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Award Abstract #1351512

CAREER: Simulation-Based Optimization Techniques For Urban Transportation Problems

NSF Org: CMMI
Div Of Civil, Mechanical, & Manufact Inn
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Initial Amendment Date: March 1, 2014
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Latest Amendment Date: March 1, 2014
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Award Number: 1351512
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Award Instrument: Standard Grant
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Program Manager: Diwakar Gupta
CMMI Div Of Civil, Mechanical, & Manufact Inn
ENG Directorate For Engineering
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Start Date: September 1, 2014
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End Date: August 31, 2019 (Estimated)
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Awarded Amount to Date: $401,000.00
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Investigator(s): Carolina Osorio osorioc@mit.edu (Principal Investigator)
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Sponsor: Massachusetts Institute of Technology
77 MASSACHUSETTS AVE
Cambridge, MA 02139-4301 (617)253-1000
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NSF Program(s): CIVIL INFRASTRUCTURE SYSTEMS,
SERVICE ENTERPRISE SYSTEMS
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Program Reference Code(s): 028E, 029E, 036E, 039E, 076E, 078E, 1045, 1631, 1787, 8023, 9102
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Program Element Code(s): 1631, 1787

ABSTRACT

The objective of this Faculty Early Career Development (CAREER) Program award is the development of computationally efficient simulation-based optimization techniques for three types of urban transportation problems: (i) dynamic, (ii) large-scale, and (iii) reliable. The techniques enable state-of-the-art urban traffic simulators to address a variety of continuous, nonlinear, constrained and high-dimensional optimization problems. They combine ideas from the fields of metamodel simulation-based optimization, transient finite capacity queueing theory and traffic flow theory. Their performance is evaluated by considering urban traffic management problems for three road networks in the United States, Europe and Asia.

This project will be carried out in collaboration with a transportation agency in the United States. The techniques will support their ongoing planning and operational efforts. Numerous transportation agencies and consultants around the world use these traffic simulation tools to inform their planning and operations decisions. The techniques will enable practitioners to identify transportation strategies that provide both local and network-wide improvements. If successful, these techniques contribute to improve the management of transportation systems, mitigate peak-hour congestion, and thereby reduce its economic and environmental impacts. They also contribute to providing an improved urban mobility experience by identifying traffic management strategies that lead to more reliable transportation services. Enabling the use of microscopic simulators to efficiently identify network design improvements may also lead to substantial savings for infrastructure projects. The ideas and results of this project will be discussed with the main simulation software developers. Through various educational activities, this project will involve, encourage and train underrepresented students in conducting engineering research and problem solving.

 

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