Use Analysis, Modeling, and Simulation (AMS) to identify gaps, determine constraints, and invest in the best combination of Integrated Corridor Management (ICM) strategies.
Experience with the AMS framework on the ICM Test Corridor, San Francisco.
- Be prepared to significantly modify the analysis framework and customize macroscopic, mesoscopic, and microscopic models to address different priorities on different corridors. Depending on the scope, complexity, and questions to be answered within a specific corridor, there may be more or less emphasis on each type of network analysis. Currently, there is no single model available that provides visibility into the cascading impacts of various congestion management strategies, much less combinations of strategies, across the entire network, transportation modes, and facility types; thus, an integrated approach is recommend that focuses on interfacing between the three classes of simulation models. In the Test Corridor, one of the primary goals was to measure the impacts of ICM on the performance of alternate routes and alternate transportation modes in the vicinity of high frequency incident sites during medium and high travel demand scenarios. All three classes of simulation modeling were proposed. In addition, researchers discussed applications for parametric simulation, time-of-departure choice, and pivot-point mode shift models.
- Consider the impacts of data quality on model calibration. Although the AMS framework is flexible and allows for the application of different types of models at the Pioneer Sites, limitations in all three locally available software programs (macroscopic, mesoscopic, and microscopic) may present challenges. Use available data. Depending on the availability of data, accuracy of model calibration can be impacted.
The AMS framework used in this study was designed to help decision-makers identify gaps, determine constraints, and invest in the best combination of strategies to improve performance. In addition, AMS provides a long-term capability enabling corridor managers to continually improve implementation strategies based on experience.
Author: Alexiadis, V.
Published By: U.S. Department of Transportation
Prepared by Cambridge Systematics for the U.S. DOT
Source Date: September 2008URL: http://ntl.bts.gov/lib/32000/32300/32303/14440_files/14440.pdf
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Intelligent Transportation Systems > Traveler Information > En Route Information > Wireless
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Intelligent Transportation Systems > Arterial Management > Information Dissemination > Dynamic Message Signs
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