Accelerated Inverse Reinforcement Learning with Randomly Pre-sampled Policies for Autonomous Driving Reward Design. - Long Xin; Shengbo Eben Li; Pin Wang; Wenhan Cao; Bingbing Nie; Ching-Yao Chan; Bo Cheng 003 (ITSC, 2019)

Analysis of Motion Sickness Associated Brain Activity Using fNIRS: A Driving Simulator Study. - Chenyang Zhang 006; Shuguang Li; Yaohua Li; Shengbo Eben Li; Bingbing Nie (IEEE Access, 2020)

Mixed Reinforcement Learning with Additive Stochastic Uncertainty. - Yao Mu 001; Shengbo Eben Li; Chang Liu 002; Qi Sun 004; Bingbing Nie; Bo Cheng 003; Baiyu Peng (CoRR, 2020)

Constructing personalized situation awareness dataset for hazard perception, comprehension, projection, and action of drivers. - Shun Gan; Quan Li; Qingfan Wang; WenTao Chen; Detong Qin; Bingbing Nie (ITSC, 2021)

Decision-Making under On-Ramp merge Scenarios by Distributional Soft Actor-Critic Algorithm. - Yiting Kong; Yang Guan; Jingliang Duan; Shengbo Eben Li; Qi Sun 004; Bingbing Nie (CoRR, 2021)

A GAN based approach for inferring progression trajectories of costal cartilage calcification from cross-sectional data at image level. - Yuan Huang; Sven A. Holcombe; Qing Zhou; Stewart C. Wang; Jisi Tang; Bingbing Nie (Comput. Biol. Medicine, 2022)

Quantifying the Individual Differences of Driver' Risk Perception with Just Four Interpretable Parameters. - Chen Chen 068; Zhiqian Lan; Guojian Zhan; Yao Lyu; Bingbing Nie; Shengbo Eben Li (CoRR, 2022)

Multisource Adaption for Driver Attention Prediction in Arbitrary Driving Scenes. - Shun Gan; Xizhe Pei; Yulong Ge; Qingfan Wang; Shi Shang; Shengbo Eben Li; Bingbing Nie (IEEE Trans. Intell. Transp. Syst., 2022)

Sensitivity of Electrodermal Activity Features for Driver Arousal Measurement in Cognitive Load: The Application in Automated Driving Systems. - Penghui Li; Yibing Li; Yao Yao; Changxu Wu; Bingbing Nie; Shengbo Eben Li (IEEE Trans. Intell. Transp. Syst., 2022)

A Prediction-Uncertainty-Aware Safety Decision-Making Algorithm Towards Injury Risk Minimization Under Safety-Critical Scenarios. - Qingfan Wang; Detong Qin; Gaoyuan Kuang; Ruiyang Li; Bingbing Nie (ITSC, 2023)

STDA: Spatio-Temporal Dual-Encoder Network Incorporating Driver Attention to Predict Driver Behaviors Under Safety-Critical Scenarios. - Dongyang Xu; Yiran Luo; Tianle Lu; Qingfan Wang; Qing Zhou; Bingbing Nie (CoRR, 2024)

Cross-modal knowledge learning with scene text for fine-grained image classification. - Li Xiong; Yingchi Mao; Zicheng Wang; Bingbing Nie; Chang Li (IET Image Process., 2024)

Quantifying the Individual Differences of Drivers' Risk Perception via Potential Damage Risk Model. - Chen Chen 068; Zhiqian Lan; Guojian Zhan; Yao Lyu; Bingbing Nie; Shengbo Eben Li (IEEE Trans. Intell. Transp. Syst., 2024)

Real-Time Reconstruction of Multi-Body Pedestrian Pre-Impact Posture in Collision Accidents From Monocular Images. - Meijun Wang; Yu Meng; Yan Xu; Quan Li; Bingbing Nie (IEEE Trans. Intell. Transp. Syst., 2025)

Risk-Aware Vehicle Trajectory Prediction Under Safety-Critical Scenarios. - Qingfan Wang; Dongyang Xu; Gaoyuan Kuang; Chen Lv; Shengbo Eben Li; Bingbing Nie (IEEE Trans. Intell. Transp. Syst., 2025)

When Do Drivers Maneuver: Experimental Investigation and Inference of Perception-Response Time for Tailored Safety Systems in Intelligent Vehicles. - Detong Qin; Qingfan Wang; Quan Li; Tianle Lu; Chen Chen 068; Hong Wang 014; Bingbing Nie (IEEE Trans. Hum. Mach. Syst., 2025)