The COMMOTIONS Urban Interactions Driving Simulator Study Dataset

TL;DR

This work tackles the limited public data on near-crash interactions in urban driving by presenting a high-fidelity driving-simulator dataset from the COMMOTIONS project. Using a moving-base UoLDS system, it collects routine and targeted near-crash scenarios, plus controlled gap-acceptance trials, from 80 participants across two near-crash scenarios and two urgency levels. The dataset comprises 160 near-crash observations and 160 gap-acceptance observations, with thorough metadata and anonymization to enable reproducibility and model validation for automated-vehicle research. By providing detailed scenario definitions, simulator configurations, and data-access instructions, the dataset supports evaluation of human-driving interaction models prior to real-world deployment and can aid regulators and manufacturers in safety testing.

Abstract

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.

Figures (8)

• Figure 1: A graphical representation of the gap acceptance scenario where SV has no priority and POVs are in the arterial (tangential) roadway with priority
• Figure 2: Principal other vehicle (POV) yielding to the turning subject vehicle (SV) out of courtesy (a) pictorial depiction (b) time to arrival (TTA) of the POV & SV at the conflict zone (CZ) based schematic description. $T_{h_1}$ and $T_{h_2}$ are the headlight flashes by the POV based on SV's TTA to CZ
• Figure 3: Principal other vehicle (POV) waiting for subject vehicle (SV) to cross before pulling out and driving in opposite direction (a) pictorial depiction (b) typical acceleration profile for the POV with respect to the SV according to the scenario description
• Figure 4: Acceleration profile for the POV in a near-crash pull-out by POV in a T-junction. Here we have assumed that the SV keeps a constant speed throughout the scenario. The step-like change in acceleration of POV is used to showcase the timing of the event. The POV in practice had a ramp-like acceleration profile
• Figure 5: TTA profile for the POV in a near-crash initiated by POV in a T-like junction with headlight flashing similar to \ref{['sec:like_yield']}