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，随着自动化车辆的兴起，道路交通参与者交互的精确建模受到广泛关注。为支撑此类建模工作，有必要用定向、受控的研究数据补充自然状态下的交互数据集。本文介绍了在COMMOTIONS项目中开展的一项模拟器研究中所采集的数据集，该研究利用先进运动基座驾驶模拟器，聚焦城市驾驶交互场景。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，同时采集了驾驶员在多种受控间隙序列下的间隙接受行为数据。