Civil & Environmental Engineer
CIVE 7381: Transportation Demand Forecasting and Model Estimation
Lecture - 4 credits
- Studies methods used for model estimation, model building, and interpretation of results.
- Emphasizes travel demand forecasting, including trip generation, distribution, model choice, and route choice.
- Topics include aggregate and disaggregate models, including discrete choice (binary and multinomial logit and extensions), model building and statistical testing, aggregation, sampling, and sample design.
- Demonstrates the applicability and underlying principles of the various models through case studies with focus on practical aspects and interpretation.
- Bases main methodological approaches on econometric methods, mainly on regression modeling and maximum likelihood estimation.
- Uses general and specialized software tools for data analysis and model estimation.
- While the focus is on estimating transportation demand models, the methods are applicable to a broad class of applications in engineering, marketing, etc.
Studies methods used for model estimation, model building, and interpretation of results. Show more.