| Multistep speed prediction on traffic networks: A deep learning approach considering spatio-temporal dependencies Z Zhang, M Li, X Lin, Y Wang, F He Transportation research part C: emerging technologies 105, 297-322, 2019 | 237 | 2019 |
| Short-term prediction of lane-level traffic speeds: A fusion deep learning model Y Gu, W Lu, L Qin, M Li, Z Shao Transportation research part C: emerging technologies 106, 1-16, 2019 | 153 | 2019 |
| Traffic energy and emission reductions at signalized intersections: a study of the benefits of advanced driver information M Li, K Boriboonsomsin, G Wu, WB Zhang, M Barth International Journal of Intelligent Transportation Systems Research 7 (1 …, 2009 | 152 | 2009 |
| Multi-vehicle routing problems with soft time windows: A multi-agent reinforcement learning approach K Zhang, F He, Z Zhang, X Lin, M Li Transportation Research Part C: Emerging Technologies 121, 102861, 2020 | 140 | 2020 |
| Modeling and implementation of adaptive transit signal priority on actuated control systems M Li, Y Yin, WB Zhang, K Zhou, H Nakamura Computer‐Aided Civil and Infrastructure Engineering 26 (4), 270-284, 2011 | 95 | 2011 |
| Contribution of hydroxymethane sulfonate to ambient particulate matter: A potential explanation for high particulate sulfur during severe winter haze in Beijing JM Moch, E Dovrou, LJ Mickley, FN Keutsch, Y Cheng, DJ Jacob, J Jiang, ... Geophysical Research Letters 45 (21), 11,969-11,979, 2018 | 89 | 2018 |
| A two-layer model for taxi customer searching behaviors using GPS trajectory data J Tang, H Jiang, Z Li, M Li, F Liu, Y Wang IEEE transactions on intelligent transportation systems 17 (11), 3318-3324, 2016 | 86 | 2016 |
| Short-term prediction of safety and operation impacts of lane changes in oscillations with empirical vehicle trajectories M Li, Z Li, C Xu, T Liu Accident Analysis & Prevention 135, 105345, 2020 | 81 | 2020 |
| Energy and emission benefit comparison of stationary and in-vehicle advanced driving alert systems G Wu, K Boriboonsomsin, WB Zhang, M Li, M Barth Transportation research record 2189 (1), 98-106, 2010 | 70 | 2010 |
| Emission mitigation via longitudinal control of intelligent vehicles in a congested platoon Z Wang, X Chen, Y Ouyang, M Li Computer‐Aided Civil and Infrastructure Engineering 30 (6), 490-506, 2015 | 69 | 2015 |
| Designing locations and capacities for charging stations to support intercity travel of electric vehicles: An expanded network approach C Wang, F He, X Lin, ZJM Shen, M Li Transportation Research Part C: Emerging Technologies 102, 210-232, 2019 | 68 | 2019 |
| Offline offset refiner for coordinated actuated signal control systems Y Yin, M Li, A Skabardonis Journal of transportation engineering 133 (7), 423-432, 2007 | 66 | 2007 |
| A reinforcement learning-based vehicle platoon control strategy for reducing energy consumption in traffic oscillations M Li, Z Cao, Z Li IEEE Transactions on Neural Networks and Learning Systems 32 (12), 5309-5322, 2021 | 56 | 2021 |
| Network-wide traffic flow estimation with insufficient volume detection and crowdsourcing data Z Zhang, M Li, X Lin, Y Wang Transportation Research Part C: Emerging Technologies 121, 102870, 2020 | 55 | 2020 |
| Optimal detector location for bus signal priority H Liu, A Skabardonis, W Zhang, M Li Transportation Research Record 1867 (1), 144-150, 2004 | 54 | 2004 |
| Path controlling of automated vehicles for system optimum on transportation networks with heterogeneous traffic stream Z Chen, X Lin, Y Yin, M Li Transportation Research Part C: Emerging Technologies 110, 312-329, 2020 | 53 | 2020 |
| A regret theory-based route choice model M Li, HJ Huang Transportmetrica A: Transport Science 13 (3), 250-272, 2017 | 53 | 2017 |
| Traveler information tool with integrated real-time transit information and multimodal trip planning: Design and implementation L Zhang, JQ Li, K Zhou, SD Gupta, M Li, WB Zhang, MA Miller, JA Misener Transportation research record 2215 (1), 1-10, 2011 | 53 | 2011 |
| A customized deep learning approach to integrate network-scale online traffic data imputation and prediction Z Zhang, X Lin, M Li, Y Wang Transportation Research Part C: Emerging Technologies 132, 103372, 2021 | 51 | 2021 |
| An agent-based choice model for travel mode and departure time and its case study in Beijing M Zou, M Li, X Lin, C Xiong, C Mao, C Wan, K Zhang, J Yu Transportation Research Part C: Emerging Technologies 64, 133-147, 2016 | 51 | 2016 |
Xi LinUniversity of MichiganVerified email at umich.edu
