Journal of Advances in Developmental Research

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Simulation Strategies for Autonomous Vehicle Validation: A Modular and Scalable Approach

Author(s) Nishant Shrivastava
Country United States
Abstract As autonomous vehicle (AV) technology advances, validating complex behavior across diverse driving scenarios becomes increasingly critical. This paper presents a set of simulation strategies designed to rigorously validate AV systems using a modular, scalable, and automated framework. Drawing from real-world applications and tooling—including Simulation Data Inspector (SDI) and Simulink Test—we outline an approach to scenario generation, data management, performance metric definition, and automated analysis. Emphasis is placed on reproducibility, interoperability, and performance traceability, especially in hardware-in-the-loop (HIL) and model-in-the-loop (MIL) environments. These strategies help accelerate development cycles while ensuring safety, robustness, and regulatory compliance.
Keywords Autonomous Vehicle Validation, Simulation Strategies, Model-in-the-Loop (MIL), Hardware-in-the-Loop (HIL), Scenario-Based Testing, Performance Metrics, Modular Simulation Architecture, Automated Testing, Real-World Fidelity, Safety Validation, Reinforcement Learning, Rare-Event Simulation, Simulation Data Management, AI-Driven Test Generation, Digital Twins
Field Engineering
Published In Volume 16, Issue 2, July-December 2025
Published On 2025-07-26
Cite This Simulation Strategies for Autonomous Vehicle Validation: A Modular and Scalable Approach - Nishant Shrivastava - IJAIDR Volume 16, Issue 2, July-December 2025. DOI 10.71097/IJAIDR.v16.i2.1491
DOI https://doi.org/10.71097/IJAIDR.v16.i2.1491
Short DOI https://doi.org/g9vdfn
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