  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.
