Commercial floating car data (FCD) is being increasingly used as a traffic data source due to its lower cost despite concerns about its reliability. This paper focuses on the evaluation of FCD speed quality as a surrogate measure for arterial speed from different aspects. First, FCD speed is compared to video-based traffic data, collected from a specific urban road segment and assumed as ground truth in (a) descriptive evaluations, (b) speed estimation, and (c) level of service estimation. Regression analysis carried out to derive transformation function between two datasets showed a nonlinear relation with a high correlation coefficient of 0.82. Working with data along an urban corridor of 3.6 km also showed that despite some outliers, FCD was capable of detecting peak-hour queue formations as well as incident related ones. Use of transformation function on FCD speeds helped to increase its potential in urban traffic monitoring.
Finalising the vertical alignment of a highway geometric design is a critical phase in a highway project and directly affects its construction cost. Generally, a vertical alignment performed by even an experienced designer and conforming to the specifications is sub-optimum unless it has been modified properly to minimise the earthwork cost. This paper proposes use of the mesh adaptive direct search approach to establish a nearly optimum vertical alignment based on a designer's alignment by moving points of vertical intersections. The method is applied during the design process in a building information modelling environment by a module developed and integrated in AutoCAD Civil 3D software, the aims being to increase the applicability of the method and obtain accurate earthwork volumes. The numerical results showed earthwork costs reduced by as much as 27% by slight adjustments to the vertical alignments of three virtual roads and a real highway project. According to the results, applying the method practically in the design process could save millions in various highway projects.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.