Physical Human Driver Interaction - Honda Research Institute USA

Physical Human Driver Interaction

Physical Human Driver Interaction

We compute various musculoskeletal indicators of human performance when the driver is operating a vehicle under normal and emergency maneuvering.

The physical interaction between the driver and vehicle system is important in  the design of effective driver assist and occupant packaging systems.  In this study, we compute various musculoskeletal indicators of human performance when the driver is operating a vehicle under normal and emergency maneuvering.  Toward this goal, we have developed a full-body musculoskeletal model in the OpenSim musculoskeletal modeling platform.  The human drivers are motion captured using an optical motion capture system.    The captured motion is applied to subject specific models of each driver to compute various quantities such as joint torque due to gravitational effects, total kinetic energy,  and metabolic energy consumption.

Publications

Findings of the Association for Computational Linguistics: ACL 2025. 2025
Lingjun Zhao, Mingyang Xie, Paola Cascante-Bonilla, Hal Daumé III, Kwonjoon Lee
Findings of the Association for Computational Linguistics: ACL 2025. 2025
Huaizhi Qu, Xinyu Zhao, Jie Peng, Kwonjoon Lee, Behzad Dariush, Tianlong Chen
International Conference on Machine Learning (ICML), 2025 [Spotlight, top 2.6% submittions] 2025
Chunhui Zhang, Zhongyu Ouyang, Kwonjoon Lee, Nakul Agarwal, Sean Dae Houlihan, Soroush Vosoughi, Shao-Yuan Lo
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025. 2025
Haoqiang Kang, Enna Sachdeva, Piyush Gupta, Sangjae Bae, Kwonjoon Lee
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025 [Highlight, top 3.7% submittions] 2025
Bardia Safaei, Faizan Siddiqui, Jiacong Xu, Vishal M. Patel, Shao-Yuan Lo
Robotics Science and Systems (RSS), 2025 2025
Sirui Chen, Sergio Francisco Aguilera Marinovic, Soshi Iba, Rana Soltani Zarrin
International Journal of Computer Vision (IJCV) [IF=11.6] 2025
Yuxiang Guo, Faizan Siddiqui, Yang Zhao, Rama Chellappa, Shao-Yuan Lo
RSS 2025 - Workshop on Learned Robot Representations 2025
Fan Yang, Sergio Francisco Aguilera Marinovic, Soshi Iba, Rana Soltani Zarrin, Dmitry Berenson
CVPRW 2025 2025
Zhihao Zhao, Reza Ghoddoosian, Isht Dwivedi, Nakul Agarwal, Behzad Dariush
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025 [Highlight, top 3.7% submittions] 2025
Jiacong Xu, Shao-Yuan Lo, Bardia Safaei, Vishal M. Patel, Isht Dwivedi
Robotics Science and Systems (RSS) 2025 - Workshop on Out-of-Distribution Generalization in Robotics 2025
Zifan Zhao, Siddhant Haldar, Jinda Cui, Lerrel Pinto,
IEEE International Conference on Learning Representations (ICRA), 2025. 2025
Piyush Gupta, David Isele, Enna Sachdeva, Pin-Hao Huang, Behzad Dariush, Kwonjoon Lee, Sangjae Bae
Physical Review Letters 134, 183603 (2025) 2025
Hanfeng Wang, Shuang Wu, Kurt Jacobs, Yuqin Duan, Dirk R Englund, Matthew E Trusheim
ICRA 2025 2025
David Isele, Alexandre Miranda A˜non, Faizan M. Tariq, Goro Yeh, Avinash Singh, and Sangjae Bae
IEEE International Conference on Robotics and Automation (ICRA), 2025, 2025
Abhinav Kumar, Thomas Power, Fan Yang, Sergio Aguilera Marinovic, Soshi Iba, Rana Soltani Zarrin, Dmitry Berenson
ICRA 2025 2025
Max Muchen Sun, Peter Trautman, and Todd Murphey
NAFEMS World Congress; 2025 2025
Ali Nassiri, Phillip Aquino, Allen Sheldon, Sogol Lotfi, Duane Detwiler
International Conference on Learning Representations (ICLR), 2025 2025
Hongxin Zhang, Zeyuan Wang, Qiushi Lyu, Zheyuan Zhang, Sunli Chen, Tianmin Shu, Behzad Dariush, Kwonjoon Lee, Yilun Du, Chuang Gan
Ohio State Materials and Manufacturing Conference 2025
Phillip Aquino
International Conference on Acoustics, Speech and Signal Processing 2025
Abinay Reddy Naini, Zhaobo Zheng, Teruhisa Misu, Kumar Akash