Browsing by Subject "Integrated corridor management"
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Item Improving Traffic Signal Operations for Integrated Corridor Management(Minnesota Department of Transportation, 2013-07) Liu, Henry X.; Hu, HengThe Integrated Corridor Management (ICM) approach has drawn increasingly more attention in recent years because it is believed to be a promising tool to mitigate urban traffic congestion. In this project, a maximum flow based control model was first developed to handle oversaturated traffic conditions at signalized arterials. Based on the arterial control model, an integrated control model was proposed to manage network congestion. Through diversion control, the model aims to fully utilize the available capacity along parallel routes. The impact of the diversion traffic is considered, especially for signalized arterials, so that traffic congestion on the diversion route can be reduced or eliminated by proper adjustment of signal timings. This model does not rely on time-dependent traffic demand as model inputs and it is ready to be implemented at typical parallel traffic corridors where the standard detection system is available. The performance of the proposed model was tested using microscopic traffic simulation in the I-394 and TH 55 corridor in Minneapolis, Minnesota. The results indicate that the proposed model can significantly reduce network congestion.Item Measure of Truck Delay and Reliability at the Corridor Level(Minnesota Department of Transportation, 2018-04) Liao, Chen-FuFreight transportation provides a significant contribution to our nation’s economy. A reliable and accessible freight network enables business in the Twin Cities to be more competitive in the Upper Midwest region. Accurate and reliable freight data on freight activity is essential for freight planning, forecasting and decision making on infrastructure investment. A report entitled “Twin Cities Metropolitan Region Freight Study” published by MnDOT and the Metropolitan Council in 2013, suggested a need to understand where and when trucks are most affected by congestion. A framework for truck data collection and analysis was recommended to better understand the relationships between truck traffic and congestion in rush hours. Building upon our previous study to measure freight mobility and reliability along 38 key freight corridors in the Twin Cities Metropolitan Area (TCMA), this study leveraged our previous effort to implement the performance measures using the National Performance Measurement Research Dataset (NPMRDS) from the USDOT. The researcher team first worked with stakeholders to prioritize a list of key freight corridors with recurring congestion in peak periods in the TCMA. We used 24 months of NPMRDS data to measure travel time reliability and estimate truck delay at the corridor level and to identify system impediments during the peak hours. The objective is to use performance measures for assessing impact of truck congestions and identifying operational bottlenecks or physical constraints. Trucking activity nearby a congested area is examined to analyze traffic pattern and investigate possible causes of recurring congestions.