Accurate modelling of road user interaction has received lot of attention in recent years due to the advent of increasingly automated vehicles. To support such modelling, there is a need to complement naturalistic datasets of road user interaction with targeted, controlled study data. This paper describes a dataset collected in a simulator study conducted in the project COMMOTIONS, addressing urban driving interactions, in a state of the art moving base driving simulator. The study focused on two types of near-crash situations that can arise in urban driving interactions, and also collected data on human driver gap acceptance across a range of controlled gap sequences.

翻译：近年来，随着自动化车辆的日益普及，道路使用者交互的精确建模受到了广泛关注。为支持此类建模，有必要通过有针对性的受控研究数据来补充道路使用者交互的自然主义数据集。本文描述了在COMMOTIONS项目中通过先进动基驾驶模拟器收集的数据集，该研究聚焦于城市驾驶交互。研究重点关注城市驾驶交互中可能出现的两类近碰撞情境，同时采集了人类驾驶员在一系列受控间隙序列中的间隙接受行为数据。