Autonomous vehicle technology is expected to be disruptive for automotive industry involving OEMs, suppliers, technology giants and academic institutions. It has the potential to completely revolutionize mobility and transportation concepts and to change consumers’ habits. This thesis provides a detailed analysis of the global automotive market considering the most probable industrial scenarios and actors involved. Pointing out the main transportation issues present nowadays, autonomous driving is considered the natural evolutionary perspective of automotive market. Moreover, an exhaustive overview of automotive active safety systems available is presented. In particular, higher SAE automation levels are described with a detailed overview of industrial and academical prototypes. A general scheme for autonomous vehicles is proposed and an extensive state of the art of the most recent and known motion planning techniques is presented. Starting from the definition of reasonable working assumptions (verified by means of a fully sensorized vehicle prototype), this PhD thesis aims at proposing a novel decisional control logic for trajectory planning and vehicle control that satisfies real-time feasibility, robustness and capability of handling multiple moving obstacles. Several control algorithms are proposed in order to highlight drawbacks and limits of classical implementations based on Model Predictive Control. Finally, a novel algorithm is proposed and thoroughly described. Several numerical simulations are shown in order to validate its capabilities and to evaluate its performances.

TBD

Innovative ADAS systems for autonomous vehicles

ARRIGONI, STEFANO

Abstract

Autonomous vehicle technology is expected to be disruptive for automotive industry involving OEMs, suppliers, technology giants and academic institutions. It has the potential to completely revolutionize mobility and transportation concepts and to change consumers’ habits. This thesis provides a detailed analysis of the global automotive market considering the most probable industrial scenarios and actors involved. Pointing out the main transportation issues present nowadays, autonomous driving is considered the natural evolutionary perspective of automotive market. Moreover, an exhaustive overview of automotive active safety systems available is presented. In particular, higher SAE automation levels are described with a detailed overview of industrial and academical prototypes. A general scheme for autonomous vehicles is proposed and an extensive state of the art of the most recent and known motion planning techniques is presented. Starting from the definition of reasonable working assumptions (verified by means of a fully sensorized vehicle prototype), this PhD thesis aims at proposing a novel decisional control logic for trajectory planning and vehicle control that satisfies real-time feasibility, robustness and capability of handling multiple moving obstacles. Several control algorithms are proposed in order to highlight drawbacks and limits of classical implementations based on Model Predictive Control. Finally, a novel algorithm is proposed and thoroughly described. Several numerical simulations are shown in order to validate its capabilities and to evaluate its performances.
COLOSIMO, BIANCA MARIA
GOBBI, MASSIMILIANO
CHELI, FEDERICO
12-lug-2017
TBD
Tesi di dottorato
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10589/134561