Efficient Extraction of Horizontal and Vertical Alignment Information for Roadways Using Public Data and Open Application Programming Interfaces

Document Type

Article

Publication Date

6-19-2024

Publication Title

Transportation Research Record, Transportation Research Record: Journal of the Transportation Research Board, Journal of the Transportation Research Board

DOI

10.1177/03611981241254117

ISSN

0361-1981

Abstract

An open-source program was developed to extract horizontal and vertical alignment information from roadways using public data and open application programming interfaces. The program employs unsupervised analysis to detect, segment, classify, and measure curves and tangents along an individual route or a network of connected routes. The algorithms used in the horizontal and vertical alignment analyses were described. For vertical alignment, the route was segmented based on the vertical grade profile using a data structure change method. Erratic vertical grade data points at bridges were detected and replaced with estimated values. Two validation cases are provided to demonstrate the function of the program. The first case is an 11.0 km Interstate highway route. The second case is a network of 13 connected routes at a highway interchange. A visual inspection of the results showed that the program was able to detect and measure horizontal and vertical alignment segments with reasonable accuracy. Occasional inaccuracies in the vertical alignment analysis were observed, mainly at short segments near bridges. The program was developed in the R language. The complete source code of the program is publicly accessible via a dedicated GitHub repository.

Comments

Georgia Southern University faculty member, Xiaoming Yang co-authored, "Efficient Extraction of Horizontal and Vertical Alignment Information for Roadways Using Public Data and Open Application Programming Interfaces."

Copyright

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