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The COMMOTIONS Urban Interactions Driving Simulator Study Dataset

Authors :
Srinivasan, Aravinda Ramakrishnan
Schumann, Julian
Wang, Yueyang
Lin, Yi-Shin
Daly, Michael
Solernou, Albert
Zgonnikov, Arkady
Leonetti, Matteo
Billington, Jac
Markkula, Gustav
Srinivasan, Aravinda Ramakrishnan
Schumann, Julian
Wang, Yueyang
Lin, Yi-Shin
Daly, Michael
Solernou, Albert
Zgonnikov, Arkady
Leonetti, Matteo
Billington, Jac
Markkula, Gustav
Publication Year :
2023

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.<br />Comment: 5 pages, 8 figures, 6 tables, data techincal description paper, Open Science Foundation - https://osf.io/eazg5

Details

Database :
OAIster
Publication Type :
Electronic Resource
Accession number :
edsoai.on1381627557
Document Type :
Electronic Resource