详情

Multisource Data Fusion for Real-Time and Accurate Traffic Incident Detection via Predictive Analytics

项目名称：	Multisource Data Fusion for Real-Time and Accurate Traffic Incident Detection via Predictive Analytics
摘要：	This research will investigate how data from the various traffic data sources that Massachusetts Department of Transportation (MassDOT) owns or has access to can be merged for accurate, real-time traffic incident detection, to improve travel time reliability. It will assess the current traffic incident detection methods employed by MassDOT and develop new tools for improved traffic incident detection based on available traffic data. The research will address the fusion of information from multiple sources of different temporal and spatial scales such as traffic data collected from loop detectors; information from the MassDOT Real Time Traffic Management (RTTM) system; and information available through third-party vendors (e.g., Waze, Google, INRIX). The fusion of these sources will be accomplished through evaluating the reliability of the various data sources and deploying advanced data analytical methods such as deep neural networks.
状态：	Active
资金：	150000
资助组织：	Federal Highway Administration
项目负责人：	Flanary, Michael
执行机构：	University of Massachusetts Lowell
开始时间：	20210413
预计完成日期：	20221231
主题领域：	Data and Information Technology；Highways；Operations and Traffic Management