系统化识别驾驶模拟中交通仿真需求，提升真实感与实验有效性。
Requirement Identification for Traffic Simulations in Driving Simulators
- 分阶段设定子目标，推导微观仿真、智能体模型与视觉呈现的技术需求。
- 确保仿真高保真度，提升实验结果可信度与参与者沉浸感。
- 适合自动驾驶测试、人机交互研究等需高真实感的场景。
本文针对保障交通模拟真实性的挑战，提出一种系统化方法，用于识别交通仿真需求。该方法基于各研究阶段的子目标，推导出微观层面、代理模型及视觉表现的具体技术要求。通过建立研究目标与仿真设计之间的清晰关联，该方法旨在维持高保真度，从而增强实验结果的有效性与参与者的沉浸体验。该框架支持更可靠的汽车研发与测试流程。
原文摘要 · Abstract (English)
This paper addresses the challenge of ensuring realistic traffic conditions by proposing a methodology that systematically identifies traffic simulation requirements. Using a structured approach based on sub-goals in each study phase, specific technical needs are derived for microscopic levels, agent models, and visual representation. The methodology aims to maintain a high degree of fidelity, enhancing both the validity of experimental outcomes and participant engagement. By providing a clear link between study objectives and traffic simulation design, this approach supports robust automotive development and testing.
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