|CARNIER STEFANO||Cycle: XXXV |
Section: Systems and Control
Tutor: FAGIANO LORENZO MARIO
Advisor: SAVARESI SERGIO MATTEO Major Research topic
:Variable estimation techniques for advanced vehicle dynamics control Abstract:
Advanced driver assistance systems (ADAS) and autonomous driving algorithms are among the most investigated and promising technologies in the field of automotive research. These systems aim at improving passengers’ safety and reducing traffic fatalities by assisting the driver or taking over the vehicle control in specific conditions. The development and implementation of such applications require an accurate and real time knowledge of the vehicle state variables. The main issue to cope with is the significant cost and the not consolidated reliability in extreme driving environments of sensors to be installed on vehicles for a direct measurement of these variables. The most logical approach to overcome this issue is to estimate unmeasured vehicle states using signals coming from cheap and reliable onboard sensors already embedded in most of the vehicles.
This study investigates and develops advanced vehicle state variables estimation techniques focusing on the potential benefits they would bring in ADAS and autonomous driving control systems advancement.