Here we give the published papers about the Autonomous driving of DRL lab from Insitute of Automation, Chinese Academy of Sciences. The leader of DRL lab is Prof. Dongbin Zhao.
(1). Yaran Chen, Dongbin Zhao*, Le Lv, Qichao Zhang, "Multi-task learning for dangerous object detection in autonomous driving", Information Sciences, vol. 432, pp. 559-571, 2018. DOI: 10.1016/j.ins.2017.08.035 paper
(2). Dongbin Zhao*, Yaran Chen, Le Lv, “Deep reinforcement learning with visual attention for vehicle classification,” IEEE Transactions on Cognitive and Developmental Systems, vol.9,issue:4, pp.356-367,2017,DOI 10.1109/TCDS.2016.2614675. paper
(3). Yaran Chen, Dongbin Zhao, Haoran Li, Dong Li and Ping Guo, "A temporal-based deep learning method for multiple objects detection in autonomous driving"，International Joint Conference on Neural Networks，2018.
(4). Yaran Chen, Dongbin Zhao, “Multi-task learning with Cartesian product-based multi-objective combination for dangerous object detection”, F. Cong et al. (Eds.): ISNN 2017, Part I, LNCS 10261, pp. 28–35, 2017. paper
(5). Yaran Chen, Dongbin Zhao, Le Lv, Chengdong Li, “A visual attention based convolutional neural network for image classification,” Proceedings of the 12th World Congress on Intelligent Control and Automation (WCICA 2016), Guilin, China, July 12-15, 2016, pp.764-769. (Steve and Rosalind Hsia Best Biomedical Paper Award List).
(6). Haoran Li, Xiaolei Zhou, Yaran Chen, Dongbin Zhao, “Comparison of 3D object detection based on LiDAR point cloud,” IEEE Data Driven Control and Learning Systems Conference (DDCLS), Dali, China, May 25-27, 2019.
(1). Junjie Wang, Qichao Zhang, Dongbin Zhao and Yaran Chen, “Lane change decision-making through deep reinforcement learning with rule-based constraints,” The International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, July 14 -19, 2019.
(1). Dong Li, Dongbin Zhao, Qichao Zhang, Yaran Chen, Reinforcement learning and deep learning based lateral control for autonomous driving, IEEE Computational Intelligence Magazine, vol. 14, no. 2, pp. 83 – 98, 2019. (SCI Q2, IF 5.24/2019)
(2). Dong Li, Dongbin Zhao, Qichao Zhang, “Reinforcement learning based lane change decision-making with imaginary sampling,” Proceedings of IEEE Symposium Series on Computational Intelligence (SSCI) – Symposium on Adaptive Dynamic Programming and Reinforcement Learning, Xiamen, China, Dec.6 - 9, 2019.
(3). Qichao Zhang, Rui Luo, Dongbin Zhao, Chaomin Luo and Dianwei Qian, “Model-free reinforcement learning based lateral control for lane keeping,” The International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, July 14 -19, 2019.
(4). Yuanheng Zhu, Dongbin Zhao, “Driving control with deep and reinforcement learning in the open racing car simulator,” L. Cheng et al. (Eds.): ICONIP 2018, LNCS 11303, pp. 326–334, 2018. Paper.
(5).YinFeng Gao, Qichao Zhang, Yu Wang, Dongbin Zhao, Dawei Ding, “Comparison of control methods based on imitation learning for autonomous driving,” International Conference on Intelligent Control and Information Processing (ICICIP), Marrakesh, Morocco, Dec. 14-19, 2019.
(1).Yuanheng Zhu, Dongbin Zhao, Haibo He*, Synthesis of cooperative adaptive cruise control with feedforward strategies," IEEE Transactions on Vehicular Technology, vol. 69, no. 4, pp. 3615–3627, 2019. DOI: 10.1109/TVT.2020.2974932. (SCI Q1, IF 6.41/2019).
(2). Bin Wang*, Dongbin Zhao, Jin Cheng, “Adaptive cruise control via adaptive dynamic programming with experience replay”, Soft Computing, vol. 23, no. 12, pp. 4131–4144, 2019. DOI: 10.1007/s00500-018-3063-7. (SCI Q2, IF 3.14/2019).
(3). Dongbin Zhao, Zhongpu Xia, Qichao Zhang*, “Model-free optimal control based intelligent cruise control with hardware-in-the-loop demonstration,” IEEE Computational Intelligence Magazine, vol. 12, no. 2, pp. 56–69, 2017. 10.1109/MCI.2017.2670380.
(4). Bin Wang, Dongbin Zhao, Chengdong Li, Yujie Dai, “Design and implementation of an adaptive cruise control system based on supervised actor-critic learning,” The 5th International Conference on Information Science and Technology (ICIST 2015), Hunan, China, April 24–26, 2015, pp. 243-248.
(5). Dongbin Zhao, Zhaohui Hu, Zhongpu Xia*, Cesare Alippi, Ding Wang, “Full range adaptive cruise control based on supervised adaptive dynamic programming,” Neurocomputing, vol.125, pp. 57-67, 2014.
(6). Dongbin Zhao*, Bin Wang, Derong Liu, “A supervised actor-critic approach for adaptive cruise control,” Soft Computing, Vol. 17, No. 11, pp 2089-2099, 2013. (7). Dongbin Zhao, Zhongpu Xia, An adaptive cruise control system for different driving habits, 2013 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI 2013), Dongguan, Guangdong, China, July 28-30, 2013, pp. 159-164.
(8). Dongbin Zhao, Zhaohui Hu. Supervised adaptive dynamic programming based adaptive cruise control. Proceedings of IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning (ADPRL 2011), Paris, France, Apr. 11-15, 2011, pp. 318-323.
(9). Zhaohui Hu, Dongbin Zhao*, “Adaptive cruise control based on reinforcement leaning with shaping rewards,” Journal of Advanced Computational Intelligence & Intelligent Informatics, vol. 15, no.3, pp. 351-356, 2011.
(1). Li Dong, Zhao Dongbin and Zhang Qichao, “An autonomous driving experience platform with learning-based functions,” Proceedings of IEEE Symposium Series on Computational Intelligence (SSCI) – Symposium on Adaptive Dynamic Programming and Reinforcement Learning, Bengaluru, India, Nov.18 - 21, 2018, pp. 1174-1179.