Fast and Realistic Automated Scenario Simulations and Reporting for an Autonomous Racing Stack

Fuente: arXiv
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Main Authors: Lambertini, Giovanni, Pini, Matteo, Mascaro, Eugenio, Moretti, Francesco, Raji, Ayoub, Bertogna, Marko
Format: Preprint
Published: 2025
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author Lambertini, Giovanni
Pini, Matteo
Mascaro, Eugenio
Moretti, Francesco
Raji, Ayoub
Bertogna, Marko
author_facet Lambertini, Giovanni
Pini, Matteo
Mascaro, Eugenio
Moretti, Francesco
Raji, Ayoub
Bertogna, Marko
contents In this paper, we describe the automated simulation and reporting pipeline implemented for our autonomous racing stack, ur.autopilot. The backbone of the simulation is based on a high-fidelity model of the vehicle interfaced as a Functional Mockup Unit (FMU). The pipeline can execute the software stack and the simulation up to three times faster than real-time, locally or on GitHub for Continuous Integration/- Continuous Delivery (CI/CD). As the most important input of the pipeline, there is a set of running scenarios. Each scenario allows the initialization of the ego vehicle in different initial conditions (position and speed), as well as the initialization of any other configuration of the stack. This functionality is essential to validate efficiently critical modules, like the one responsible for high-speed overtaking maneuvers or localization, which are among the most challenging aspects of autonomous racing. Moreover, we describe how we implemented a fault injection module, capable of introducing sensor delays and perturbations as well as modifying outputs of any node of the stack. Finally, we describe the design of our automated reporting process, aimed at maximizing the effectiveness of the simulation analysis.
format Preprint
id arxiv_https___arxiv_org_abs_2512_24402
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Fast and Realistic Automated Scenario Simulations and Reporting for an Autonomous Racing Stack
Lambertini, Giovanni
Pini, Matteo
Mascaro, Eugenio
Moretti, Francesco
Raji, Ayoub
Bertogna, Marko
Robotics
Artificial Intelligence
Software Engineering
Systems and Control
In this paper, we describe the automated simulation and reporting pipeline implemented for our autonomous racing stack, ur.autopilot. The backbone of the simulation is based on a high-fidelity model of the vehicle interfaced as a Functional Mockup Unit (FMU). The pipeline can execute the software stack and the simulation up to three times faster than real-time, locally or on GitHub for Continuous Integration/- Continuous Delivery (CI/CD). As the most important input of the pipeline, there is a set of running scenarios. Each scenario allows the initialization of the ego vehicle in different initial conditions (position and speed), as well as the initialization of any other configuration of the stack. This functionality is essential to validate efficiently critical modules, like the one responsible for high-speed overtaking maneuvers or localization, which are among the most challenging aspects of autonomous racing. Moreover, we describe how we implemented a fault injection module, capable of introducing sensor delays and perturbations as well as modifying outputs of any node of the stack. Finally, we describe the design of our automated reporting process, aimed at maximizing the effectiveness of the simulation analysis.
title Fast and Realistic Automated Scenario Simulations and Reporting for an Autonomous Racing Stack
topic Robotics
Artificial Intelligence
Software Engineering
Systems and Control
url https://arxiv.org/abs/2512.24402