## 2 Related Work  
XILS-based techniques have been actively researched and utilized as a systematic approach to verifying ADS safety. As shown in Figure 1, a key component in the development and validation of ADSs, XILS is categorized into MILS, SILS, HILS, and VILS based on the development stage and constitutes the final step before real-world validation [22]. Figure 1 illustrates the hierarchical integration of XILS technologies within the V-Model development framework. The figure demonstrates systematic progression from early-stage MILS for algorithm verification, through SILS for software validation, HILS for real-time hardware integration testing, to VILS for comprehensive vehicle-level validation, culminating in real vehicle testing. With the continued progress in simulation research, though, the characteristics and limitations of each XILS phase are becoming clearer. Specifically, MILS enables rapid verification of control algorithms and vehicle models within a purely software environment, thus being an effective tool for securing algorithm stability during the initial development phase [23]. However, it is limited by its inability to reflect real hardware characteristics. SILS leverages virtual electronic control unit (ECU) models to systematically validate control software functionality and evaluate software code performance before hardware integration [24]. However, aspects such as actual hardware data structures and computational delays are difficult to emulate perfectly. HILS incorporates real ECUs and hardware for real-time validation and a comprehensive assessment of hardware-software interactions, but it fails to reproduce the complexity of real vehicle dynamics [25; 26; 27]. To overcome these stage-specific limitations, recent research has focused on VILS, an advanced approach that integrates a real vehicle with a virtual environment, maintaining the vehicle's dynamic characteristics while enabling safe testing across various virtual scenarios [28]. To address the limitations of existing XILS approaches while maintaining vehicle dynamic fidelity, [PERSON] et al. [29] proposed a proving ground (PG)-based VILS system that recreates a real proving ground as a high-definition (HD) map-based virtual road. The system comprises four key components: virtual road generation, real-to-virtual synchronization, virtual traffic behavior generation, and perception sensor modeling. This design preserves the vehicle's true dynamic characteristics while enabling safe, repeatable testing of various scenarios in a virtual environment. Unlike dynamometer-based VILS, it can be implemented with only a proving ground and does not require large-scale dynamometers or over-the-air (OTA) equipment, which significantly reduces initial infrastructure costs and operational risks. Additionally, by utilizing a virtual road derived from an actual test  
Figure 1: XILS technologies integrated with V-Model. site, it enhances the reproducibility of experiments. Given these advantages, we adopted the PG-based VILS platform for our XILS case study. Simulation platforms for the evaluation and verification of ADSs have been continuously developed and refined. However, before assessing the consistency of results between real-world experiments and simulations, the credibility of the simulation platform itself must be confirmed. [PERSON] [30,31] proposed a methodology to implement the AD-VILS platform designed for evaluating ADSs and developed a technique to assess the platform's reliability based on key test parameters relevant to ADSs. They quantitatively evaluated consistency by comparing these key parameters between real-vehicle tests and VILS tests based on statistical indicators. Furthermore, they proposed a scenario-based reliability evaluation method to verify whether VILS testing could partially replace real-world testing or be effective in specific scenarios. Based on the indices of consistency between real-vehicle tests and VILS tests, they derived correlation and applicability metrics to evaluate the platform's overall reliability.