The motivation of conducting transportation planning is straightforward for everyone to understand. The travel pattern for an urban region (city) in the future is going to be different when compared to the present-day situation. The shift in travel patterns is almost happening every day and everywhere, not to mention the situation in the future. Through transportation planning, we may invest in new facilities or revising the current ones. Planning will help us put a transportation system in place which can take care of these needs. In order to understand the process of transportation planning, this course arranges eleven chapters. The main contents include the introduction to this course, the overview of travel demand modeling, the regression models for forecasting trip generation and its application, the gravity models and growth factor models, the mode choice models, the mathematical modeling methods of network assignment and the concept of OD estimation. The teaching team is from Beijing Jiaotong University and the teachers have an internationalized background toward the studies and research in the field of transportation planning.

The objective of this course is to convey basic knowledge, especially the methodological aspects of transportation planning. The focus of this course is traditional trip-based planning techniques. The students are expecting to understand the basic knowledge of transportation planning and grasp the process of travel demand forecasting.

1. Introduction to traffic engineering

2. Calculus

3. Probability and statistics
   

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2. Martin, W.A. and McGuckin, N.A. (1998) Travel Estimation Techniques for Urban Planning, National Cooperative Highway Research Program Report 365, Transportation Research Board

3. Meyer, M.D. and Miller, E.J. (2001) Urban Transportation Planning: A Decision-Oriented Approach (second edition), McGraw-Hill, NY, USA.

4. Hensher, D.A. and Button. K.J. [ed] (2000) Handbook of Transport Modeling, Pergamon Publishing

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Patriksson, M. (1994) The Traffic Assignment Problem—Model and Methods, Sweden