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."
It is highly recommended that you apply for a course at least 6-8 weeks before the start date to guarantee there will be space available. After that date you may be placed on a waitlist. Courses with low enrollment may be cancelled up to 4 weeks before start date if sufficient enrollments are not met. If you are able to access the online application form, then registration for that particular course is still open.
- 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.
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.
Scholarships are available for graduate students and faculty; see information in Links and Resources below.
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:
- 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
- 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
- Economic Activity Models
- Logistics Choices
- Evaluation of Traffic Predictions
Calibration and Validation
- Estimation of Origin to Destination Flows from Counts
- Estimation of Behavioral Models and Simultaneous Calibration
View 2018 Course Schedule (pdf, subject to change)
Class runs 9:30 am - 5:00 pm every day.
Special events include a reception for course participants and faculty on Monday night and a dinner on Thursday evening. All evening activities are included in tuition.
SENIOR SPECIALIST, TENNESSEE VALLEY AUTHORITY
“The MIT short course far exceeded the experience at other classes. The environment and instructor's skills were excellent.”
ASSISTANT PROFESSOR, UNIVERSITY OF DELAWARE
“In general, the quality level of the instructors made the course. To have five days of lectures from the academics who are advancing the state-of-the-art instead of talking about the state-of-the-practice was extremely beneficial.”
SENIOR SUPPORT ENGINEER, CITILABS
“Positive; a unique opportunity to learn from some of the best minds in my field and discuss ideas with peers.”
ASSISTANT STAFF SCIENTIST, E2MANAGETECH
“Great overview with specificity of model design, confirmation, calibration, and application.”
OWNER, LUCIDATA, INC.
“The instructors were experts in this field, and they obviously had practical experience, which enhanced the lectures, and made for interesting conversation.”
GRADUATE STUDENT, KARLSRUHE INSTITUTE OF TECHNOLOGY
“The lecturers were professional, the amount of work done was high and the course materials were good. Also the atmosphere and discussion were on a high professional level.”
URBAN TRANSPORT ECONOMIST, EUROPEAN INVESTMENT BANK
“Very high quality of lectures. Comprehensive overview of the state-of-the-art in transportation modeling and simulation with a good balance of theory and practical applications.”
GRADUATE STUDENT, ROYAL INSTITUTE OF TECHNOLOGY (KTH)
“Apart from being experts in the field, the lecturers managed to present the different topics in way that was understandable by all participants, taking into consideration the various knowledge background and interests of each participant.”
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. He holds a PhD degree in Transportation Systems from MIT and honorary degrees from the University of the Aegean, the Université Lumiére Lyon, the Royal Institute of Technology (KTH), and the University of Antwerp. His awards include the Lifetime Achievement Award of the International Association for Travel Behavior Research; the Jules Dupuit prize from the World Conference on Transport Research Society (WCTRS); and the Institute of Electrical and Electronics Engineers (IEEE) ITS Society Outstanding Application Award for DynaMIT, a mesoscopic simulator with algorithms for dynamic traffic assignment, traffic predictions, and travel information and guidance. Ben-Akiva has coauthored two books, including the textbook Discrete Choice Analysis, published by MIT Press, and over 200 papers in refereed journals or conference proceedings. He has been a member of over three dozen various scientific committees, advisory boards, and editorial boards. He has worked as a consultant in industries such as transportation, energy, telecommunications, financial services and marketing for a number of private and public organizations, including Hague Consulting Group, RAND Europe, ChoiceStream and Cambridge Systematics, where he was previously a Senior Principal and member of the Board of Directors.
This course takes place on the MIT campus in Cambridge, Massachusetts. We can also offer this course for groups of employees at your location. Please complete the Custom Programs request form for further details.
|Fundamentals: Core concepts, understandings, and tools (30%)||30|
|Latest Developments: Recent advances and future trends (50%)||50|
|Industry Applications: Linking theory and real-world (20%)||20|
|Lecture: Delivery of material in a lecture format (100%)||100|
|Introductory: Appropriate for a general audience (25%)||25|
|Specialized: Assumes experience in practice area or field (50%)||50|
|Advanced: In-depth explorations at the graduate level (25%)||25|