This thesis proposes two sub-components in MSTM to incorporate more advanced methods in four-step models. The first addresses travel time reliability by proposing a method to measure the value, to forecast, and to incorporate reliability in the transportation planning process. Empirically observed travel time data from INRIX are used in an introduced method to measure OD-based reliability. The measured reliability is utilized to find the value of reliability for a specific mode choice problem and to establish the relationship between travel time and reliability. Findings are combined with MSTM to find the economic benefits of improving the network in a case study. The second addresses the peak spreading. Discrete choice models are combined with MSTM to model departure time choice. A method is introduced to estimate preferred arrival time of travelers based on skim values. Two iterative frameworks are proposed to estimate the model and predict the demand distribution.