Presenter: Carlos Lima Azevedo is an Associate Professor at the Technical University of Denmark (DTU) and a Research Affiliate of the ITS Lab at the Massachusetts Institute of Technology (MIT). Prior to join DTU, he held the position of Research Scientist and Executive Director of the Transportation Education Committee at MIT, Postdoc at the Singapore-MIT Alliance for Research and Technology and Research Scholar at the Portuguese National Laboratory for Civil Engineering. He has a PhD (2014), MSc (2008), 5y-BSc in Structural Engineering (2004) all from U. Lisbon. He is expert in development of new models and simulation techniques for smart mobility design and assessment. Previous research includes the development and application of large-scale agent-based urban simulation, its application for the design and evaluation of shared automated vehicles on-demand, the development of personalized real-time incentive systems, individual behavior experiments and preferences modelling towards new mobility solutions, methods for the calibration and validation of simulation tools and innovative road safety assessment models without accident data.

Abstract of Presentation: Tradable mobility credit (TMC) schemes are an approach to travel demand management that have received significant attention in the transportation domain in recent years as a promising means to mitigate the adverse environmental, economic and social effects of urban traffic congestion. In TMC schemes, a regulator provides an initial endowment of mobility credits (or tokens) to all potential travelers. In order to use the transportation system, travelers need to spend a certain amount of tokens (tariff) that could vary with their choice of mode, route, departure time etc. The tokens can be bought and sold in a market that is managed and operated by a regulator at a price dynamically determined by the demand and supply of tokens. In this lecture, we will go over some of the key concepts of TMC and briefly discuss a theoretical study on the efficiency and effectiveness of area-based TMC using the trip-based Macroscopic Fundamental Diagram model for the morning commute problem.