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Modeling and Simulating ACC and LKA with Advanced Control Strategies

Giulia Rotili

Modeling and Simulating ACC and LKA with Advanced Control Strategies.

Rel. Stefano Alberto Malan, Davide Faverato, Angelo Borneo. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2024

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Abstract:

The focus of this thesis project is to model and test autonomous driving systems, with particular emphasis on Adaptive Cruise Control (ACC) and Lane Keeping Assistant (LKA), using the MATLAB and Simulink environment. The vehicle of interest, referred to as the ego, and the vehicle in front of it, referred to as the lead, are both subjected to a dynamic model based on the single track model, which allows their dynamic behaviour during driving to be represented in an accurate and simplified manner. The simulations involve various working situations, in which the ego vehicle, based on suitable variables, activates the previously designed ACC or LKA control via an integrated control logic. This approach allows the effectiveness of such systems to be assessed in realistic scenarios and their performance improved in order to enhance the safety and efficiency of autonomous driving. Furthermore, the flexibility of the model also allows it to be adapted to the characteristics of the vehicle of interest, such as the Rosmaster X3, which has significant mechanical and dynamic behaviour compared to a conventional vehicle.

Relatori: Stefano Alberto Malan, Davide Faverato, Angelo Borneo
Anno accademico: 2023/24
Tipo di pubblicazione: Elettronica
Numero di pagine: 68
Soggetti:
Corso di laurea: Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica)
Classe di laurea: Nuovo ordinamento > Laurea magistrale > LM-25 - INGEGNERIA DELL'AUTOMAZIONE
Aziende collaboratrici: MCA Engineering S.r.l.
URI: http://webthesis.biblio.polito.it/id/eprint/31802
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