Link: https://doi.org/10.17605/OSF.IO/ZBFXU Data from the real-world data collection described in (Kalantari et al., 2025), using a setup of two stereo camera sensors to record road user trajectories at two locations in Leeds, UK, with frequent driver-pedestrian interactions, one week per location. Kalantari, A. H., Lin, Y. S., Mohammadi, A., Merat, N., & Markkula, G. (2025). Testing the validity of multi-participant distributed simulation for understanding and modeling road user interaction. PsyArXiv preprint.

Link: https://zenodo.org/records/8321136 Data from the experiment described in (Ma et al., 2024) and (Lin et al., 2024), on pedestrian road-crossing decisions in a controlled environment. Participants were seated in front of a computer screen, with each trial showing an approaching car at one of four times to arrival, and the participants responded with button presses to indicate when they wanted to initiate road-crossing. Both behavioural data (the button press responses) and 64-channel EEG was recorded.

Link: https://doi.org/10.17605/OSF.IO/EAZG5 Data from the experiment described in (Schumann et al., 2023) and (Srinivasan et al., 2024), where participants drove the University of Leeds moving base driving simulator in a simulated urban environment, including both non-critical and safety-critical interactions with other, computer-controlled cars. Schumann, J. F., Srinivasan, A. R., Kober, J., Markkula, G., & Zgonnikov, A. (2023). Using models based on cognitive theory to predict human behavior in traffic: A case study.

Link: https://github.com/gmarkkula/COMMOTIONSFramework A Python implementation of a modular framework for modeling road user interactions, developed in the EPSRC-funded project COMMOTIONS. The repository contains some base modules, an implementation of the framework for “straight crossing paths” scenarios, and a number of tests of specific model variants in driver-pedestrian interaction scenarios, as described in (Markkula et al., 2023). See the repository README for further guidance. Markkula, G., Lin, Y. S., Srinivasan, A.

Link: https://github.com/gmarkkula/GolmanEtAlTypeModel A Python (Jupyter Notebook) implementation of a variant of the “dual accumulator” model of human-like game-theoretic decision making, as proposed by Golman et al. (2019). Golman, R., Bhatia, S., & Kane, P. B. (2019). The dual accumulator model of strategic deliberation and decision making. Psychological Review. https://doi.org/10.1037/rev0000176

Link: https://doi.org/10.17605/OSF.IO/49AWH MATLAB implementation of the models of road-crossing decisions of pedestrians and turning drivers, developed in the European interACT project and described in (Dietrich et al., 2019). This also includes a standalone “simulation tool” with a GUI allowing investigations of how crossing decisions are affected by the behaviour of an approaching vehicle. Dietrich, A., Bengler, K., Markkula, G., Giles, O. T., Lee, Y. M., Pekkanen, J., Madigan, R., & Merat, N.