用响应图建模人类对自动驾驶车行为的反应，揭示不同交互模式下的驾驶差异。
Characterizing Driver Interactions with Autonomous Vehicles via Response Maps
- 基于博弈论构建响应图，将人类驾驶行为建模为与自动驾驶车辆状态的反馈关系。
- 实验证明人类加速行为可被响应图有效捕捉，且对让行、不让行等行为反应显著不同。
- 适用于自动驾驶系统设计与人机交互研究，尤其关注社会兼容性导航场景。
理解人类对自动驾驶车辆（AV）行为的反应对于实现社会意识交互至关重要，这在共享交通环境中是实现社会兼容导航的关键。本文将人类驾驶员在与自动驾驶车辆交互中的反应建模为人类驾驶车辆与自动驾驶车辆耦合状态空间上的反馈律。通过基于博弈论的响应图概念，采用线性表示方法，根据驾驶模拟器实验的实证数据，将人类驾驶员的行为建模为自动驾驶车辆行为的函数。结果表明：1）人类驾驶员的加速度行为可被响应图有效捕捉；2）人类驾驶员的反应在自动驾驶车辆采取让行、不让行以及响应人类驾驶员等不同行为时存在显著差异。
原文摘要 · Abstract (English)
Understanding human responses to autonomous vehicle (AV) behaviors is essential for socially aware interaction, which is crucial for socially compatible navigation in shared traffic environments. We characterize human driving responses in interactions with AVs as feedback laws over the coupled state space of the human driven vehicle and the AV. We model the human driver's actions using a response map, a concept based in game theory, and employ a linear representation to capture driver behaviors as a function of AV behaviors, based on empirical data from a driving simulator study. Our results show that 1) human driver acceleration behavior can be captured using response maps, and 2) human driver responses differ significantly with respect to AV behaviors of yielding, non-yielding, and responsive to the human driver.
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