## 2 Related Work
However, existing credibility-assessment techniques for XILS platforms still have significant limitations. Major issues include their focus on evaluating advanced driver assistance system (ADAS) functions without sufficiently considering the overall dynamic behavior of the vehicle. Furthermore, most verification frameworks are limited to low-speed scenarios, which hinders reliability verification under higher-speed conditions. Additionally, the requirement for repeating independent experiments under different speed conditions represents a significant structural inefficiency. Therefore, we propose a novel framework for evaluating the credibility of XILS platforms as a virtual tool chain for ADS validation. The strategy involves statistical and mathematical comparisons between the results of XILS tests and real-vehicle tests, with similarity and consistency metrics calculated for each test. These metrics are determined from the perspectives of parameters, scenarios, and dynamics, and the calculated consistency enables evaluation across three aspects: parameter-based reliability, scenario-based reliability, and dynamics-based fidelity. Ultimately, the credibility of the XILS platform is determined based on the results of these three types of analyses. Furthermore, to ensure efficient credibility evaluation, geometric similarity analysis is performed. The credibility evaluation metrics, derived from experimental data obtained through tests conducted under various speed conditions within the same scenario, are visualized on spider charts. The use of geometric shape comparison metrics allows quantitative analysis of the similarity between two shapes, demonstrating that speed is not the dominant factor when assessing scenario credibility. Additionally, the analysis of geometric similarities between different scenarios suggests the possibility of establishing a representativeness assessment framework, where certain scenarios can serve as proxies for the credibility assessment of others. The systematic credibility evaluation framework proposed herein is expected to efficiently verify whether virtual XILS test results remain valid in real-world driving environments, thereby serving as a dependable foundation for the development of ADSs. The remainder of this paper is structured as follows: Section 3 explains the proposed credibility-assessment methodology, which is based on an integrated evaluation framework that considers not only reliability but also fidelity while reflecting dynamic consistency. Section 4 introduces the procedures for efficiently verifying the credibility of XILS platforms, which is followed by a test to determine whether the speed condition is the dominant factor when assessing a given scenario. The credibility-assessment results across various speed conditions within the same scenario are visualized through spider charts, and the similarity between shapes is quantitatively analyzed through geometric shape comparison. This similarity analysis serves as the basis for evaluating the efficiency of credibility validation. Furthermore, we extend the geometric shape comparison to scenarios involving different driving maneuvers to establish a methodology for confirming whether certain scenarios can represent others. Section 5 describes the experimental environment created for the real-vehicle tests and VILS tests and discusses the validity of the methods outlined in Sections 3 and 4 based on experimental results. Finally, Section 6 presents the implications of our findings for the credibility assessment of simulation platforms, states the limitations of this study, and outlines future research directions.