Transportation Networks and Smart Mobility

Overview

What you will study

The Transportation Networks and Smart Mobility course offered by Massachusetts Institute of Technology (MIT) presents theory of transportation modelling and simulation techniques, with a focus on Smart Mobility, AI and ML solutions and real-world applications. It provides an in-depth study of the most sophisticated traffic simulation models, demand modeling methods, and related discrete choice, machine learning analytical techniques. Some of the topics include: modeling and simulation approaches for future mobility; discrete choice models and their application to travel choices and driving behavior; predicting traffic congestion; traffic flow models and simulation methods (microscopic, mesoscopic, and macroscopic); automated and connective vehicles in mixed traffic; alternative dynamic traffic assignment methods; and calibration of large scale simulation systems. In addition, the course covers recent developments in modelling, simulation, operations of smart mobility services, and machine learning applications in transportation. The course also includes case studies to elucidate the concepts and showcase the potential applications.

By taking this course, you will:

• 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.