Biblio
Found 9 results
Filters: Author is Baichuan Mo [Clear All Filters]
Competition between Shared Autonomous Vehicles and Public Transit: A Case Study in Singapore. Transportation Research Part C. 2021.
Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks. Transportation Research Part B. 2021.
Capacity-Constrained Network Performance Model for Urban Rail Systems. Transportation Research Record. 2020.
Deep Neural Networks for Choice Analysis: Architecture Design with Alternative-Specific Utility Functions. Transportation Research Part C. 2020.
Latent Attitudes of Existing Travel Modes on Autonomous Vehicle Adoption. In: Transportation Research Board 99th Annual Meeting. Washington, D.C.; 2020.
Modeling Epidemic Spreading through Public Transit using Time-Varying Encounter Network. Transportation Research Part C. 2020.
Predicting Travel Mode Choice with 86 Machine Learning Classifiers: An Empirical Benchmark Study. In: Transportation Research Board 99th Annual Meeting. Washington, D.C.; 2020.
Built Environment and Autonomous Vehicles Mode Choice: A First Mile Scenario in Singapore. In: Transportation Research Board 98th Annual Meeting. Washington, D.C.; 2019.
Impact of Built Environment on First- and Last-Mile Travel Mode Choice. Transportation Research Record. 2018.