| Human-like autonomous car-following model with deep reinforcement learning M Zhu, X Wang, Y Wang Transportation research part C: emerging technologies 97, 348-368, 2018 | 89 | 2018 |
| Drivers’ rear end collision avoidance behaviors under different levels of situational urgency X Wang, M Zhu, M Chen, P Tremont Transportation research part C: emerging technologies 71, 419-433, 2016 | 61 | 2016 |
| Modeling car-following behavior on urban expressways in Shanghai: A naturalistic driving study M Zhu, X Wang, A Tarko Transportation research part C: emerging technologies 93, 425-445, 2018 | 51 | 2018 |
| Development of a kinematic-based forward collision warning algorithm using an advanced driving simulator X Wang, M Chen, M Zhu, P Tremont IEEE Transactions on Intelligent Transportation Systems 17 (9), 2583-2591, 2016 | 31 | 2016 |
| Safe, efficient, and comfortable velocity control based on reinforcement learning for autonomous driving M Zhu, Y Wang, Z Pu, J Hu, X Wang, R Ke Transportation Research Part C: Emerging Technologies 117, 102662, 2020 | 16 | 2020 |
| Impact on car following behavior of a forward collision warning system with headway monitoring M Zhu, X Wang, J Hu Transportation research part C: emerging technologies 111, 226-244, 2020 | 8 | 2020 |
| Car-following headways in different driving situations: A naturalistic driving study M Zhu, X Wang, X Wang CICTP 2016, 1419-1428, 2016 | 5 | 2016 |
| Monitoring Public Transit Ridership Flow by Passively Sensing Wi-Fi and Bluetooth Mobile Devices Z Pu, M Zhu, W Li, Z Cui, X Guo, Y Wang IEEE Internet of Things Journal 8 (1), 474-486, 2020 | 2 | 2020 |
| Traffic Performance Score for Measuring the Impact of COVID-19 on Urban Mobility Z Cui, M Zhu, S Wang, P Wang, Y Zhou, Q Cao, C Kopca, Y Wang arXiv preprint arXiv:2007.00648, 2020 | 2 | 2020 |
| Human-like autonomous car-following planning by deep reinforcement learning M Zhu, X Wang, Y Wang Transportation Research Board 97th Annual MeetingTransportation Research Board, 2018 | 2 | 2018 |
| Optimizing Signal Timing Control for Large Urban Traffic Networks Using an Adaptive Linear Quadratic Regulator Control Strategy H Wang, M Zhu, W Hong, C Wang, G Tao, Y Wang IEEE Transactions on Intelligent Transportation Systems, 2020 | 1 | 2020 |
| Mining public transit ridership flow and origin-destination information from Wi-Fi and Bluetooth sensing data Z Pu, M Zhu, Z Cui, Y Wang arXiv preprint arXiv:1911.01282, 2019 | 1 | 2019 |
| Traffic Sign Detection and Recognition for Autonomous Driving in Virtual Simulation Environment M Zhu, J Hu, Z Pu, Z Cui, L Yan, Y Wang arXiv preprint arXiv:1911.05626, 2019 | 1 | 2019 |
| Globalized Modeling and Signal Timing Control for Large-scale Networked Intersections H Wang, CR Wang, M Zhu, W Hong Proceedings of the 2nd ACM/EIGSCC Symposium on Smart Cities and Communities, 1-7, 2019 | 1 | 2019 |
| An artificial intelligence platform for network-wide congestion detection and prediction using multi-source data Y Wang, XJ Ban, Z Cui, M Zhu Connected Cities for Smart Mobility toward Accessible and Resilient …, 2019 | 1 | 2019 |
| 驾驶员前向避撞行为特征的降维及多元方差分析 王雪松， 朱美新， 陈铭 同济大学学报 (自然科学版) 44 (12), 1858-1866, 2017 | 1 | 2017 |
| 基于自然驾驶数据的避撞预警对跟车行为影响 王雪松， 朱美新， 邢祎伦 同济大学学报 (自然科学版) 44 (7), 1045-1051, 2016 | 1 | 2016 |
| 工况紧急程度对驾驶员避撞行为的影响 王雪松， 朱美新， 陈铭 同济大学学报 (自然科学版) 44 (6), 0876-0883, 2016 | 1 | 2016 |
| How Fast You Will Drive? Predicting Speed of Customized Paths By Deep Neural Network H Yang, C Liu, M Zhu, X Ban, Y Wang IEEE Transactions on Intelligent Transportation Systems, 2021 | | 2021 |
| Hybrid Data-Fusion Model for Short-Term Road Hazardous Segments Identification Based on the Acceleration and Deceleration Information H Yang, C Liu, M Zhu, W Sun, Y Wang International Conference on Transportation and Development 2020, 313-326, 2020 | | 2020 |
Yinhai WangProfessor of Civil and Environmental Engineering, University of WashingtonVerified email at uw.edu
