摘要: |
The goal of the proposed project is to systematically extract traffic safety information from multiple complex sources of flood monitoring such as remote sensing technologies, flow gages, and weather stations, which can support informed planning for transportation safety against flooding in future smart cities. Flooding poses a significant hazard to the moving vehicles and causes traffic disruption by placing water flow in the transportation network, resulting in sweeping vehicles away, injuries and loss of life of passengers. While different methods to continuously monitor flooding are available in the field of flood management, the collected data is too complex to directly offer relevant information for transportation safety. As a result, the application of flood monitoring in Connected Vehicles has been limited to weather information, which does not directly relate to transportation safety. To fill this gap, the research team will employ Big Data Analytics to extract transportation safety information from multiple monitoring sources, each of which continuously collect data in a fine temporal scale. This approach, as an example application, will provide a decision support system to identify and prioritize candidate locations for future installation of roadside units. To facilitate visualization of their findings for an enhanced technology transfer, the team will define metrics following the risk assessment of flooding in transportation network. Consequently, the team will develop regional “heat maps” to visualize such metrics across large geographic scales, including communities that are disadvantaged. |