Cited by

• 2020A tutorial on recursive models for analyzing and predicting path choice behavior44 cited
• 2024Travel behaviour and multimodality: a conceptual framework and critical review of research34 cited
• 2020Surveying and analysing mode and route choices in Switzerland 2010–201531 cited
• 2022Understanding the route choice behaviour of metro-bikeshare users29 cited
• 2021The whole day path planning problem incorporating mode chains modeling in the era of mobility as a service26 cited
• 2023Capturing positive network attributes during the estimation of recursive logit models: A prism-based approach23 cited
• 2024What influences intermodal Choices: Metro-Centric, Bus-Centric, Hybrid? insights from Machine learning Approaches21 cited
• 2023Exploring motivations for multimodal commuting: A hierarchical means-end chain analysis17 cited
• 2024Comparative study of route choice models for cyclists16 cited
• 2023Roles of accessibility and air-rail intermodality in shaping mobility patterns in mega-city regions: Behavioural insights from China16 cited
• 2024Understanding passengers' intermodal travel behavior to improve air-rail service: A case study of Beijing-Tianjin-Hebei urban agglomeration14 cited
• 2020Determining an efficient and precise choice set for public transport based on tracking data12 cited
• 2025Modelling route choice in public transport with deep learning10 cited
• 2024Recursive logit-based meta-inverse reinforcement learning for driver-preferred route planning9 cited
• 2021Using neural nets to predict transportation mode choice: Amsterdam network change analysis9 cited
• 2024How does the built environment affect intermodal transit demand across different spatiotemporal contexts?8 cited