Traffic interactions between merging and highway vehicles are a major topic of research, yielding many empirical studies and models of driver behaviour. Most of these studies on merging use naturalistic data. Although this provides insight into human gap acceptance and traffic flow effects, it obscures the operational inputs of interacting drivers. Besides that, researchers have no control over the vehicle kinematics (i.e., positions and velocities) at the start of the interactions. Therefore the relationship between initial kinematics and the outcome of the interaction is difficult to investigate. To address these gaps, we conducted an experiment in a coupled driving simulator with a simplified, top-down view, merging scenario with two vehicles. We found that kinematics can explain the outcome (i.e., which driver merges first) and the duration of the merging conflict. Furthermore, our results show that drivers use key decision moments combined with constant acceleration inputs (intermittent piecewise-constant control) during merging. This indicates that they do not continuously optimize their expected utility. Therefore, these results advocate the development of interaction models based on intermittent piecewise-constant control. We hope our work can contribute to this development and to the fundamental knowledge of interactive driver behaviour.

翻译：合流车辆与高速公路车辆之间的交通交互是研究的重要课题，催生了许多关于驾驶员行为的实证研究和模型。大多数关于合流的研究使用自然驾驶数据。尽管这为理解人类可接受间隙和交通流影响提供了洞见，但掩盖了交互驾驶员的操作输入。此外，研究人员无法控制交互开始时车辆的运动学特征（即位置和速度），因此初始运动学与交互结果之间的关系难以探究。为解决这些问题，我们在一个采用简化俯视合流场景的双车耦合驾驶模拟器中开展实验。研究发现，运动学特征能够解释合流结果（即哪辆车先合流）及合流冲突的持续时间。此外，我们的结果表明驾驶员在合流过程中会结合恒定加速度输入（间歇片式恒定控制）使用关键决策时刻。这表明他们并非持续优化预期效用。因此，这些结果支持基于间歇片式恒定控制的交互模型开发。我们希望这项工作能为该模型开发及交互式驾驶员行为的基础认知做出贡献。