Multiclass intermodal network model: The use of combined model on system evaluations.

摘要

United States transportation policy has generally addressed the negative economic and social effects of the standpoint of individual transportation modes and local government involvement. Therefore, there has been an increased focus on the development of intermodal transportation. Integrating the modes and using each of them to its best advantage are strategies to optimize the existing recourses and to create new capabilities.;According to the literature review performed in this research, the research in intermodal transportation system evaluation is far from mature. Most transportation performance measurements are focused on one mode rather than a whole network. In practice, the data necessary for evaluations are mostly from surveys or on-site data collection, which need a huge amount of time and cost. This study builds a combines intermodal network model and evaluation system specifically for intermodal transportation systems. It includes two main parts. The first part is to construct a combined network equilibrium model (CNEM) for multiclass travelers. Then the combined model projects mode split and traffic assignment/route choice simultaneously. The impact of transfer is being considered in the modeling process. The output if CNEM model is used to evaluate an intermodal transportation system in the aspects of social, economic, environmental and transferable.;After that, one real world case study is done to demonstrate the feasibility of the methodology and show the application process. The study area is located in north New Jersey. NJ Transit is interested in updating one freight line, North Branch Line, to provide passenger service. Assuming the O-D trip matrix already exist, the mode share and route choice are projected for no build and build conditions. The transportation system evaluations are done respectively. Through the comparison of no build and build conditions, transportation planners can see the usage of the new service and its impact on the overall system performance. In additional, sensitivity analysis in year 2015 and 2030 is done to present the long term effect. The application shows the methodology is very useful in transportation planning.