Design and Implementation of a Modular ROS 2 Framework Integrating Advanced Driver Assistance Capabilities for High-Fidelity Mahindra Thar Vehicle Simulation in Gazebo Classic
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- Publication code
- 20264532
- Paper/Info type
- International Journal of Automotive Engineering
Vol.17 No.3
- Pages
- 164-170(Total 7 p)
- Date of publication
- Jul 2026
- Publisher
- JSAE
- Language
- English
Detailed Information
| Category(E) | Research paper |
|---|---|
| Author(E) | 1) Rohan D. Kumar, 2) Nithin Nivhar, 3) Mohammed Fahim, 4) Romesh V. Rajashree, 5) Saravanan Ravi |
| Affiliation(E) | 1) Rajalakshmi Engineering College, 2) Rajalakshmi Engineering College, 3) Rajalakshmi Engineering College, 4) Rajalakshmi Engineering College, 5) Rajalakshmi Engineering College |
| Abstract(E) | The integration of Advanced Driver Assistance Systems (ADAS) within modular robotic frameworks presents significant opportunities for scalable autonomous mobility research. This paper introduces a comprehensive ROS 2 Humble-based simulation framework for implementing and evaluating core ADAS functionalities-Lane Keeping Assist (LKA), Adaptive Cruise Control (ACC), Forward Collision Warning (FCW), and Automatic Emergency Braking (AEB)-on a differential-drive robotic platform modeled in Gazebo. Our architecture uniquely combines multi-sensor perception, a dual-SLAM strategy (2D mapping via SLAM Toolbox and dense 3D reconstruction/localization via RTAB-Map), and real-time navigation control using Nav2 within a unified, extensible ROS 2 node graph. The system integrates (i) a URDF/Xacro vehicle equipped with LiDAR, RGB and depth cameras for multimodal perception; (ii) modular AI perception pipelines for lane detection, object recognition and obstacle classification; (iii) control-theoretic ADAS implementations (PID and MPC) for lateral stabilization and adaptive longitudinal regulation; (iv) a Time-to-Collision (TTC) safety module enabling predictive FCW/AEB; and (v) a hierarchical arbitration mechanism that dynamically interfaces with and-under safety-critical conditions-overrides the navigation stack. The architecture is designed with clearly defined topic interfaces, deterministic message flows, and fail-safe prioritization logic to meet real-time constraints; simulation experiments in the Gazebo environment demonstrate robust behavior across dynamic obstacle scenarios, sensor noise profiles and timing stresses. Finally, a computational feasibility analysis on the Raspberry Pi 4 highlights trade-offs between modular and monolithic architectural strategies in latency, scalability and maintainability. |
