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 | 107 | 2021 |
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 | 85 | 2020 |
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 | 61* | 2021 |
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 | 48 | 2021 |
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 | 48 | 2018 |
Speed profile estimation using license plate recognition data B Mo, R Li, X Zhan Transportation Research Part C: Emerging Technologies 82, 358-378, 2017 | 46 | 2017 |
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 | 40 | 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 | 40 | 2020 |
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 | 39 | 2020 |
Individual mobility prediction in mass transit systems using smart card data: an interpretable activity-based hidden Markov approach B Mo, Z Zhao, HN Koutsopoulos, J Zhao IEEE Transactions on Intelligent Transportation Systems 23 (8), 12014-12026, 2022 | 37* | 2022 |
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 | 33 | 2021 |
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 | 31* | 2021 |
Inferring passenger responses to urban rail disruptions using smart card data: A probabilistic framework B Mo, HN Koutsopoulos, J Zhao Transportation Research Part E: Logistics and Transportation Review 159, 102628, 2022 | 26 | 2022 |
Ex post path choice estimation for urban rail systems using smart card data: An aggregated time-space hypernetwork approach B Mo, Z Ma, HN Koutsopoulos, J Zhao Transportation Science 57 (2), 313-335, 2023 | 20* | 2023 |
Impacts of subjective evaluations and inertia from existing travel modes on adoption of autonomous mobility-on-demand B Mo, QY Wang, J Moody, Y Shen, J Zhao Transportation Research Part C: Emerging Technologies 130, 103281, 2021 | 19 | 2021 |
Robust path recommendations during public transit disruptions under demand uncertainty B Mo, HN Koutsopoulos, ZJM Shen, J Zhao Transportation Research Part B: Methodological 169, 82-107, 2023 | 15 | 2023 |
Impact of unplanned long-term service disruptions on urban public transit systems B Mo, MY Von Franque, HN Koutsopoulos, JP Attanucci, J Zhao IEEE Open Journal of Intelligent Transportation Systems 3, 551-569, 2022 | 11* | 2022 |
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 | 7 | 2019 |
Large language models for travel behavior prediction B Mo, H Xu, D Zhuang, R Ma, X Guo, J Zhao arXiv preprint arXiv:2312.00819, 2023 | 6 | 2023 |
Predicting drivers’ route trajectories in last-mile delivery using a pair-wise attention-based pointer neural network B Mo, Q Wang, X Guo, M Winkenbach, J Zhao Transportation Research Part E: Logistics and Transportation Review 175, 103168, 2023 | 6 | 2023 |