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Journal Article

Citation

Jamaleddin K, Kaysi I. Transp. Res. Rec. 2018; 2672(39): 142-154.

Copyright

(Copyright © 2018, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.1177/0361198118781664

PMID

unavailable

Abstract

An interchange is a road junction that typically uses grade separation to accommodate different volumes of traffic safely and efficiently through interconnecting roads. There are many types of interchanges, each of which has different characteristics and applications. In this paper, a prioritization framework is proposed for selecting a suitable interchange type based on a variety of performance measures, including operational performance, socio-environment, safety, and cost. The assessment is based on a multi-criteria analysis (MCA) approach. The relative importance of the criteria is obtained using the Analytic Hierarchy Process (AHP) whereby the weights of the criteria are derived using multilevel hierarchic structures. Consequently, using a linear additive model, each alternative is evaluated on a set of criteria derived from several objectives. This paper illustrates the implementation of the proposed framework in a case study of an urban interchange in the city of Riyadh. This research study considers three interchanges in the analysis to demonstrate the procedure; other interchange forms may also be appropriate at the site used in the study. This research helps in defining the criteria that play a significant role in determining the preferred design alternative, and the extent to which each of these criteria has an effect on the overall priority of a certain interchange configuration. The results of the study showed that the Diverging Diamond Interchange (DDI) outperformed its interchange counterparts and was chosen as the most preferred interchange configuration. The Single Point Urban Interchange (SPUI) ranked second while the Tight Urban Diamond (TUDI) was least preferred. Sensitivity analysis was undertaken to determine the impact of changes in criteria scoring or weights on the overall results, and revealed the robustness of the proposed model.


Language: en

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