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This project aimd at developing a decision support system (DSS) for Integrated Active Traffic Management (IATM) for both freeways/expressways and arterials/collectors. In order to achieve the objectives, the following tasks were performed. The research team first reviewed different traffic detection technologies to understand the output data characteristics and operation mechanisms. After initially checking data availability and roadway network, the Greater Downtown Orlando Metropolitan Area was selected as the study area. In the study area, the research team devoted great effort to collect different data sources to ensure sufficient data coverage on both freeways/expressways and arterials/collectors. The data sources included HERE, NPMRDS (National Performance Management Research Data Set), MVDS (Microwave Vehicle Detection System), AVI (Automatic Vehicle Identification), BlueTOAD, BlueMAC, etc. All data were processed to reflect traffic for the same segment at the same time and evaluated with the consideration of accuracy and availability. Fusion algorithms were developed to improve the data accuracy as well. The appropriate data were used to identify the critical roadways and segments which experienced serious traffic congestion and travel time unreliability. Around 600 miles roadways, with around 1,200 segments in total, were evaluated based on measures reflecting traffic efficiency and reliability. Two critical corridors (i.e., I-4 corridor in Downtown Orlando and SR-417 corridor in East Orlando) were selected for developing the DSS for IATM. By using Aimsun Next, the research team has developed a dynamic traffic …