| 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 | 173 | 2018 |
| 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 | 94 | 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 | 74 | 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 | 56 | 2020 |
| 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 | 46 | 2016 |
| 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 | 21 | 2020 |
| 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 | 13 | 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 | 7 | 2020 |
| Car-following headways in different driving situations: a naturalistic driving study M Zhu, X Wang, X Wang CICTP 2016, 1419-1428, 2016 | 7 | 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 | 6 | 2021 |
| 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 | 6 | 2020 |
| Calibrating and Validating Car-following Models on Urban Expressways for Chinese Drivers Using Naturalistic Driving Data X Wang, M Zhu China Journal of Highway and Transport 31 (9), 129-138, 2017 | 6 | 2017 |
| Impacts of collision warning system on car following behavior based on naturalistic driving data X Wang, M Zhu, Y Xing Journal of Tongji University (Natural Science) 44 (7), 1045-1051, 2016 | 6 | 2016 |
| 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 | 5 | 2016 |
| 基于自然驾驶数据的中国驾驶人城市快速路跟驰模型标定与验证 王雪松， 朱美新 中国公路学报 31 (9), 129-137, 2018 | 4 | 2018 |
| 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 | 2 | 2020 |
| 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 | 2 | 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 | 2 | 2019 |
| 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 |
| Modeling car-following behavior on freeways considering driving style P Sun, X Wang, M Zhu Journal of transportation engineering, Part A: Systems 147 (12), 04021083, 2021 | 1 | 2021 |
Yinhai WangProfessor of Civil and Environmental Engineering, University of WashingtonVerified email at uw.edu
