Abstract
This paper presents a learning model that can be implemented on autonomous vehicles, using a dedicated software platform, based on physics, which can also be used to track the behavior of components and subsystems of the vehicle. In order to prepare the data for entering the software platform, data (position, orientation, acceleration, instantaneous speed) were recorded from a vehicle driven by several drivers on a previously established route. By processing the data, a driving style was established based on the average values recorded, for each subject who participated in the experimental tests. A virtual environment was created to correspond to the real route in which an autonomous vehicle was modeled and the data on the previously established driving style (instantaneous speeds vs. positions) were transferred. Following the running in the virtual environment and the registration of the data about the behavior of the vehicle on the established route, the data obtained by the classical method and the virtual simulation were compared. Thus, corrections can be made on the speed profile implemented for the autonomous vehicle, in order to comply with the limits imposed by the use of this vehicle with passengers: speed limits, longitudinal and lateral acceleration limits, braking limits.
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