| Accelerated evaluation of automated vehicles safety in lane-change scenarios based on importance sampling techniques D Zhao, H Lam, H Peng, S Bao, DJ LeBlanc, K Nobukawa, CS Pan IEEE transactions on intelligent transportation systems 18 (3), 595-607, 2016 | 407 | 2016 |
| Accelerated evaluation of automated vehicles in car-following maneuvers D Zhao, X Huang, H Peng, H Lam, DJ LeBlanc IEEE Transactions on Intelligent Transportation Systems 19 (3), 733-744, 2017 | 232 | 2017 |
| Intelligent and connected vehicles: Current status and future perspectives DG Yang, K Jiang, D Zhao, CL Yu, Z Cao, SC Xie, ZY Xiao, XY Jiao, ... Science China Technological Sciences 61, 1446-1471, 2018 | 176 | 2018 |
| Driving style analysis using primitive driving patterns with Bayesian nonparametric approaches W Wang, J Xi, D Zhao IEEE Transactions on Intelligent Transportation Systems 20 (8), 2986-2998, 2018 | 160 | 2018 |
| A learning-based approach for lane departure warning systems with a personalized driver model W Wang, D Zhao, W Han, J Xi IEEE Transactions on Vehicular Technology 67 (10), 9145-9157, 2018 | 144 | 2018 |
| A survey on safety-critical driving scenario generation—A methodological perspective W Ding, C Xu, M Arief, H Lin, B Li, D Zhao IEEE Transactions on Intelligent Transportation Systems 24 (7), 6971-6988, 2023 | 114 | 2023 |
| Learning and inferring a driver's braking action in car-following scenarios W Wang, J Xi, D Zhao IEEE Transactions on Vehicular Technology 67 (5), 3887-3899, 2018 | 107 | 2018 |
| How much data are enough? A statistical approach with case study on longitudinal driving behavior W Wang, C Liu, D Zhao IEEE Transactions on Intelligent Vehicles 2 (2), 85-98, 2017 | 105 | 2017 |
| Prompting decision transformer for few-shot policy generalization M Xu, Y Shen, S Zhang, Y Lu, D Zhao, J Tenenbaum, C Gan international conference on machine learning, 24631-24645, 2022 | 96 | 2022 |
| Accelerated evaluation of automated vehicles using piecewise mixture models Z Huang, H Lam, DJ LeBlanc, D Zhao IEEE Transactions on Intelligent Transportation Systems 19 (9), 2845-2855, 2017 | 91 | 2017 |
| Multimodal safety-critical scenarios generation for decision-making algorithms evaluation W Ding, B Chen, B Li, KJ Eun, D Zhao IEEE Robotics and Automation Letters 6 (2), 1551-1558, 2021 | 90 | 2021 |
| Learning to collide: An adaptive safety-critical scenarios generating method W Ding, B Chen, M Xu, D Zhao 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 90 | 2020 |
| Mapper: Multi-agent path planning with evolutionary reinforcement learning in mixed dynamic environments Z Liu, B Chen, H Zhou, G Koushik, M Hebert, D Zhao 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 84 | 2020 |
| Extracting traffic primitives directly from naturalistically logged data for self-driving applications W Wang, D Zhao IEEE Robotics and Automation Letters 3 (2), 1223-1229, 2018 | 84 | 2018 |
| Empirical study of DSRC performance based on safety pilot model deployment data X Huang, D Zhao, H Peng IEEE Transactions on Intelligent Transportation Systems 18 (10), 2619-2628, 2017 | 76 | 2017 |
| Trafficnet: An open naturalistic driving scenario library D Zhao, Y Guo, YJ Jia 2017 IEEE 20th International Conference on Intelligent Transportation …, 2017 | 71 | 2017 |
| Constrained variational policy optimization for safe reinforcement learning Z Liu, Z Cen, V Isenbaev, W Liu, S Wu, B Li, D Zhao International Conference on Machine Learning, 13644-13668, 2022 | 66 | 2022 |
| Accelerated Evaluation of Automated Vehicles. D Zhao | 64 | 2016 |
| Delay-aware model-based reinforcement learning for continuous control B Chen, M Xu, L Li, D Zhao Neurocomputing 450, 119-128, 2021 | 62 | 2021 |
| A multi-vehicle trajectories generator to simulate vehicle-to-vehicle encountering scenarios W Ding, W Wang, D Zhao 2019 International Conference on Robotics and Automation (ICRA), 4255-4261, 2019 | 56* | 2019 |
Henry LamColumbia University在 columbia.edu 的电子邮件经过验证
