Curves represent the most interesting element to be analyzed when evaluating the operational and safety effects of road geometrics. Despite the existence of several static and dynamic survey techniques, the correct identification of curves and the interpretation of spatial data fromhorizontal road alignment surveys still present a challenge. This paper presents the results of an investigation into the effects of both accuracy and sampling frequency (i.e., the interval between data points) of alignment spatial data on the identification of the radius and center of curvature. In pursuit of this objective, the authors adopted an original approach consisting of the generation of dispersed spatial data points from circular arcs with known characteristics. The least-squares, Huber, and Landau methods were used to back-calculate the radius and the coordinates of the center of curvature and to assess the effects of accuracy and interval between data points. The results obtained quantified the effects of accuracy, interval between points, radius magnitude, and length of circular arc on the identification of circular arcs. In support of future survey activities, considerations regarding the accuracy of measurements, the sampling frequency, and arc characteristics (i.e., length, radius) are discussed in the paper.
Identification of Horizontal Circular Arc from Spatial Data Sources / Bassani, Marco; Marinelli, Giuseppe; Piras, Marco. - In: JOURNAL OF SURVEYING ENGINEERING-ASCE. - ISSN 0733-9453. - ELETTRONICO. - (2016), pp. 04016013-1-04016013-14. [10.1061/(ASCE)SU.1943-5428.0000186]
Identification of Horizontal Circular Arc from Spatial Data Sources
BASSANI, Marco;MARINELLI, GIUSEPPE;PIRAS, MARCO
2016
Abstract
Curves represent the most interesting element to be analyzed when evaluating the operational and safety effects of road geometrics. Despite the existence of several static and dynamic survey techniques, the correct identification of curves and the interpretation of spatial data fromhorizontal road alignment surveys still present a challenge. This paper presents the results of an investigation into the effects of both accuracy and sampling frequency (i.e., the interval between data points) of alignment spatial data on the identification of the radius and center of curvature. In pursuit of this objective, the authors adopted an original approach consisting of the generation of dispersed spatial data points from circular arcs with known characteristics. The least-squares, Huber, and Landau methods were used to back-calculate the radius and the coordinates of the center of curvature and to assess the effects of accuracy and interval between data points. The results obtained quantified the effects of accuracy, interval between points, radius magnitude, and length of circular arc on the identification of circular arcs. In support of future survey activities, considerations regarding the accuracy of measurements, the sampling frequency, and arc characteristics (i.e., length, radius) are discussed in the paper.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2640859
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