Modeling Naturalistic Driving Environment with High-Resolution Trajectory Data
| 项目名称： | Modeling Naturalistic Driving Environment with High-Resolution Trajectory Data |
| 摘要： | In this project, the team will develop a methodological framework for modeling the high-fidelity naturalistic driving environment (NDE) with high-resolution trajectory data. Different from traditional NDE models that mainly match the moments of macroscopic traffic behaviors, the high-fidelity NDE models will match the distributions of microscopic driving behaviors, which are critical for safety-critical applications such as autonomous vehicle testing and training. The large-scale high-resolution data that is being collected by roadside sensors will be leveraged. The developed NDE models will be implemented at the SAFE-TEST toolbox for the safety assessment of autonomous vehicles at the American Center for Mobility, which will significantly expand the toolbox into the complex urban driving environment. Both the high-resolution data collection system and SAFE-TEST toolbox were developed by the PI research team with previous CCAT and Mcity sponsored projects. |
| 状态： | Active |
| 资金： | 250000 |
| 资助组织： | Office of the Assistant Secretary for Research and Technology |
| 管理组织： | University of Michigan Transportation Research Institute |
| 项目负责人： | Bezzina, Debra<==>Tucker-Thomas, Dawn |
| 执行机构： | University of Michigan Transportation Research Institute<==>University of Michigan, Ann Arbor |
| 主要研究人员： | Feng, Shuo；Liu, Henry |
| 开始时间： | 20220401 |
| 预计完成日期： | 20230331 |
| 主题领域： | Data and Information Technology；Highways；Safety and Human Factors；Vehicles and Equipment |
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