Model-Based Business intelligence Support of Transportation System Management and Operations (TSMO)

Focus Area: Traffic Analysis and Management Tools
Submitting On Behalf Of: Other: TRB Traffic Simulation Committee (ACP80)
Urgency: Critical - High Priority
Cost: $250,000 - 499,000
Timeframe: 1 - 2 years
Type of Research: Full Research Project

Date Posted: Aug 11, 2023
Status: Not Funded

Research Description

There has been a strong interest in utilizing business intelligence to support Transportation System Management and Operations (TSMO) strategic, programmatic, and tactical processes with focus on data analytics. However, data analytics by themselves are not sufficient to satisfy the needs of the planning, design, operation, and management of the transportation systems. The recently released Transportation Operations Manual (TOM) was created for use by transportation agencies in developing and maintaining the operational capabilities and strategies to preserve and optimize transportation system performance. The manual incorporates the strategic, programmatic, and tactical levels of TSMO. To achieve the full potential of TOM, there is a need for business intelligence that use different analytical, simulation approaches and tools., combined with machine learning to optimize the decision-making process of different levels of TSMO.

This project will produce a framework, guidance and demonstration on the use of simulation and analytical procedures combined with machine learning to support various TSMO decision processes. The project will use TOM and stakeholder inputs as an important basis for the research. The following are the anticipated tasks of the projects 1) Identify current use of simulation in the analytical procedures in supporting TSMO strategic, tactical, and operational (both off-line and real-time) decisions, and identify opportunities where mobility and response efficiency can be enhanced with simulation integrated analytical process 2) Develop a business intelligence framework for using simulation and analytical procedures and/or machine learning to support the TSMO decisions including the strategies, tactics, and operational processes to deliver accurate and efficient decision making; the assessed performance measures; the required data; the analysis approaches; the required tools; and the required resources and staff. 3) Provide a catalog that map simulation and analytical approaches to various TSMO processes and associated decisions with estimated potential benefits of the use of these approaches based on identified performance measures, 4) Demonstrate the application of simulation and analytical procedures as part of a business intelligence framework to selected case studies. 5) Document the results, findings, and guidance based on the project tasks.

Additional Supporting Information

This proposal was identified by the Traffic Simulation Committee of the Transportation Research Board (ACP80) as a high priority project. This proposal is also supported by Virginia Department of Transportation (VDOT).

Submitted By: Mohammed Hadi; Florida International University; 561-306-3330

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