Abstract:Rural roads represent an important part of the economy in the Great Plains and Midwest of the United States. As oil exploration in North Dakota increases, the number of vehicles travelling on these roads is also increasing, resulting in significant needs for infrastructure maintenance and upgrades, including the construction of new bridges. The lifecycle benefit-cost analysis of bridge construction is the overall objective of this research. This paper investigates the benefits of combining travel demand modeling and lifecycle benefit-cost analysis, and demonstrates traffic forecasting using geographic information systems (GIS) and network flow problem. The paper also shows a comparison of the alternative scenarios. The authors demonstrate a method of integrating geographic information systems, operations research, and data analytics to estimate future traffic by evaluating infrastructure needs. The travel demand modeling is essential for the lifecycle benefit-cost analysis. This study would help government agencies and construction companies evaluate and prioritize new bridge construction projects. The agencies should consider adding the environmental costs.

The purpose of this paper is to review logistics concepts used in macro freight transportation modeling by various planning agencies at the national, state and city level. The chronological development of freight modeling endeavors are studied here and the logistics component incorporated in the modeling is identified. The key modeling tools are identified and analyzed to identify the efficacy of the model, ease of use, and data required to implement the model. The conclusion was that European freight models were more developed than North American freight models. The tools most widely used are the aggregate-disaggregate-aggregate model, input-output model, artificial neural network model, matrix estimation method and PCOD model. This paper will give transportation modelers a better idea of the freight modeling tools available.