Baichuan Mo
Baichuan Mo
Ph.D. Candidate, MIT
在 mit.edu 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Speed profile estimation using license plate recognition data
B Mo, R Li, X Zhan
Transportation Research Part C: Emerging Technologies 82, 358-378, 2017
232017
Impact of built environment on first-and last-mile travel mode choice
B Mo, Y Shen, J Zhao
Transportation Research Record 2672 (6), 40-51, 2018
152018
Modeling epidemic spreading through public transit using time-varying encounter network
B Mo, K Feng, Y Shen, C Tam, D Li, Y Yin, J Zhao
Transportation Research Part C: Emerging Technologies 122, 102893, 2021
142021
Deep neural networks for choice analysis: Architecture design with alternative-specific utility functions
S Wang, B Mo, J Zhao
Transportation Research Part C: Emerging Technologies 112, 234-251, 2020
122020
Calibrating Path Choices and Train Capacities for Urban Rail Transit Simulation Models Using Smart Card and Train Movement Data
B Mo, Z Ma, HN Koutsopoulos, J Zhao
Journal of Advanced Transportation 2021, 5597130, 2021
7*2021
Capacity-constrained network performance model for urban rail systems
B Mo, Z Ma, HN Koutsopoulos, J Zhao
Transportation Research Record 2674 (5), 59-69, 2020
62020
Estimating dynamic origin–destination demand: A hybrid framework using license plate recognition data
B Mo, R Li, J Dai
ComputerAided Civil and Infrastructure Engineering 35 (7), 734-752, 2020
42020
Competition between shared autonomous vehicles and public transit: A case study in Singapore
B Mo, Z Cao, H Zhang, Y Shen, J Zhao
Transportation Research Part C: Emerging Technologies 127, 103058, 2021
3*2021
Assignment-based Path Choice Estimation for Metro Systems Using Smart Card Data
B Mo, Z Ma, HN Koutsopoulos, J Zhao
arXiv preprint arXiv:2001.03196, 2020
32020
Network performance model for urban rail systems
B Mo
Massachusetts Institute of Technology, 2020
32020
Built environment and autonomous vehicle mode choice: A first-mile scenario in Singapore
Y Shen, B Mo, X Zhang, J Zhao
Transportation Research Board 98th Annual Meeting Transportation Research Board, 2019
32019
Comparing hundreds of machine learning classifiers and discrete choice models in predicting travel behavior: an empirical benchmark
S Wang, B Mo, S Hess, J Zhao
arXiv preprint arXiv:2102.01130, 2021
12021
Individual Mobility Prediction: An Interpretable Activity-based Hidden Markov Approach
B Mo, Z Zhao, HN Koutsopoulos, J Zhao
arXiv preprint arXiv:2101.03996, 2021
12021
Impact of pricing policy change on on-street parking demand and user satisfaction: A case study in Nanning, China
B Mo, H Kong, H Wang, XC Wang, R Li
Transportation Research Part A: Policy and Practice 148, 445-469, 2021
2021
Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks
S Wang, B Mo, J Zhao
Transportation Research Part B: Methodological 146, 333-358, 2021
2021
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