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MIT Professional Education

Transportation Networks and SMART Mobility: Methods and Solutions

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Next dates

Aug 5—9
5 days
Cambridge, Massachusetts, United States
USD 3600
USD 720 per day


Modeling and simulation methods are essential elements in the design and operation of transportation systems. Congestion problems in cities worldwide have prompted, at all levels of government and industry, a proliferation of interest in Intelligent Transportation Systems (ITS) that include advanced supply and demand management techniques. Such techniques include real-time traffic control measures and real-time traveler information and guidance systems whose purpose is to assist travelers in making departure time, mode, and route choice decisions. Transportation researchers have developed models and simulators for use in the planning, design, and operations of such systems. This course draws heavily on the results of recent research and is sponsored by the Intelligent Transportation Systems Laboratory of the Massachusetts Institute of Technology.

The course studies theories and applications of transportation network demand and supply models and simulation techniques. It provides an in-depth study of the world's most sophisticated traffic simulation models, demand modeling methods, and related analytical techniques, including discrete choice models, and their application to travel choices and driving behavior; origin-destination estimation; prediction of traffic congestion; traffic flow models and simulation methods (microscopic, mesoscopic, and macroscopic); and alternative dynamic traffic assignment methods.

This course was previously titled "Modeling and Simulation of Transportation Networks."


  • Understand transportation network demand and supply models.
  • Distinguish among alternative approaches to dynamic traffic assignment and traffic simulation.
  • Assess the advantages and disadvantages of alternative network modeling and simulation methods.


The course consists of a series of lectures, including software demonstrations and case studies that develop the concepts and techniques.

The following lecture topics may be addressed as part of the course:

Traffic Performance

  • Modeling and Simulation Approaches
  • Macroscopic Traffic Models and Introduction to Traffic Simulation
  • Microscopic and Mesoscopic Traffic Simulation
  • Static and Dynamic Network Supply Models

Demand and User Behavior

  • Overview of Discrete Choice Analysis
  • Route and Time-of-Travel Choice
  • Activity-Based Models
  • Integrated Land Use and Transportation Models

Traffic Assignment

  • Framework for Demand/Supply Interactions
  • Equilibrium and Day-to-Day Dynamics
  • Testing Optimization Algorithms
  • Pricing and Travel Time Reliability

Public Transportation Models

  • Framework and Low Frequency Services
  • High Frequency Services

Freight Models

  • Economic Activity Models
  • Logistics Choices

Real-Time Systems

  • Evaluation of Traffic Predictions

Calibration and Validation

  • Estimation of Origin to Destination Flows from Counts
  • Estimation of Behavioral Models and Simultaneous Calibration

Who should attend

This program is intended for individuals interested in theory, research, and practice and includes analysts, engineers, managers, and planners, as well as industry, government, and academics who seek to understand, analyze, and predict performance of transportation systems. Participants with backgrounds in diverse areas such as traffic engineering, systems engineering, transportation planning, operations management, operations research, and control systems are welcome.


Moshe Ben-Akiva is the Edmund K. Turner Professor of Civil and Environmental Engineering at the Massachusetts Institute of Technology (MIT), and Director of the MIT Intelligent Transportation Systems (ITS) Lab, and Principal Investigator at the Singapore-MIT Alliance for Research and Technology. ...
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