mlsanityData to 14 Oct 2026

A Modular Architecture Design for Autonomous Driving Racing in Controlled Environments

arXiv 2512.03886 ↗First posted 3 Dec 2025cs.RO cs.SY eess.SYcited by 0

On the map: End-to-end autonomous driving → Imitation-learning end-to-end planners

Abstract (arXiv)

This paper presents a modular autonomous driving architecture for Formula Student Driverless competition vehicles operating in closed-circuit environments. The perception module employs YOLOv11 for real-time traffic cone detection, achieving 0.93 [email protected] on the FSOCO dataset, combined with neural stereo depth estimation from a ZED 2i camera for 3D cone localization with sub-0.5 m median error at distances up to 7 m. State estimation fuses RTK-GNSS positioning and IMU measurements through an Extended Kalman Filter (EKF) based on a kinematic bicycle model, achieving centimeter-level localization accuracy with a 12 cm improvement over raw GNSS. Path planning computes the racing line via cubic spline interpolation on ordered track boundaries and assigns speed profiles constrained by curvature and vehicle dynamics. A regulated pure pursuit controller tracks the planned trajectory with a dynamic lookahead parameterized by speed error. The complete pipeline is implemented as a modular ROS 2 architecture on an NVIDIA Jetson Orin NX platform, with each subsystem deployed as independent nodes communicating through a dual-computer configuration. Experimental validation combines real-world sensor evaluation with simulation-based end-to-end testing, where realistic sensor error distributions are injected to assess system-level performance under representative conditions.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Imitation-learning end-to-end planners, one of 9 directions in End-to-end autonomous driving. Builds on 6 of its 21 references that are in the map. First posted on arXiv 3 Dec 2025.

Builds on

6 of 21 references.

References · 6

  1. 2022YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectorscited by 982
  2. 2022Robot Operating System 2: Design, Architecture, and Uses In The Wildcited by 199
  3. 2014Multiple Object Tracking: A Literature Reviewcited by 166
  4. 2019AMZ Driverless: The Full Autonomous Racing Systemcited by 29
  5. 2020FSOCO: The Formula Student Objects in Context Datasetcited by 4
  6. 2023A Tricycle Model to Accurately Control an Autonomous Racecar with Locked Differentialcited by 4

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  1. 2022Autonomous Vehicles on the Edge: A Survey on Autonomous Vehicle Racing
  2. 2024Unifying F1TENTH Autonomous Racing: Survey, Methods and Benchmarks
  3. 2024Analysis of a Modular Autonomous Driving Architecture: The Top Submission to CARLA Leaderboard 2.0 Challenge
  4. 2026CooperDrive: Enhancing Driving Decisions Through Cooperative Perception
  5. 2026Dynamic Lookahead Distance via Reinforcement Learning-Based Pure Pursuit for Autonomous Racing
  6. 2025A Champion-level Vision-based Reinforcement Learning Agent for Competitive Racing in Gran Turismo 7
  7. 2024A Super-human Vision-based Reinforcement Learning Agent for Autonomous Racing in Gran Turismo
  8. 2024A Simulation Benchmark for Autonomous Racing with Large-Scale Human Data