Transportation Demand Modeling

Recommended Prerequisites

Not applicable.

Teaching Methods

Lectures combining theoretical explanations with exercise solving and with conceptual and real-case discussions.

Learning Outcomes

Provide students with a deep knowledge and with advanced R&D skills and competences on the subject of transport demand modeling.

Work Placement(s)

No

Syllabus

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.

Head Lecturer(s)

Anabela Salgueiro Narciso Ribeiro

Assessment Methods

Assessment
Home assignments and written final exam: 100.0%

Bibliography

Axelrod R, The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration, Princeton
UP, 1997
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