This thesis investigates two main aspects of air transportation system, demand and capacity. The first study aims to estimate the potential market for Zip Vehicles, an advanced commuter type of aircraft equipped with automation and electric propulsion technologies. A Multinomial Logit Model was developed to estimate the mode choice behavior of commuters between Zip vehicle, auto and transit in seven metropolitan areas in the United States. The results showed that the Out-of-Vehicle travel time plays an important role in the decision process of commuters. Zip Vehicle is predicted to achieve residual demand with the current technologies and could become more competitive if it was equipped with Vertical Take-Off Technology. The second study developed a hybrid airport runway capacity model that blends both deterministic and simulation techniques. The model includes a graphic user interface that allows high degree of freedom to modify input parameters, such as airport information, weather conditions, minimum separation distances and aircraft grouping system. The model is widely validated and it appears to be a consistent solution for estimating airport capacity at different levels and with various degree of extensibility. / Master of Science