Transportation Demand Modeling
City Planning and Transportation
3rd Cycle Studies
Lectures combining theoretical explanations with exercise solving and with conceptual and real-case discussions.
Provide students with a deep knowledge and with advanced R&D skills and competences on the subject of transport demand modeling.
Linear regression models. Estimation methods. Assumption violations: non-linearity; heteroscedasticity; serial correlation of errors; non-normal distribution of errors; multicollinearity. Modeling strategies.
Time series models. Smoothing methods. ARIMA models. Non-linear models.
Panel data models. Fixed-effect and random-effect models.
Generalized regression models (counts of events). Poisson regression model. Negative binomial regression model. Zero-inflated Poisson regression model.
Ordered response and discrete choice models. Probit and logit models.
System dynamics models. Model ingredients – stocks, transitions, loops, and boundary. Construction of a system dynamics model with the Vensim software.
Multi-agent models. Model ingredients – environment, agents, objects, space-time interactions, and boundary.
Construction of a multi-agent model with the Anylogic software.
Anabela Salgueiro Narciso Ribeiro
Home assignments and written final exam: 100.0%
Axelrod R, The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration, Princeton
Ben Akiva M, Lerman S, Discrete Choice Analysis: Theory and Application to Travel Demand, MIT Press, 1985
Epstein JM, Axtell RL, Growing Artificial Societies: Social Science from the Bottom Up, MIT Press, 1996
Greene W, Econometric Analysis, Prentice Hall, 2007
Hensher DA, Rose JM, Greene WH, Applied Choice Analysis: A Primer, Cambridge UP, 2005
Long, JS, Regression Models for Categorical and Limited Dependent Variables, Sage Publications, 1997
Ortúzar JD, Willumsen LG, Modeling Transport, Wiley, 2001
Sterman J, Business Dynamics: Systems Thinking and Modeling for a Complex World, McGraw Hill, 2000
Train K, Discrete Choice Models with Simulation, Cambridge UP, 2009
Washington SP, Karlaftis MG, Mannering FL, Statistical and Econometric Methods for Transportation Data
Analysis, Chapman & Hall, 2003