ITS is an important new component in surface transportation as introduced over the last several decades.

Under ITS, one of the research projects aims to conceive, organize and simulate the implementation of new smart transportation services and modes, such as congestion and parking pricing, incident detection and speed adaptation systems, car-sharing and one-way car rentals, etc.

The second, and intimately related, ITS project aims to develop several types of information technologies that could be deployed within the Portuguese transportation system in order to improve mobility services, provide new information for infrastructure and service design, and allow users to make better-informed decisions about their mobility via seamless integration of the necessary information (including prices and externalities) and convenient delivery of this information when and where it is needed.

Two more projects were launched in 2009 to address protocols for information-gathering to support intelligent transportation systems (MISC) and the creation of infrastructure to support dynamic vehicle attribute adjustments for greater safety (SAVED).

In April 2010, MIT Portugal ITS researchers at IST and at MIT were among the collaborators awarded a US$3.5M Bus Rapid Transit Centre of Excellence from the Volvo Research Foundation.

Project 1: Smart Combination of passenger transport modes and services in Urban areas for maximum System Sustainability and Efficiency (SCUSSE)
(November 2007 – June 2010)

Description: The project aims to conceive, organize and simulate the implementation of new smart transport modes and services to optimize integration with lifestyles, and also with already existing individual and collective transport. For this, three levels of decision (strategic, tactic and operational) will be approached covering the institutional design required for the regulatory environment, network planning focusing on productive efficiency as well as efficiency in consumption, and enforcement and performance monitoring at the operational level. Performance assessment at the strategic level will also be developed.

Objectives: The project is organized around the following specific objectives:

  • Understanding factors of preference and repulsion on choice of travel mode and developing proto-solutions for multiple market segments
  • Conceptualizing and evaluating innovative services, modes, and congestion management initiatives (including pricing) with the aim of better fit to user requirements and the potential for greater sustainability and efficiency
  • Developing incentives, marketing, acceptability, and business models for the innovative services and modes
  • Analyzing the urban activity space and the implications of the innovative services
  • Designing and simulating the new services, modes, and congestion management initiatives (including pricing)
  • Analyzing the implications of new services and pricing paradigms on governance structures
  • Assessing institutional, economic, and financial feasibility of new solutions found as well as their impact at tactical and strategic levels
  • Developing a handbook on smart combination of passenger transport modes and services in urban areas.


  • Development and testing of several concepts of innovative intermediate transport modes and services, aimed at an improved fit with evolving lifestyles
  • Assessment of the reception of these new modes and services, together with the implementation of parking enforcement policies and dynamic congestion charging schemes, using a web-based stated preference survey
  • Simulation of some of these intermediate modes and services (still underway) shows a strong potential for achieving a range of “double second-best” solutions which promote substantial gains of social welfare, with rather low penalty for the traveler, thus making them more easily acceptable
  • Development of business models for these solutions

Industry Involvement: Information will be obtained from a variety of sources including authorities and current operators of innovative services and mobility solutions in Portugal and elsewhere.

PT Faculty: João Abreu e Silva (IST), Rosário Macário (IST), José Viegas (IST), Álvaro Seco (Coimbra)

MIT Faculty: Moshe Ben-Akiva, William Mitchell, Joseph Sussman

Student Researchers on this Project: Rafaela Arriaga (IST), Carlos Azevedo (IST), Diana Carvalho (IST), Travis P Dunn (MIT), Andres Sevtsuk (MIT)

Working Papers:

pdf Happiness and Travel Behavior Modification by Maya Abou-Zeid & Moshe Ben-Akiva

pdf Stated Preference Survey for New Smart Transport Modes and Services by By Lang Yang, Charisma F Choudhury, Moshe Ben-Akiva, João Abreu e Silva & Diana Carvalho

pdf Strategy in Surface Transportation by Travis P. Dunn & Joseph Sussman

pdf  Role of Technology in Surface Transportation Strategy Development


pdf Alternative Strategy Development Frameworks for Surface Transportation Systems , poster, Travis Dunn, MIT Portugal Program’s 1st Annual Conference, July 7, 2009.

pdf Fighting Parasite Circulation Through Parking Space Reservations , poster, Diana Carvalho, MIT Portugal Program’s 1st Annual Conference, July 7, 2009.

pdf Innovation in Transport Modes and Services in Urban Areas and Their Potential to Fight Congestion by José Manuel Viegas, João de Abreu e Silva, Rafaela Arriaga

pdf Location Choices, Accessibility & City Form , poster, Andres Sevtsuk, MIT Portugal Program’s 1st Annual Conference, July 7, 2009.

pdf Long-Term Drivers of Cultural Shifts Within Generations in Favor of Sustainable Mobility , poster, Rafaela Arriaga, MIT Portugal Program’s 1st Annual Conference, July 7, 2009.

pdf Safety Criteria for the Management of Variable Speed Limits , poster, Carlos Lima Azevedo, MIT Portugal Program’s 1st Annual Conference, July 7, 2009.

pdf Smart Combination of passenger transport modes and services in Urban areas for maximum System Sustainability and Efficiency (SCUSSE) , poster, MIT Portugal Program’s 1st Annual Conference, July 7, 2009.

pdf SCUSSE Project Overview by José Manuel Viegas

pdf A Structured Simulation-based Methodology for Carpooling Viability Assessment by Gonçalo Correia & José Manuel Viegas

pdf Transportation Systems Research 2008 SCUSSE

Project 2: Data Fusion for Mobility Consumers, Providers, and Planners (CityMotion)
December 2007 – December 2010

Description: This project focuses on the development of a knowledge infrastructure, computational models, and user applications that allow access to real-time information about the state of transportation-related resources as well as predictions regarding their future state. A pilot service that exemplifies the usage potential of available data will be provided to citizens for making public transportation more efficient and pleasant to use and to policy-makers as a decision-support tool.

