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TransModeler has recently been the microsimulation platform of
choice behind two significant research projects at Vanderbilt
University and the University of Florida.
At Vanderbilt, researchers harnessed TransModeler to push the boundaries of state-of-the-art corridor management. The I-24 SMART Corridor project, a pioneering initiative by the Tennessee Department of Transportation (TDOT), marks the nation’s first implementation of artificial intelligence (AI)-driven Integrated Corridor Management (ICM) strategies. The SMART Corridor is equipped for ramp metering, variable speed limit (VSL) control, ITS, and other ICM solutions, deploying real-time strategies to enhance safety, operations, and reliability.
Employing AI and machine learning techniques, the research team at Vanderbilt used high-performance microsimulation of the corridor in TransModeler to train an advanced VSL algorithm. The algorithm, developed by the Vanderbilt team, was trained to detect bottlenecks and test strategies to mitigate their occurrence, severity, and duration.
The I-24 SMART Corridor project is evidence of the transformative power of combining AI with fast, scalable, high-fidelity traffic simulation. With the computational performance and behavioral realism that TransModeler can provide, researchers can deliver smart transportation solutions with unparalleled efficiency.
In a collaborative effort, the University of Florida Transportation Institute, alongside HDR Engineering, the Texas A&M Transportation Institute, and the University of Kansas, used TransModeler for a pivotal study under the National Cooperative Highway Research Program. This research focused on developing an enhanced methodology to evaluate the operating performance of weaving sections on arterials.
TransModeler was selected as the microsimulation platform for “its flexibility in the calibration of driver behavior parameters and the provision of a metric to record the number of failed weaving maneuvers.” With TransModeler, the project team generated data through simulations of more than 1,000 scenarios at five sites generating over 413,000 vehicle trajectories. The study provides important insights into the speed drops and delays caused by vehicle weaving, especially in shorter weaving sections.
The findings of the project are detailed in NCHRP Research Report 1094, which is available for download here.
These projects highlight the impact that TransModeler can have in advancing traffic and transportation research. The exceptional performance and digital twin realism that TransModeler provides can unlock enormous potential, accelerating the development of innovative traffic management solutions and advanced traffic flow analysis methodologies and data analytics. The fusion of simulation and AI is set to significantly enhance the safety, efficiency, and effectiveness of transportation systems.
For more information on TransModeler, please contact Daniel Morgan, Vice President at Caliper, daniel@caliper.com.
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