A hybrid deep learning based traffic flow prediction method and its understanding Y Wu, H Tan, L Qin, B Ran, Z Jiang Transportation Research Part C: Emerging Technologies 90, 166-180, 2018 | 742 | 2018 |
Modeling dynamic transportation networks: an intelligent transportation system oriented approach B Ran, D Boyce Springer Science & Business Media, 1996 | 689* | 1996 |
Method of providing travel time B Ran US Patent 6,317,686, 2001 | 605 | 2001 |
A new class of instantaneous dynamic user-optimal traffic assignment models B Ran, DE Boyce, LJ LeBlanc Operations Research 41 (1), 192-202, 1993 | 336 | 1993 |
Dynamic passenger demand oriented metro train scheduling with energy-efficiency and waiting time minimization: Mixed-integer linear programming approaches J Yin, L Yang, T Tang, Z Gao, B Ran Transportation Research Part B: Methodological 97, 182-213, 2017 | 304 | 2017 |
Energy-efficient metro train rescheduling with uncertain time-variant passenger demands: An approximate dynamic programming approach J Yin, T Tang, L Yang, Z Gao, B Ran Transportation Research Part B: Methodological 91, 178-210, 2016 | 286 | 2016 |
A dynamic lane-changing trajectory planning model for automated vehicles D Yang, S Zheng, C Wen, PJ Jin, B Ran Transportation Research Part C: Emerging Technologies 95, 228-247, 2018 | 240 | 2018 |
Use of local linear regression model for short-term traffic forecasting H Sun, HX Liu, H Xiao, RR He, B Ran Transportation Research Record 1836 (1), 143-150, 2003 | 240 | 2003 |
Central processing and combined central and local processing of personalized real-time traveler information over internet/intranet B Ran, J Li US Patent 6,209,026, 2001 | 230 | 2001 |
Short-term traffic prediction based on dynamic tensor completion H Tan, Y Wu, B Shen, PJ Jin, B Ran IEEE Transactions on Intelligent Transportation Systems 17 (8), 2123-2133, 2016 | 223 | 2016 |
Short term traffic forecasting using the local linear regression model H Sun, HX Liu, H Xiao, B Ran | 197 | 2002 |
Exploring the factors affecting mode choice Intention of autonomous vehicle based on an extended theory of planned behavior—A case study in China P Jing, H Huang, B Ran, F Zhan, Y Shi Sustainability 11 (4), 1155, 2019 | 196 | 2019 |
Day-ahead traffic flow forecasting based on a deep belief network optimized by the multi-objective particle swarm algorithm L Li, L Qin, X Qu, J Zhang, Y Wang, B Ran Knowledge-Based Systems 172, 1-14, 2019 | 190 | 2019 |
Dynamic urban transportation network models: theory and implications for intelligent vehicle-highway systems B Ran, D Boyce Springer Science & Business Media, 2012 | 190 | 2012 |
Missing value imputation for traffic-related time series data based on a multi-view learning method L Li, J Zhang, Y Wang, B Ran IEEE Transactions on Intelligent Transportation Systems 20 (8), 2933-2943, 2018 | 181 | 2018 |
A link-based variational inequality model for dynamic departure time/route choice B Ran, RW Hall, DE Boyce Transportation Research Part B: Methodological 30 (1), 31-46, 1996 | 180 | 1996 |
Developing a dynamic traffic management modeling framework for hurricane evacuation B Barrett, B Ran, R Pillai Transportation Research Record 1733 (1), 115-121, 2000 | 175 | 2000 |
Autonomous vehicle-intersection coordination method in a connected vehicle environment P Lin, J Liu, PJ Jin, B Ran IEEE Intelligent Transportation Systems Magazine 9 (4), 37-47, 2017 | 149 | 2017 |
Tensor based missing traffic data completion with spatial–temporal correlation B Ran, H Tan, Y Wu, PJ Jin Physica A: Statistical Mechanics and its Applications 446, 54-63, 2016 | 149 | 2016 |
Decentralized cooperative lane-changing decision-making for connected autonomous vehicles J Nie, J Zhang, W Ding, X Wan, X Chen, B Ran IEEE access 4, 9413-9420, 2016 | 141 | 2016 |