Objectives: The project is organized around the following specific objectives:

  • Acquiring and parsing data that describe the state of transportation-related resources (e.g. bus and train locations, cell phone traces, road sensors, GPS tracking, weather, emergency events, and census data)
  • Developing a data fusion engine that combines the data to extract from them additional information including predictions
  • Developing a model-based data fusion engine (with simulation capabilities) that models a particular transportation network along with the behaviour of travellers within it
  • Developing a web-based service that enables different applications to access the data collected
  • Developing an interactive multi-modal, multi-criteria route-planning application that would exemplify the capabilities of the data fusion engine and provide support to the travelling decisions of the public
  • Developing a geographical modelling and visualization module of city dynamics for use by planners and service providers


  • The first Portuguese project that combines a mixture of data from several (often competing) sources. For the first time in Portugal, the project is advancing “reality mining” from heterogeneous (and differently owned) data sources.
  • CityMotion has spawned a second phase proposal for a large national project in the mobility area (TICE.mobilidade, QREN funding program) involving a large number of private companies and the universities of Coimbra, Porto and Minho.
  • Prototype of the Portugal Brisa A5 motorway online laboratory is being developed. Initial testing of various online-calibration algorithms within DynaMIT were carried out and preliminary results on the quality of traffic estimation and prediction, as well as computational performance were obtained and analyzed. Furthermore, a parallel calibration strategy, which leads to dramatic reductions in algorithm running time, was designed and implemented.


  • Innovative visualizations of mobility patterns for Lisbon
  • Development of density matrixes, origin-destination matrixes and clustering results involving different mobility modalities. Study of relations between mobility and the urban space.
  • Adaptation of DynaMIT to Brisa’s A5 motorway, to develop a “short-term” traffic prediction tool

Industry Involvement: TMN, Frotcom, CARRIS, Geotaxis, CML, CMP, Metro Porto, STCP, Brisa.

PT Faculty: João Abreu e Silva (IST), Carlos Lisboa Bento (Coimbra), Francisco C. Pereira (Coimbra), Teresa Galvão (Porto)

MIT Faculty: Moshe Ben-Akiva, Assaf Biderman, Carlo Ratti, P. Christopher Zegras

Student Researchers on this Project: Tiago Fernandes (Coimbra), Rui Gomes (Porto), Jorge Lopes (IST)

Working Papers:

Data Fusion for Real-Time Traffic Management by Enyang Huang, Constantinos Antoniou, Moshe Ben-Akiva (currently in review)

pdf Multi-Sensor Data Fusion on Intelligent Transport Systems by Marco Veloso, Carlos Bento, and Francisco Câmara Pereira

pdf State of the Practice Overview of Transportation Data Fusion by Andrew Amey, Liang Liu, Francisco Pereira, Christopher Zegras, Marco Veloso, Carlos Bento, Assaf Biderman


pdf CityMotion Overview by Carlos Bento

pdf Data Fusion for TDM: State of the Practice & Prospects by Christopher Zegras, Francisco Pereira, Andrew Amey, Marco Veloso, Liang Liu, Carlos Bento, Assaf Biderman

pdf Dynamic Vehicle Routing for Demand Responsive Transportation , poster, Rui Gomes, MIT Portugal Program’s 1st Annual Conference, July 7, 2009.

pdf Perceiving City Dynamics Resorting to Data Fusion Mechanisms , poster, Marco Veloso, MIT Portugal Program’s 1st Annual Conference, July 7, 2009.

pdf Transportation Systems Research 2008 CityMotion



Project 3: MISC - Massive Information Scavenging with Intelligent Transportation Systems July 2009 – June 2012

MISC studies methods to allow efficient and reliable information-gathering – from diverse, heterogeneous, and mobile users – to support the design and operation of intelligent transportation systems.  The particular focus is on network coding for robust and resilient routing in wireless settings.

Achievements to date include:

  • Examination of network coding with TCP for efficient/reliable transmission
  • Showing, analytically and experimentally, that TCP with network coding achieves a higher transmission rate than TCP alone.
  • Designing a secure multi-hop protocol, called algebraic watchdog, in a mobile wireless network.
  • Finalizing the analysis for multi-hop, multi-source network.



Project 4:SAVED: System for Adapting Vehicle dynamic parameters to the driving Environment and Driver capabilities
September 2009 – August 2012

SAVED seeks to employ innovative methods to provide a lasting significant improvement to road safety by developing the concept and specifications for a system that adjusts the road vehicle’s dynamic attributes to the driver’s state (permanent and short-term limitations) and driving circumstances.

Work is now proceeding with the identification of possible contributions from infrastructure embedded sensors to enrich the information about driving hazards related to the infrastructure condition and to traffic flows, and the enhancement of the model considering other driving limitations and taking into account vehicles defects.

Initial accomplishments:

  • Development of an agent-based simulation model that tests the consequences of the proportion of “safe” drivers (i.e. drivers who adequately adjust their driving style to the driving conditions) in relation to “hazardous” drivers (i.e. drivers who have poor sightseeing, tiredness and speeding predisposition).
  • Model representation of a hypothetical vehicle technology to convert hazardous drivers to safer drivers. For example, the vehicle could automatically limit the driver’s maximum speed.