ALL THE ASPECTS OF TRANSPORTATION SYSTEMS ENGINEERING ARE DEVELOPED WITH REFERENCE TO THE MOST INNOVATIVE MATHEMATICAL MODELS. THE GOAL IS TO OBTAIN THE MOST ADVANCED SKILLS FOR THE SIMULATION OF TRANSPORT SUPPLY AND DEMAND, AND THEIR INTERACTIONS. THE COURSE PROVIDES AN OVERALL FRAMEWORK OF TRANSPORT MODELS TO BE ADOPTED FOR THE DESIGN AND EVALUATION OF TRANSPORT SYSTEMS PLANNING.
Curriculum
teacher profile teaching materials
Travel Demand. Behavioural models based on random utility theory: Multinomial Logit, Nested Logit, Cross-Nested Logit, Probit.
Systematic utility formulation. Additive property. Logsum property. Calibration of behavioural models. Aggregation.
Four steps models: emission, distribution, modal shift, route choice.
Assignment models. Travel demand estimation based on traffic counts. Within-day dynamic models.
Programme
Transport System Definition. Modelling approach to transport systems. Supply system. Supply system modelling.Travel Demand. Behavioural models based on random utility theory: Multinomial Logit, Nested Logit, Cross-Nested Logit, Probit.
Systematic utility formulation. Additive property. Logsum property. Calibration of behavioural models. Aggregation.
Four steps models: emission, distribution, modal shift, route choice.
Assignment models. Travel demand estimation based on traffic counts. Within-day dynamic models.
Core Documentation
“Transportation Systems Analysis. Models and Applications” (E. Cascetta, Springer, 2009) teacher profile teaching materials
Travel Demand. Behavioural models based on random utility theory: Multinomial Logit, Nested Logit, Cross-Nested Logit, Probit.
Systematic utility formulation. Additive property. Logsum property. Calibration of behavioural models. Aggregation.
Four steps models: emission, distribution, modal shift, route choice.
Assignment models. Travel demand estimation based on traffic counts. Within-day dynamic models.
Programme
Transport System Definition. Modelling approach to transport systems. Supply system. Supply system modelling.Travel Demand. Behavioural models based on random utility theory: Multinomial Logit, Nested Logit, Cross-Nested Logit, Probit.
Systematic utility formulation. Additive property. Logsum property. Calibration of behavioural models. Aggregation.
Four steps models: emission, distribution, modal shift, route choice.
Assignment models. Travel demand estimation based on traffic counts. Within-day dynamic models.
Core Documentation
“Transportation Systems Analysis. Models and Applications” (E. Cascetta, Springer, 2009)