Data and analysis scripts for: Modeling the impact of motivation on pedestrian dynamics using expectancy-value theory

This dataset accompanies the manuscript "Modeling the impact of motivation on pedestrian dynamics using expectancy-value theory" by Üsten, Sieben, Chraibi, and Seyfried.

It contains the aggregated simulation results, experimental analysis outputs, configuration files, and all figures presented in the paper. The simulation implements
  an expectancy-value-payoff (EVP) motivation model on top of the Collision-Free Speed Model in JuPedSim, evaluated in a closed-door bottleneck scenario with two
  population sizes (N=40 and N=80) across 10 paired seeds per model.

The experimental analysis applies the same rank–area observable to trajectory data from the CROMA bottleneck experiments (Adrian et al., 2020; Sieben & Postmes,
  2025), comparing low-motivation and high-motivation conditions.

Key contents:

- Paired Wilcoxon signed-rank tests and Cliff's delta effect sizes (PVE vs base model)
- Per-seed summary scalars (Spearman rho, OLS slope, tail ratio, density metrics)
-  CROMA experimental crossing-order vs Voronoi area data
- All paper figures (band plots, trajectory visualizations, EVP component curves, parameter mappings)
- Simulation configuration files for full reproducibility

  ▎ The full simulation code is available at: https://github.com/PedestrianDynamics/Motivation (commit b7124fc).