Developing AI-driven Safe Navigation Tool
| 项目名称： | Developing AI-driven Safe Navigation Tool |
| 摘要： | Traffic crashes are a leading cause of death in the United States. The conventional safety evaluation methods incorporate safety modeling to determine the risk scoring of the roadways and provide these risk maps in non-reproducible format. For roadway users, these risk maps are not usable in their daily roadway trips. On the other hand, popular navigation applications such as Google Maps and Apple Maps provide distance-based or travel time-based alternative routes with no real-time risk scoring. There is a need for a real-time navigation system that can provide data-driven decision on the safest path or route. Obtaining data from several historical and real-time data sources, the user interface of the tool or application can provide the safest navigation decision by examining several scorings such as safety, distance, travel time, and overall scoring. Conducting safety prediction by using multiple big data sources, AI-driven algorithms perform better than conventional statistical models. This study aims to conduct a unique contribution by developing a robust, AI-driven, safe navigation tool, which can provide an informed decision of the safest route instead of providing several uninformed decisions offered by the current navigation tools. |
| 状态： | Active |
| 资金： | 349970 |
| 资助组织： | Office of the Assistant Secretary for Research and Technology |
| 项目负责人： | Glenn, Eric Zachary |
| 执行机构： | Texas A&M Transportation Institute (TTI) |
| 开始时间： | 20210815 |
| 预计完成日期： | 20230731 |
| 主题领域： | Data and Information Technology；Highways；Operations and Traffic Management；Safety and Human Factors |
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