time and date: 
10:30 am, July 30, 2026

location:
Room 441, HYTRB, Taipei Tech

Abstract: 
This study analyses bicycle route choice, focusing on methodological comparison and explainable artificial intelligence (XAI). Using data from multiple German cities, we combine detailed route-level attributes with city-level characteristics to capture both local and contextual influences.

We compare a classical discrete-choice model with machine learning methods. The emphasis is on the trade-off between predictive performance and interpretability. To address this, we apply XAI techniques to systematically evaluate feature importance and model behaviour across methods.

 
Best regards,

Iryna Okhrin