Integrated Freeway/Arterial Active Traffic Management
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Integrated Freeway/Arterial Active Traffic Management

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    Final Deliverable, April 30, 2017-October 2019
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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 assignment (DTA) simulation platform, involving multi-resolution modeling (MRM) framework. The platform is the largest DTA-based simulation network attempted in the United States. The microscopic simulation models were developed to test IATM control strategies. Based on the developed simulation platform, different IATM control strategies, including Variable Speed Limit (VSL), Queue Warning (QW), Ramp Metering (RM), and their combinations were tested under three different congestion levels on both corridors. Two METANET models were developed to predict traffic conditions. The DSS was developed for the IATM controls by balancing the traffic on both freeways/expressways and arterials/collectors. A total of 420 simulation runs were conducted to evaluate the developed DSS of IATM, and the generic rules of IATM controls were summarized for implementation. The results suggested that the developed DSS could successfully reduce traffic congestion and improve travel time reliability. It is intended that the results of the project would provide a solution to help operators select efficient and effective control strategies to simultaneously improve traffic conditions of freeways/expressways and arterials/collectors.
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