| Logistic modeling of the equilibrium speed–density relationship H Wang, J Li, QY Chen, D Ni Transportation research part A: policy and practice 45 (6), 554-566, 2011 | 201 | 2011 |
| Stochastic modeling of the equilibrium speed–density relationship H Wang, D Ni, QY Chen, J Li Journal of advanced transportation 47 (1), 126-150, 2013 | 126 | 2013 |
| Modeling heterogeneous traffic flow: A pragmatic approach ZS Qian, J Li, X Li, M Zhang, H Wang Transportation Research Part B: Methodological 99, 183-204, 2017 | 118 | 2017 |
| Analysis of LWR model with fundamental diagram subject to uncertainties J Li, QY Chen, H Wang, D Ni Taylor & Francis Group, 2011 | 104 | 2011 |
| Fundamental diagram of traffic flow: New identification scheme and further evidence from empirical data J Li, M Zhang Transportation Research Record, 50-59, 2011 | 83 | 2011 |
| Speed-density relationship: From deterministic to stochastic H Wang, J Li, Q Chen, D Ni Transportation Research Board 88th Annual MeetingTransportation Research Board, 2009 | 80 | 2009 |
| Calculation of traffic flow breakdown probability to optimize link throughput H Wang, K Rudy, J Li, D Ni Applied Mathematical Modelling 34 (11), 3376-3389, 2010 | 58 | 2010 |
| Forecasting people’s needs in hurricane events from social network L Nguyen, Z Yang, J Li, Z Pan, G Cao, F Jin IEEE Transactions on Big Data 8 (1), 229-240, 2019 | 42 | 2019 |
| A methodology to estimate capacity impact due to connected vehicle technology D Ni, J Li, S Andrews, H Wang International Journal of Vehicular Technology 2012 (1), 502432, 2012 | 34 | 2012 |
| Preliminary estimate of highway capacity benefit attainable with IntelliDrive technologies D Ni, J Li, S Andrews, H Wang 13th International IEEE Conference on Intelligent Transportation Systems …, 2010 | 22 | 2010 |
| Modeling space–time inhomogeneities with the kinematic wave theory J Li, HM Zhang Transportation Research Part B: Methodological 54, 113-125, 2013 | 21 | 2013 |
| Representing the fundamental diagram: The pursuit of mathematical elegance and empirical accuracy H Wang, J Li, Q Chen, D Ni Transportation Research Board 89th Annual MeetingTransportation Research Board, 2010 | 21 | 2010 |
| Cross-validating traffic speed measurements from probe and stationary sensors through state reconstruction J Li, K Perrine, L Wu, CM Walton International journal of transportation science and technology 8 (3), 290-303, 2019 | 18 | 2019 |
| Coordinating disaster emergency response with heuristic reinforcement learning Z Yang, L Nguyen, J Zhu, Z Pan, J Li, F Jin 2020 IEEE/ACM International Conference on Advances in Social Networks …, 2020 | 15 | 2020 |
| Coupled linear programming approach for decentralized control of urban traffic J Li, HM Zhang Transportation Research Record 2439 (1), 83-93, 2014 | 13 | 2014 |
| Equilibrium modeling of mixed autonomy traffic flow based on game theory J Li, D Chen, M Zhang Transportation research part B: methodological 166, 110-127, 2022 | 12 | 2022 |
| The variational formulation of a non-equilibrium traffic flow model: theory and implications J Li, HM Zhang Procedia-Social and Behavioral Sciences 80, 327-340, 2013 | 12 | 2013 |
| A generalized queuing model and its solution properties J Li, HM Zhang Transportation Research Part B: Methodological 79, 78-92, 2015 | 10 | 2015 |
| Optimizing environmental sensor station locations for road weather management: overview and a generalized modeling framework AK Singh, J Li, M Murphy, CM Walton Transportation Research Record 2551 (1), 18-28, 2016 | 7 | 2016 |
| Bounding tandem queuing system performance with variational theory J Li, HM Zhang Transportation Research Part B: Methodological 81, 848-862, 2015 | 5 | 2015 |
