1. Introduction to quantitative methods.
2. Databases.
3. Linear and logistic regression.
4. Surveys of declared and revealed preference.
5. Discrete choice models.
6. Time series analysis.
7. Optimisation problems.
8. Software demonstration.

Learning Outcomes

With the successful completion of the course, the student will be able to:

• Identify the basic quantitative methods in transportation problems.
• Solve transportation problems using quantitative methods.
• Manage traffic and transportation data databases.
• Use software to solve transportation problems.