"This book examines contemporary transportation issues through the lens of various modes of transportation (aviation and airports, inland and short sea shipping, public transit and more) while also focusing on the importance of sustainability, urban planning, and funding. All chapters will provide managerial and policy focus to contemporary transportation issues."
To expand GIS abilities to the consideration of decision criteria, OR/MS researchers strongly pronounce in favor of developing synergies between GIS and multicriteria decision making tools. The rationale of this integration is the GIS ability to store and manage and visualize geographically referenced data and the efficiency of Operational Research tools for modeling decision problems. As a result, MultiCriteria Spatial Decision Support Systems (MC-SDSS) provide a consistent framework that allows alternatives' ranking combining both spatial data and DMs preferences according to a selected decision rule. Regarding to their applicability in situations that involve classification, multiattribute decision models are considered as a very attractive procedure in urban and regional planning concerning the appraisal of transportation infrastructure construction. In the present a spatial multicriteria evaluation of the impacts derived by the realization of Egnatia Motorway is performed. Egnatia Motorway is considered one of the most significant interventions that have taken place in Greece during the early pre-Olympic Games period and up to the year 2007. With a length of 670 km, it crosses 12 prefectures starting from the Igoumenitsa Port, which provides links by boat to Italy, ending to Kipi in Evros (Greek-Turkish borders). It is a dual carriageway with two traffic lanes per direction with an overall construction cost of about 6b€. Aiming to enrich Northern Greece's potential in transport industry and tourism, European Union has heavily invested in its construction. In the present paper an integration among GIS functionalities and multi-attribute decision making models such as Analytic Hierarchy Process (AHP) and Ideal Point Methods is proposed in order to estimate the impacts provoked by the construction and operation of Egnatia Motorway in regional level.
To expand GIS abilities to the consideration of decision criteria, OR/MS researchers strongly pronounce in favor of developing synergies between GIS and multicriteria decision making tools. The rationale of this integration is the GIS ability to store and manage and visualize geographically referenced data and the efficiency of Operational Research tools for modeling decision problems. As a result, MultiCriteria Spatial Decision Support Systems (MC-SDSS) provide a consistent framework that allows alternatives' ranking combining both spatial data and DMs preferences according to a selected decision rule. Regarding to their applicability in situations that involve classification, multiattribute decision models are considered as a very attractive procedure in urban and regional planning concerning the appraisal of transportation infrastructure construction. In the present a spatial multicriteria evaluation of the impacts derived by the realization of Egnatia Motorway is performed. Egnatia Motorway is considered one of the most significant interventions that have taken place in Greece during the early pre-Olympic Games period and up to the year 2007. With a length of 670 km, it crosses 12 prefectures starting from the Igoumenitsa Port, which provides links by boat to Italy, ending to Kipi in Evros (Greek-Turkish borders). It is a dual carriageway with two traffic lanes per direction with an overall construction cost of about 6b€. Aiming to enrich Northern Greece's potential in transport industry and tourism, European Union has heavily invested in its construction. In the present paper an integration among GIS functionalities and multi-attribute decision making models such as Analytic Hierarchy Process (AHP) and Ideal Point Methods is proposed in order to estimate the impacts provoked by the construction and operation of Egnatia Motorway in regional level.
A letter report issued by the General Accounting Office with an abstract that begins "Pursuant to a legislative requirement, GAO assessed the impact that delays in relocating utilities are having on the delivery and cost of federal-aid highway and bridge projects, focusing on the: (1) extent to which states are experiencing such delays and the causes and impacts of the delays; (2) number of states that are compensating construction contractors for the added costs incurred on their projects because of untimely relocations by utility companies; (3) available technologies, such as subsurface utility engineering; and (4) mitigation methods that states are using, such as incentives, penalties, and litigation, to encourage or compel cooperation by utility companies that are relocating utilities on federal-aid highway and bridge projects."
A letter report issued by the General Accounting Office with an abstract that begins "Pursuant to a legislative requirement, GAO provided information on federal and state efforts to assess the conditions of the nation's highways, focusing on: (1) the uses the Federal Highway Administration (FHwA), the states, and others make of the International Roughness Index to assess highway conditions; (2) the consistency and accuracy of state-reported data on highway roughness; and (3) FHwA's efforts to improve the data across states."
Iowa is a state rich in renewable energy resources, especially biomass. The successful development of renewable energy industry in Iowa is concomitant with increase in freight traffic and is likely to have significant impacts on transportation infrastructure condition and increased maintenance expenses for the state and local governments. The primary goal of this paper is to investigate the feasibility of employing the Neural Networks (NN) methodology to forecast the impacts of Iowa's biofuels and wind power industries on Iowa's secondary and local road condition and maintenance-related costs in a panel data framework. The data for this study were obtained from a number of sources and for a total of 24 counties in clusters in Northern, Western, and Southern Iowa over a period of ten years. Back-Propagation NN (BPNN) using a Quasi-Newton secondorder training algorithm was chosen for this study owing to its very fast convergence properties. Since the size of the training set is relatively small, ensembles of well-trained NNs were formed to achieve significant improvements in generalization performance. The developed NN forecasting models could identify the presence of biofuel plants and wind farms as well as large-truck traffic as the most sensitive inputs influencing pavement condition and granular and blading maintenance costs. Pavement deterioration resulting from traffic loads was found to be associated with the presence of both biofuel plants and wind farms. The developed NN forecasting models can be useful in identifying and properly evaluating future transportation infrastructure impacts resulting from the renewable energy industry development and thus help Iowa maintain its competitive edge in the rapidly developing bioeconomy.
"February 1997." ; "Report to the Chairman, Subcommittee on Oversight of Government Management, Restructuring and the District of Columbia, Committee on Governmental Affairs, U.S. Senate." ; Running title: Managing the costs of highway projects. ; Cover title. ; Includes bibliographical references. ; Mode of access: Internet.
Many American cities were designed with the automobile in mind, a prioritization that has often led to congestion and pollution. How then, can we move away from our reliance on the car in our cities? In new research which examines transport policies in Boulder, Colorado over a twenty year period, researchers at the University of Colorado found that when the city government increased the 'supply' of infrastructure for bikes, pedestrians and other forms of sustainable transit, single-occupancy auto-use fell by nearly 10 percent. Lead author, Alejandro Henao, argues that other cities can learn from Boulder's focus on developing policies and infrastructure that expand the number and capacity of sustainable transportation choices.
