This study aims to adapt the ideal model of autonomous driver, already implemented in previous research, into a real model. Following the adaptation, the model's efficiency will be assessed against the trajectory defined as the baseline. Specifically, Gaussian disturbances and second-order filters will be added to the ideal model and parameter choice will be performed to obtain efficient results. Initial findings will be obtained by using a constant velocity which will be substituted, in a second approach, with a velocity profile to understand the real behaviour of the vehicle. Consequently, adjustments to the dynamics model will be necessary to accurately account for velocity variations during tracking. To do so, the model will be tested changing the parameters until the optimal viable combination will be found.

This study aims to adapt the ideal model of autonomous driver, already implemented in previous research, into a real model. Following the adaptation, the model's efficiency will be assessed against the trajectory defined as the baseline. Specifically, Gaussian disturbances and second-order filters will be added to the ideal model and parameter choice will be performed to obtain efficient results. Initial findings will be obtained by using a constant velocity which will be substituted, in a second approach, with a velocity profile to understand the real behaviour of the vehicle. Consequently, adjustments to the dynamics model will be necessary to accurately account for velocity variations during tracking. To do so, the model will be tested changing the parameters until the optimal viable combination will be found.

Implementation of the dynamical model of an autonomous driver by using a Stanley controller: a simulation study for a Formula Student race vehicle

FUSARO, VALENTINA
2023/2024

Abstract

This study aims to adapt the ideal model of autonomous driver, already implemented in previous research, into a real model. Following the adaptation, the model's efficiency will be assessed against the trajectory defined as the baseline. Specifically, Gaussian disturbances and second-order filters will be added to the ideal model and parameter choice will be performed to obtain efficient results. Initial findings will be obtained by using a constant velocity which will be substituted, in a second approach, with a velocity profile to understand the real behaviour of the vehicle. Consequently, adjustments to the dynamics model will be necessary to accurately account for velocity variations during tracking. To do so, the model will be tested changing the parameters until the optimal viable combination will be found.
2023
Implementation of the dynamical model of an autonomous driver by using a Stanley controller: a simulation study for a Formula Student race vehicle
This study aims to adapt the ideal model of autonomous driver, already implemented in previous research, into a real model. Following the adaptation, the model's efficiency will be assessed against the trajectory defined as the baseline. Specifically, Gaussian disturbances and second-order filters will be added to the ideal model and parameter choice will be performed to obtain efficient results. Initial findings will be obtained by using a constant velocity which will be substituted, in a second approach, with a velocity profile to understand the real behaviour of the vehicle. Consequently, adjustments to the dynamics model will be necessary to accurately account for velocity variations during tracking. To do so, the model will be tested changing the parameters until the optimal viable combination will be found.
Non linear MPC
Autonomous driver
Simulation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12608/66470