%0 Generic
%A He, Xiaolin
%A Li, Zirui
%A Wang, Xinwei
%A Happee, R. (Riender)
%A Wang, Meng
%D 2025
%T Data and code underlying the online perceived risk study
%U 
%R 10.4121/242d9474-e522-4518-8917-8f284fc8a7a8.v1
%K perceived risk
%K automated vehicles
%K explainable AI
%K data-driven human behaviour analysis
%X <p>This study explores the dynamic nature of perceived risk in vehicle interactions. Using a novel simulation-based approach, time-continuous perceived risk data were obtained from over 140k ratings by 2,164 participants across various traffic scenarios. This package contains the collected perceived risk data, corresponding kinematic data of the simulation, code and software implementation in MATLAB, Python, SPSS, and Origin for data processing, statistical analysis, model calibration, perceived risk prediction, SHAP analysis and visualisation.</p>
%I 4TU.ResearchData