Building simulation environments for developing and testing autonomous vehicles necessitates that the simulators accurately model the statistical realism of the real-world environment, including the interaction with other vehicles driven by human drivers. To address this requirement, an accurate human behavior model is essential to incorporate the diversity and consistency of human driving behavior. We propose a mathematical framework for designing a data-driven simulation model that simulates human driving behavior more realistically than the currently used physics-based simulation models. Experiments conducted using the NGSIM dataset validate our hypothesis regarding the necessity of considering the complexity, diversity, and consistency of human driving behavior when aiming to develop realistic simulators.

翻译：为开发与测试自动驾驶车辆构建仿真环境时，须确保模拟器能精确刻画真实环境的统计真实性，包括与人类驾驶员操控的其他车辆之间的交互。为满足这一需求，需建立精确的人类行为模型以融合驾驶行为的多样性与一致性。我们提出一个数学框架，用于设计数据驱动的仿真模型，该模型能比当前基于物理的仿真模型更真实地模拟人类驾驶行为。基于NGSIM数据集开展的实验验证了这一假设：在构建逼真模拟器时，必须考虑人类驾驶行为的复杂性、多样性与一致性。