Advanced Project of Transport Systems - MEC

Course category: B - Basic; C - Core Engineering; E - Specialization; P - Complementary.

T - Lectures; TP - Theory and practice; PL - Lab Work; S - Seminar; OT - Tutorial Guidance.

• Learning outcomes of the curricular unit:
  1. To create/expand the capacity of observation, analysis and intervention on Transport Systems.
  2. To create/expand the capacity of positioning and interrelationship skills achieved in other uc's for the identification, definition and implementation of specific solutions, both in terms of design (and optimization), or in terms of the operation of transport systems.
  3. To acquire the technical competences required for the use of concepts, models and advanced equipment to develop projects and solutions for the streamlining and optimization of transport systems as complex engineering systems.
• Syllabus:

  Option A:
  Development of a project in the area of transport systems: design or planning studies, traffic study, demand analysis, traffic assignment model, management model for part or for the overall transport systems, or specific case study, in which the concepts studied in previous courses are implemented at the level of a ‘construction project’.

  Option B:
  Development of models for traffic micro-simulation, for agent-based modeling or system dynamics and use of innovative techniques for optimization and mathematical modeling. Introduction to the concepts of objectoriented programming using Java, Python and other high level programming languages.
  The students must build the modeling/simulation framework of the system in study, must learn to interact with the models and interpret the results and limitations of the models in the light of the concepts acquired previously Several tools may be used, like MatLab, Visum, Vissim, ArcGIS, NLOGIT, Urbansim, MATsim and others

• Demonstration of the syllabus coherence with the curricular unit's objectives

  Since this is a specialization course in which one wish to strengthen the professional skills of students at the level of design studies and advanced studies, the most important task is to consolidate the wide range of knowledge acquired throughout the course and expand them through incorporation of new concepts associated with the engineering of complex systems.
  The best strategy to substantiate this approach is that of autonomy and empowerment of students through the implementation of an engineering project (as a group assignment) with a degree of complexity similar to real situations, which must preferably addressed subjects taught in lectures, but not exclusively.

• Teaching methodologies (including evaluation):
  1. Theoretical lectures: on each set of 2 or 3 lessons a technology and/or mathematical modeling technique is addressed. For example, agent-based modelling, system dynamics, etc. A short overview and modeling framework is presented and the use of these advanced techniques is exploited, making reference to the tools that might be used.
  2. Lab sessions: students identify a project they want to develop (option A or B), they also choose/are driven to the adequate modeling techniques necessary to be applied. After the framework setting, the students execute their project assignment (in groups of 3 or 4 elements) during the remaining Lab sessions, having always support in class, complemented with tutorial assistance out of the classroom.
  3. Final Grade = 20% 1st Assign. (individual) + 20% 2nd Assign. (individual) + 60% Group Assign. (3/4 elements). The minimum score in the individual (T1 + T2) and group (T3) components is 10 values in 20 for each.
• Demonstration of the coherence between the teaching methodologies and the learning outcomes

  The methodologies and teaching strategies used for the assimilation of theoretical competences and objectives are:

  • Prior mandatory reading of specific articles dealing with the themes to be developed in each block of 2/3 theoretical lectures (supplied in the Moodle platform together with the slides);
  • The theoretical sessions on each block are lectured using a collection of PowerPoint slides to which students have previous access. For some issues students might be prompted to present a short essay;
  • Encouraging the reading of additional articles on each topic and the self-study by reading articles in scientific journals or R&D deliverables;
  • Teaching in some of the Lab sessions of pedagogical exercises for exemplification and assimilation of theoretical concepts;
  • Provision of course booklets and theoretical flashcards, exercises and supplementary bibliography on each topic;
  • Possible appraisal of some of the theoretical issues of the course subject during the oral assessment.
  • The evaluation of the theoretical issues of the course is made inside the theoretical chapters of the assignments.

  The methodologies and teaching strategies used for the assimilation of competences and practical objectives are:

  • Incentive for the development of small studies and exploration models using specific technologies (eg, simplified models of system dynamics or agent-based models);
  • Incentive to the implementation of methods for collaborative working that allow the simulation of transdisciplinary relations extended from transports to economics analysis and land use;
  • Development of a group assignment (3 or 4 elements) that must addresses a transportation engineering problem at the level of a ‘consultancy project’ (Option A) or at the level of optimization of complex systems (option B .)
• Main Bibliography
  • Course booklet, flashcards, slides of the course and software protocols.
  • Ennio Cascetta, Transportation Systems Analysis. Models and Applications. Second Edition, Springer.
  • Ortúzar JD & LG Willumsen, Modelling Transport, 4th Edition, Wiley
  • K. Button, Transport Economics, 3rd Edition, Edward Eldar.
  • Dexter M., 2008, Eclipse and Java: Introducing Persistence. Companion Tutorial Document, Licensed under the Educational Community License version 1.0. (webbook)
  • J. Vidal, 2009, Fundamentals of multiagent Systems with NetLogo Examples, Copyright 2007 Joseph M. Vidal. All rights reserved (web book).
  • Manuals and notes of support of GIS software ArcGIS
  • Manuals and notes of support from the software or Visum Cube.
  • Manuals and software Limdep NLogit
  • Manuals MatSim software, UrbanSim, MatLab, etc..
  • Articles in international scientific journals describing the use of IT tools in the development of optimization procedures in the field of transportation systems.