makes use of many engineering tools to realize a study developed on several steps that must be meticulously organized and timed. With a deep analysis of the trends dominating the automotive industry it is possible to identify a series of product requirements using quality function deployment (QFD). The considerations from this first evaluation led to the definition of the technical specifications via benchmarking (BM) and top-flop analysis (TFA). Then, the structured methodology of stylistic design engineering (SDE) is applied through six phases: (1) stylistic trends analysis; (2) sketches; (3) 2D CAD drawings; (4) 3D CAD models; (5) virtual prototyping; (6) solid stylistic model. Finally, Developing the IDeS method up to the final stages of Prototypes and Testing you get a product as close as possible to the ideal vehicle conceptualized in the initial analysis.

Virtual sensing technology applied to a swarm of autonomous robots.

This thesis proposes a novel technology in the field of swarm robotics that allows a swarm of robots to sense a virtual environment through virtual sensors. Virtual sensing is a desirable and helpful technology in swarm robotics research activity, because it allows the researchers to efficiently and quickly perform experiments otherwise more expensive and time consuming, or even impossible. In particular, we envision two useful applications for virtual sensing technology. On the one hand, it is possible to prototype and foresee the effects of a new sensor on a robot swarm, before producing it. On the other hand, thanks to this technology it is possible to study the behaviour of robots operating in environments that are not easily reproducible inside a lab for safety reasons or just because physically infeasible. The use of virtual sensing technology for sensor prototyping aims to foresee the behaviour of the swarm enhanced with new or more powerful sensors, without producing the hardware. Sensor prototyping can be used to tune a new sensor or perform performance comparison tests between alternative types of sensors. This kind of prototyping experiments can be performed through the presented tool, that allows to rapidly develop and test software virtual sensors of different typologies and quality, emulating the behaviour of several hardware real sensors. By investigating on which sensors is better to invest, a researcher can minimize the sensors’ production cost while achieving a given swarm performance. Through augmented reality, it is possible to test the performance of the swarm in a desired virtual environment that cannot be set into the lab for physical, logistic or economical reasons. The virtual environment is sensed by the robots through properly designed virtual sensors. Virtual sensing technology allows a researcher to quickly carry out real robots experiment in challenging scenarios without all the required hardware and environment.

Rapid Control Prototyping of an L2+ Highway Assist System

Advanced Driver Assistance Systems (ADAS) are proving to have huge potential in road safety, comfort, and efficiency. In recent years, car manufacturers have equipped their high-end vehicles with Level 2 ADAS, which are, according to SAE International, systems that combine both longitudinal and lateral active motion control. These automated driving features, while only available in highway scenarios, appear to be very promising towards the introduction of hands-free driving. However, as they rely only on an on-board sensor suite, their continuative operation may be affected by the current environmental conditions: this prevents certain functionalities such as the automated lane change, other than requiring the driver to keep constantly the hands on the steering wheel. The enabling factor for hands-free highway driving proposed by Mobileye is the integration of high-definition maps, thus leading to the so-called Level 2+. This thesis was carried out during an internship in Maserati's Virtual Engineering team. The activity consisted of the design of an L2+ Highway Assist System following the Rapid Control Prototyping approach, starting from the definition of the requirements up to the real-time implementation and testing on a simulator of the brand new compact SUV Maserati Grecale. The objective was to enhance the current Level 2 highway driving assistance system with hands-free driving capability; for this purpose an Autonomous Lane Change functionality has been designed, proposing a Model Predictive Control-based decision-maker, in charge of assessing both the feasibility and convenience of performing a lane-change maneuver. The result is a Highway Assist System capable of driving the vehicle in a traffic scenario safely and efficiently, never requiring driver intervention.