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Development of A Multi-Level Roadway Segmentation


The reliability and applicability of traffic operation and roadway safety analysis depend on their ability to integrate relevant input from disparate databases in a seamless and automated manner. These inputs include information on road geometry, traffic composition, accident profiles, and spatial referencing. These databases are collected by different agencies for essentially different purposes. As a result, they tend to lack a common definition of roadway segments for various applications. The objective of this paper is to create a systematic segmentation that considers the needs of various operational and planning studies. A multi-level segmentation methodology is developed to address different level of requirements for various studies: micro level, corresponding to the smallest roadway segmentation for traffic simulation studies; meso level, representing a combination of several micro segments, which corresponds to traffic operation studies; and macro level which corresponds to applications such as planning studies. The application of the proposed methodology is demonstrated for the segmentation of freeway and arterial corridors within the jurisdiction of the Ministry of Transportation Ontario’s (MTO) roadway network. The application of the proposed methodology is implemented for segmentation of selected freeway and arterial corridors in Ontario. At each level, a number of criteria were selected to identify the locations where the roadway network needs to be broken down. Once the segmentation methodology of the Ontario roadway network was developed, a pilot study was designed to test and evaluate the proposed methodology. The average historical operating speed was chosen as the measure of effectiveness to compare the proposed segmentation methodology with the MTO’s current interchange-to-interchange and intersection-to-intersection segmentation. It was found that the new segmentation methodology is able to fully represent the operational performance of the freeway and arterial corridors and identify the areas of congestion and queue growth / dissipation. The results of this study will assist road agencies in defining a systematic roadway segmentation that can be utilized for different types of initiatives, ranging from traffic operation to planning studies.

Conference Paper Details

Session title:
How Will "Big Data" Help Us Make Transportation More Efficient
Omrani, R.
Nikolic, G.
Izadpanah, P.
Hadayeghi, A.