Evaluating highway capacity investments using a geographic information systems-based tool: Trip-based full marginal cost approach

K Ozbay, O Yanmaz-Tuzel… - Transportation …, 2007 - journals.sagepub.com
K Ozbay, O Yanmaz-Tuzel, S Mudigonda, B Bartin
Transportation research record, 2007journals.sagepub.com
This paper presents an interactive computer tool based on geographic information systems
(GIS) and developed for the evaluation and analysis of full marginal costs (FMC) of highway
transportation in New Jersey. The first part of the paper is concerned with the
implementation of a trip-based FMC estimation methodology in the GIS environment. A
constrained k-shortest-path algorithm is proposed to estimate the trip-based FMC of a trip
along not only the shortest travel time path but also a set of feasible paths between each …
This paper presents an interactive computer tool based on geographic information systems (GIS) and developed for the evaluation and analysis of full marginal costs (FMC) of highway transportation in New Jersey. The first part of the paper is concerned with the implementation of a trip-based FMC estimation methodology in the GIS environment. A constrained k-shortest-path algorithm is proposed to estimate the trip-based FMC of a trip along not only the shortest travel time path but also a set of feasible paths between each origin-destination (O-D) pair that can be attractive to the travelers. The second part of the paper deals with estimation of various transportation cost categories, including vehicle operation, congestion, accident, air pollution, noise, and maintenance. This estimation uses New Jersey-specific data. The methodology is then implemented in ArcGIS, with the use of Visual Basic and C-programming language. The developed GIS-based tool not only estimates FMC between a selected O-D pair but also compares complete and partial networks to assess short-term impacts of infrastructure investments on the FMC. The proposed tool will help planners to calculate true trip costs between different O-D pairs for various user-defined scenarios of various demand and supply changes.
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