Collaborative Research Project to coordinate the data from the CRASH Predictive Analytics program between TDOT and TDOSHS
| 项目名称： | Collaborative Research Project to coordinate the data from the CRASH Predictive Analytics program between TDOT and TDOSHS |
| 摘要： | The ultimate goal of the proposed work is to deploy a predictive analytics tool that will enhance the current CRASH Predictive Analytics application for highway safety patrol vehicles deployment. Towards this goal, the objectives of this research are to (i) identify the best practices for data storage, integration, and maintenance infrastructure for predictive modeling, (ii) develop state-of-the-art machine learning algorithms for predicting the risk of highway incidents, and (iii) collaborate with TDOT and THP to identify best practices for model integration with existing programs. The following are expected outcomes of this research project: � the ability to forecast the varying categories of incidents across space and time and allocate emergency response resources accordingly. � Implementing the algorithm with existing operational tools and applications � New innovation in predictive analytics algorithms to reduce response time to incidents |
| 状态： | Active |
| 资金： | 174,998.00 |
| 资助组织： | Federal Highway Administration |
| 管理组织： | Tennessee Department of Transportation |
| 项目负责人： | Freeze, Brad |
| 执行机构： | Vanderbilt University |
| 主要研究人员： | Baroud, Hiba |
| 开始时间： | 20181201 |
| 预计完成日期： | 20201130 |
| 实际结束时间： | 0 |
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