System-of-systems (SoS) evolution is a complex and unpredictable process. Although various principles to facilitate collaborative SoS evolution have been proposed, there is a lack of experimental data validating their effectiveness. To address these issues, we present an Agent-Based Model (ABM) for SoS evolution in the Internet of Vehicles (IoV), serving as a quantitative analysis tool for SoS research. By integrating multiple complex and rational behaviors of individuals, we aim to simulate real-world scenarios as accurately as possible. To simulate the SoS evolution process, our model employs multiple agents with autonomous interactions and incorporates external environmental variables. Furthermore, we propose three evaluation metrics: evolutionary time, degree of variation, and evolutionary cost, to assess the performance of SoS evolution. Our study demonstrates that enhanced information transparency significantly improves the evolutionary performance of distributed SoS. Conversely, the adoption of uniform standards only brings limited performance enhancement to distributed SoSs. Although our proposed model has limitations, it stands out from other approaches that utilize Agent-Based Modeling to analyze SoS theories. Our model focuses on realistic problem contexts and simulates realistic interaction behaviors. This study enhances the comprehension of SoS evolution processes and provides valuable insights for the formulation of effective evolutionary strategies.

中文翻译：

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系统系统的有效进化原则：车载网络中基于代理的建模的见解

系统的系统（SoS）演进是一个复杂且不可预测的过程。尽管已经提出了促进协作 SoS 进化的各种原则，但缺乏验证其有效性的实验数据。为了解决这些问题，我们提出了一种用于车联网 (IoV) 中 SoS 演化的基于代理的模型 (ABM)，作为 SoS 研究的定量分析工具。通过整合个体的多种复杂而理性的行为，我们的目标是尽可能准确地模拟现实世界的场景。为了模拟 SoS 演化过程，我们的模型采用具有自主交互的多个代理，并结合了外部环境变量。此外，我们提出了三个评估指标：进化时间、变异程度和进化成本，来评估 SoS 进化的性能。我们的研究表明，增强的信息透明度可以显着提高分布式 SoS 的进化性能。相反，采用统一标准只能给分布式SoS带来有限的性能提升。尽管我们提出的模型有局限性，但它从其他利用基于代理的建模来分析 SoS 理论的方法中脱颖而出。我们的模型专注于现实问题上下文并模拟现实交互行为。这项研究增强了对 SoS 进化过程的理解，并为制定有效的进化策略提供了宝贵的见解。